11毕业设计论文外文翻译封面

第一篇：11毕业设计论文外文翻译封面

长江大学工程技术学院

毕业设计（论文）外文翻译

外 文 题 目

译 文 题 目 系部

专 业 班 级

学 生 姓 名

指 导 教 师

辅 导 教 师

完 成 日 期

AAAAAAAAAA BBBBBBBBBBB 信息系 计科60901班 某某某 某某某/教授 某某某/助教 2013年5月1日

第二篇：9、毕业设计(论文)外文资料翻译封面格式

南京工程学院

毕业设计(论文)外文资料翻译

原 文 题 目：原 文 来 源：学 生 姓 名：朱亚君学 号：231090410所在院(系)部：工业中心专 业 名 称：

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1、本封面中文字体为楷体三号；

2、原文来源栏填写原文期刊名称、发行时间等或原版书名称、出版

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4、将该翻译材料按封面－原文－译文顺序装订成册。）

第三篇：毕业设计(论文)外文翻译(原文)

毕业设计（论文）——外文翻译（原文）

NEWAPPLICATIONOFDATABASE

Relational databases have been in use for over two decades.A large portion of the applications of relational databases have been in the commercial world, supporting such tasks as transaction processing for banks and stock exchanges, sales and reservations for a variety of businesses, and inventory and payroll for almost of all companies.We study several new applications, which have become increasingly important in recent years.First.Decision-support system

As the online availability of data has grown, businesses have begun to exploit the available data to make better decisions about increase sales.We can extract much information for decision support by using simple SQL queries.Recently however, people have felt the need for better decision support based on data analysis and data mining, or knowledge discovery, using data from a variety of sources.Database applications can be broadly classified into transaction processing and decision support.Transaction-processing systems are widely used today, and companies have accumulated a vast amount of information generated by these systems.The term data mining refers loosely to finding relevant information, or “discovering knowledge,” from a large volume of data.Like knowledge discovery in artificial intelligence, data mining attempts to discover statistical rules and patterns automatically from data.However, data mining differs from machine learning in that it deals with large volumes of data, stored primarily on disk.Knowledge discovered from a database can be represented by a set of rules.We can discover rules from database using one of two models:

In the first model, the user is involved directly in the process of knowledge discovery.In the second model, the system is responsible for automatically discovering knowledge from the database, by detecting patterns and correlations in the data.Work on automatic discovery of rules has been influenced strongly by work in the artificial-intelligence community on machine learning.The main differences lie in the volume of data handled in databases, and in the need to access disk.Specialized data-mining algorithms have been developed to handle large volumes of disk-resident data efficiently.The manner in which rules are discovered depends on the class of data-mining application.We illustrate rule discovery using two application classes: classification and associations.Second.Spatial and Geographic Databases

Spatial databases store information related to spatial locations, and provide support for efficient querying and indexing based on spatial locations.Two types of spatial databases are particularly important:

Design databases, or computer-aided-design(CAD)databases, are spatial databases used to store design information about how objects---such as buildings, cars or aircraft---are constructed.Other important examples of computer-aided-design databases are integrated-circuit and electronic-device layouts.Geographic databases are spatial databases used to store geographic information, such as maps.Geographic databases are often called geographic information systems.Geographic data are spatial in nature, but differ from design data in certain ways.Maps and satellite images are typical examples of geographic data.Maps may provide not only location information-such

as boundaries, rivers and roads---but also much more detailed information associated with locations, such as elevation, soil type, land usage, and annual rainfall.Geographic data can be categorized into two types: raster data(such data consist a bit maps or pixel maps, in two or more dimensions.), vector data(vector data are constructed from basic geographic objects).Map data are often represented in vector format.Third.Multimedia Databases

Recently, there has been much interest in databases that store multimedia data, such as images, audio, and video.Today multimedia data typically are stored outside the database, in files systems.When the number of multimedia objects is relatively small, features provided by databases are usually not important.Database functionality becomes important when the number of multimedia objects stored is large.Issues such as transactional updates, querying facilities, and indexing then become important.Multimedia objects often have descriptive attributes, such as those indicating when they were created, who created them, and to what category they belong.One approach to building a database for such multimedia objects is to use database for storing the descriptive attributes, and for keeping track of the files in which the multimedia objects are stored.However, storing multimedia outside the database makes it harder to provide database functionality, such as indexing on the basis of actual multimedia data content.It can also lead to inconsistencies, such a file that is noted in the database, but whose contents are missing, or vice versa.It is therefore desirable to store the data themselves in the database.Forth.Mobility and Personal Databases

Large-scale commercial databases have traditionally been stored in central computing facilities.In the case of distributed database applications, there has usually been strong central database and network administration.Two technology trends have combined to create applications in which this assumption of central control and administration is not entirely correct:

1.The increasingly widespread use of personal computers, and, more important, of laptop or “notebook” computers.2.The development of a relatively low-cost wireless digital communication infrastructure, base on wireless local-area networks, cellular digital packet networks, and other technologies.Wireless computing creates a situation where machines no longer have fixed locations and network addresses.This complicates query processing, since it becomes difficult to determine the optimal location at which to materialize the result of a query.In some cases, the location of the user is a parameter of the query.A example is a traveler’s information system that provides data on hotels, roadside services, and the like to motorists.Queries about services that are ahead on the current route must be processed based on knowledge of the user’s location, direction of motion, and speed.Energy(battery power)is a scarce resource for mobile computers.This limitation influences many aspects of system design.Among the more interesting consequences of the need for energy efficiency is the use of scheduled data broadcasts to reduce the need for mobile system to transmit queries.Increasingly amounts of data may reside on machines administered by users, rather than by database administrators.Furthermore, these machines may, at times, be disconnected from the network.Summary

Decision-support systems are gaining importance, as companies realize the value of the on-line data collected by their on-line transaction-processing systems.Proposed extensions to SQL, such as the cube operation, help to support generation of summary data.Data mining seeks to discover

knowledge automatically, in the form of statistical rules and patterns from large databases.Data visualization systems help humans to discover such knowledge visually.Spatial databases are finding increasing use today to store computer-aided design data as well as geographic data.Design data are stored primarily as vector data;geographic data consist of a combination of vector and raster data.Multimedia databases are growing in importance.Issues such as similarity-based retrieval and delivery of data at guaranteed rates are topics of current research.Mobile computing systems have become common, leading to interest in database systems that can run on such systems.Query processing in such systems may involve lookups on server database.毕业设计（论文）——外文翻译（译文）

数据库的新应用

我们使用关系数据库已经有20多年了，关系数据库应用中有很大一部分都用于商业领域支持诸如银行和证券交易所的事务处理、各种业务的销售和预约，以及几乎所有公司都需要的财产目录和工资单管理。下面我们要研究几个新的应用，近年来它们变得越来越重要。

1、决策支持系统

由于越来越多的数据可联机获得，企业已开始利用这些可获得的数据来对自己的行动做出更好的决策，比如进什么货，以及如何最好的吸引顾客以提高销售额。我们可以通过使用简单的SQL查询语句提供大量用于决策支持的信息。但是，人们最近感到需要使用多种数据源的数据，以便在数据分析和数据挖掘（或知识发现）的基础上，更好的来做决策支持。

数据库应用从广义上可分为事务处理和决策支持两类。事务处理系统现在正被广泛使用，并且公司已经积累了大量由这类系统产生的信息。

数据挖掘这个概念广义上讲是指从大量数据中发现有关信息，或“发现知识”。与人工智能中的知识发现类似，数据挖掘试图自动从数据中发现统计规则和模式。但是，数据挖掘和机器学习的不同在于它处理的是大量数据，它们主要存储在磁盘上。

从数据库中发现的知识可以用一个规则集表示。我们用如下两个模型之一从数据库中发现规则：

● 在第一个模型中，用户直接参与知识发现的过程

● 在第二个模型中，系统通过检测数据的模式和相互关系，自动从数据库中发现知识。有关自动发现规则的研究很大程度上是受人工智能领域在知识学习方面研究的影响。其主要的区别在于数据库中处理的数据量，以及是否需要访问磁盘。已经有一些具体的数据挖掘算法用于高效地处理放在磁盘上的大量数据。

规则发现的方式依赖于数据挖掘应用的类型。我们用两类应用阐述规则发现：分类和关联。

2、空间和地理数据库

空间数据库存储有关空间位置的信息，并且对高效查询和基于空间位置的索引提供支持。有两种空间数据库特别重要：

● 设计数据库或计算机辅助设计（CAD）数据库是用于存储设计信息的空间数据库，这些信息主要是关于物体（如建筑、汽车或是飞机）是如何构造的。另一个计算机辅助设计数据库的重要例子是整合电路和电子设备设计图。

● 地理数据库是用于存储地理信息（如地图）的空间数据库。地理数据库常称为地理信息系统。

地理数据本质上是空间的，但与设计数据相比在几个方面有所不同。地图和卫星图像是地理数据的典型例子。地图不仅可提供位置信息，如边界、河流和道路，而且还可以提供许多和位置相关的详细信息，如海拔、土壤类型、土地使用和年降雨量。地理数据可以分为两类：光栅数据（这种数据由二维或更高维的位图或像素图组成）、矢量数据（由基本几何对象构成）。地图数据常以矢量形式表示。

3、多媒体数据库

最近，有关多媒体数据（如图像、声音和视频）的数据库的研究很热门。现在多媒体数据通常存储在数据库以外的文件系统中。当多媒体对象的数目相对较少时，数据库提供的特点往往不那么重要。但是当存储的多媒体对象数目较多时，数据库的功能就变得重要起来。总之，事务更新、查询机制和索引也开始变的很重要。多媒体对象常常有描述属性，如指明它们是何时创建的、谁创建的，以及它们属于哪一类。构造这种多媒体对象的数据库的方法之一是用数据存储描述属性，并且跟踪存储这些媒体对象的文件。

但是，将多媒体数据存储在数据库之外，使得难于提供数据库的功能，譬如基于实际多媒体数据内容的索引。此外这种情况还会造成不一致，譬如一个文件在数据库中做了记录，但其内容却丢失了；或其相反情况。因此我们更希望将数据本身存储在数据库中。

4、移动性和个人数据库

大型商用数据库传统上是存储在中央计算设备上的。在分布式数据库应用中，通常有强大的中央数据库和网络管理。然而以下这两个技术趋势的结合产生了一些应用，这些应用使中央控制和管理不再完全正确：

● 个人计算机越来越广泛的使用，其中更重要的 是便携式或“笔记本”计算机的使用。● 基于无限局域网、蜂窝数字包网络，以及其他技术成本相对低廉的无线数字通信基础设

施的发展。

无线计算使得计算机不必有固定的位置和网络地址这使得查询处理更加复杂，因为它难于决定实体化查询结果的最佳位置。某些情况下，用户的位置是一个查询参数。例如，一个旅客信息系统提供关于酒店、路边服务的信息及类似信息给乘车的旅客。有关当前道路前放服务的查询必须根据用户的位置、移动的方向及速度进行处理。

能源（电池能源）对应动计算机来说是有限的资源，这一限制影响了系统设计的许多方面。能源效率需求最有趣的结果之一的使用计划的数据广播来减少传输查询中移动系统的需求。越来越多的数据会放在由用户管理、而不是由数据库管理员管理的计算机上，并且这些计算机有时可能与网络断开连接。

5、总结

随着企业认识到联机事务处理系统收集的联机数据的价值，决策支持系统也越发变得重要了。现已提出SQL扩展，如cube操作，能帮助系统生成汇总数据。数据挖掘致力于从大数据库中自动发现统计规律和模式等知识。数据可视化系统帮助人们从视觉上发现这些知识。

目前，空间数据库正越来越多的被应用于存储计算机辅助设计数据和地理数据。设计数据基本上是以矢量数据的形式存储，而地理数据则包含矢量数据和光栅数据。

多媒体数据库正变得越来越重要。基于相似性的查询以及按可以确保的速率传送数据是当前研究的重要课题。

移动计算系统的普及使人们对这类系统上运行的数据库产生了浓厚的兴趣。在这类系统上的查询处理可能会设计在服务器端数据库上的查找。

第四篇：毕业设计外文翻译

外文原文

Overview of JSp Technology

Benefits of JSp

JSp pages are translated into servlets.So, fundamentally, any task JSp pages can perform could also be accomplished by servlets.However, this underlying equivalence does not mean that servlets and JSp pages are equally appropriate in all scenarios.The issue is not the power of the technology, it is the convenience, productivity, and maintainability of one or the other.After all, anything you can do on a particular computer platform in the Java programming language you could also do in assembly language.But it still matters which you choose.JSp provides the following benefits over servlets alone:

•It is easier to write and maintain the HTML.Your static code is ordinary HTML: no extra backslashes, no double quotes, and no lurking Java syntax.•You can use standard Web-site development tools.Even HTML tools that know nothing about JSp can be used because they simply ignore the JSp tags.•You can divide up your development team.The Java programmers can work on the dynamic code.The Web developers can concentrate on the presentation layer.On large projects, this division is very important.Depending on the size of your team and the complexity of your project, you can enforce a weaker or stronger separation between the static HTML and the dynamic content.Now, this discussion is not to say that you should stop using servlets and use only JSp instead.By no means.Almost all projects will use both.For some requests in your project, you will use servlets.For others, you will use JSp.For still others, you will combine them with the MVC architecture.You want the appropriate tool for the job, and servlets, by themselves, do not complete your toolkit.Advantages of JSp Over Competing Technologies

A number of years ago, Marty was invited to attend a small 20-person industry roundtable discussion on software technology.Sitting in the seat next to Marty was James Gosling, inventor of the Java programming language.Sitting several seats away was a high-level manager from a very large software company in Redmond, Washington.During the discussion, the moderator brought up the subject of Jini, which at that time was a new Java technology.The moderator asked the manager what he thought of it, and the manager responded that it was too early to tell, but that it seemed to be an excellent idea.He went on to say that they would keep an eye on it, and if it seemed to be catching on, they would follow his company's usual “embrace and extend” strategy.At this point, Gosling lightheartedly interjected “You mean disgrace and distend.”

Now, the grievance that Gosling was airing was that he felt that this company would take technology from other companies and suborn it for their own purposes.But guess what? The shoe is on the other foot here.The Java community did not invent the idea of designing pages as a mixture of static HTML and dynamic code marked with special tags.For example, ColdFusion did it years earlier.Even ASp(a product from the very software company of the aforementioned manager)popularized this approach before JSp came along and decided to jump on the bandwagon.In fact, JSp not only adopted the general idea, it even used many of the same special tags as ASp did.So, the question becomes: why use JSp instead of one of these other technologies? Our first response is that we are not arguing that everyone should.Several of those other technologies are quite good and are reasonable options in some situations.In other situations, however, JSp is clearly better.Here are a few of the reasons.Versus.NET and Active Server pages(ASp)

.NET is well-designed technology from Microsoft.ASp.NET is the part that directly competes with servlets and JSp.The advantages of JSp are twofold.First, JSp is portable to multiple operating systems and Web servers;you aren't locked into deploying on Windows and IIS.Although the core.NET platform runs on a few non-Windows platforms, the ASp part does not.You cannot expect to deploy serious ASp.NET applications on multiple servers and operating systems.For some applications, this difference does not matter.For others, it matters greatly.Second, for some applications the choice of the underlying language matters greatly.For example, although.NET's C# language is very well designed and is similar to Java, fewer programmers are familiar with either the core C# syntax or the many auxiliary libraries.In addition, many developers still use the original version of ASp.With this version, JSp has a clear advantage for the dynamic code.With JSp, the dynamic part is written in Java, not VBScript or another ASp-specific language, so JSp is more powerful and better suited to complex applications that require reusable components.You could make the same argument when comparing JSp to the previous version of ColdFusion;with JSp you can use Java for the “real code” and are not tied to a particular server product.However, the current release of ColdFusion is within the context of a J2EE server, allowing developers to easily mix ColdFusion and servlet/JSp code.Versus pHp

pHp(a recursive acronym for “pHp: Hypertext preprocessor”)is a free, open-source, HTML-embedded scripting language that is somewhat similar to both ASp and JSp.One advantage of JSp is that the dynamic part is written in Java, which already has an extensive ApI for networking, database access, distributed objects, and the like, whereas pHp requires learning an entirely new, less widely used language.A second advantage is that JSp is much more widely supported by tool and server vendors than is pHp.Versus pure Servlets

JSp doesn't provide any capabilities that couldn't, in principle, be accomplished with servlets.In fact, JSp documents are automatically translated into servlets behind the scenes.But it is more convenient to write(and to modify!)regular HTML than to use a zillion println statements to generate the HTML.plus, by separating the presentation from the content, you can put different people on different tasks: your Web page design experts can build the HTML by using familiar tools and either leave places for your servlet programmers to insert the dynamic content or invoke the dynamic content indirectly by means of XML tags.Does this mean that you can just learn JSp and forget about servlets? Absolutely not!JSp developers need to know servlets for four reasons:

1.JSp pages get translated into servlets.You can't understand how JSp works without understanding servlets.2.JSp consists of static HTML, special-purpose JSp tags, and Java code.What kind of Java code? Servlet code!You can't write that code if you don't understand servlet programming.3.Some tasks are better accomplished by servlets than by JSp.JSp is good at generating pages that consist of large sections of fairly well structured HTML or other character data.Servlets are better for generating binary data, building pages with highly variable structure, and performing tasks(such as redirection)that involve little or no output.4.Some tasks are better accomplished by a combination of servlets and JSp than by either servlets or JSp alone.Versus JavaScript

JavaScript, which is completely distinct from the Java programming language, is normally used to dynamically generate HTML on the client, building parts of the Web page as the browser loads the document.This is a useful capability and does not normally overlap with the capabilities of JSp(which runs only on the server).JSp pages still include SCRIpT tags for JavaScript, just as normal HTML pages do.In fact, JSp can even be used to dynamically generate the JavaScript that will be sent to the client.So, JavaScript is not a competing technology;it is a complementary one.It is also possible to use JavaScript on the server, most notably on Sun ONE(formerly iplanet), IIS, and BroadVision servers.However, Java is more powerful, flexible, reliable, and portable.Versus WebMacro or Velocity

JSp is by no means perfect.Many people have pointed out features that could be improved.This is a good thing, and one of the advantages of JSp is that the specification is controlled by a community that draws from many different companies.So, the technology can incorporate improvements in successive releases.However, some groups have developed alternative Java-based technologies to try to address these deficiencies.This, in our judgment, is a mistake.Using a third-party tool like Apache Struts that augments JSp and servlet technology is a good idea when that tool adds sufficient benefit to compensate for the additional complexity.But using a nonstandard tool that tries to replace JSp is a bad idea.When choosing a technology, you need to weigh many factors: standardization, portability, integration, industry support, and technical features.The arguments for JSp alternatives have focused almost exclusively on the technical features part.But portability, standardization, and integration are also very important.For example, the servlet and JSp specifications define a standard directory structure for Web applications and provide standard files(.war files)for deploying Web applications.All JSp-compatible servers must support these standards.Filters can be set up to apply to any number of servlets or JSp pages, but not to nonstandard resources.The same goes for Web application security settings.Besides, the tremendous industry support for JSp and servlet technology results in improvements that mitigate many of the criticisms of JSp.For example, the JSp Standard Tag Library and the JSp 2.0 expression language address two of the most well-founded criticisms: the lack of good iteration constructs and the difficulty of accessing dynamic results without using either explicit Java code or verbose jsp:useBean elements.10.4 Misconceptions About JSp

Forgetting JSp Is Server-Side Technology

Here are some typical questions Marty has received(most of them repeatedly).•Our server is running JDK 1.4.So, how do I put a Swing component in a JSp page?

•How do I put an image into a JSp page? I do not know the proper Java I/O commands to read image files.•Since Tomcat does not support JavaScript, how do I make images that are highlighted when the user moves the mouse over them?

•Our clients use older browsers that do not understand JSp.What should we do?

•When our clients use “View Source” in a browser, how can I prevent them from seeing the JSp tags?

All of these questions are based upon the assumption that browsers know something about the server-side process.But they do not.Thus:

•For putting applets with Swing components into Web pages, what matters is the browser's Java version—the server's version is irrelevant.If the browser supports the Java 2 platform, you use the normal AppLET(or Java plug-in)tag and would do so even if you were using non-Java technology on the server.•You do not need Java I/O to read image files;you just put the image in the directory for Web resources(i.e., two levels up from WEB-INF/classes)and output a normal IMG tag.•You create images that change under the mouse by using client-side JavaScript, referenced with the SCRIpT tag;this does not change just because the server is using JSp.•Browsers do not “support” JSp at all—they merely see the output of the JSp page.So, make sure your JSp outputs HTML compatible with the browser, just as you would do with static HTML pages.•And, of course you need not do anything to prevent clients from seeing JSp tags;those tags are processed on the server and are not part of the output that is sent to the client.Confusing Translation Time with Request Time

A JSp page is converted into a servlet.The servlet is compiled, loaded into the server's memory, initialized, and executed.But which step happens when? To answer that question, remember two points:

•The JSp page is translated into a servlet and compiled only the first time it is accessed after having been modified.•Loading into memory, initialization, and execution follow the normal rules for servlets.Table 1 gives some common scenarios and tells whether or not each step occurs in that scenario.The most frequently misunderstood entries are highlighted.When referring to the table, note that servlets resulting from JSp pages use the _jspService method(called for both GET and pOST requests), not doGet or dopost.Also, for initialization, they use the jspInit method, not the init method.Table 1.JSp Operations in Various Scenarios

JSp page translated into servletServlet compiledServlet loaded into server's memoryjspInit called_jspService called

page first written

Request 1YesYesYesYesYes

Request 2NoNoNoNoYes

Server restarted

Request 3NoNoYesYesYes

Request 4NoNoNoNoYes

page modified

Request 5YesYesYesYesYes

Request 6NoNoNoNoYes

中文翻译

JSp技术概述

一、JSp的好处

JSp页面最终会转换成servler。因而，从根本上，JSp页面能够执行的任何任务都可以用servler来完成。然而，这种底层的等同性并不意味着servler和JSp页面对于所有的情况都等同适用。问题不在于技术的能力，而是二者在便利性、生产率和可维护性上的不同。毕竟，在特定平台上能够用Java编程语言完成的事情，同样可以用汇编语言来完成，但是选择哪种语言依旧十分重要。

和单独使用servler相比，JSp提供下述好处：

JSp中HTML的编写与维护更为简单。JSp中可以使用常规的HTML：没有额外的反斜杠，没有额外的双引号，也没有暗含的Java语法。

能够使用标准的网站开发工具。即使对那些对JSp一无所知的HTML工具，我们也可以使用，因为它们会忽略JSp标签（JSp tags）。

可以对开发团队进行划分。Java程序员可以致力于动态代码。Web开发人员可以将经理集中在表示层（presentation layer）上。对于大型的项目，这种划分极为重要。依据开发团队的大小，及项目的复杂程度，可以对静态HTML和动态内容进行弱分离（weaker separation）和强分离（stronger separation）。

在此，这个讨论并不是让您停止使用servlets，只使用JSp。几乎所有的项目都会同时用到这两种技术。针对项目中的某些请求，您可能会在MVC构架下组合使用这两项技术。我们总是希望用适当的工具完成相对应的工作，仅仅是servlet并不能填满您的工具箱。

二、JSp相对于竞争技术的优势

许多年前，Marty受到邀请,参加一个有关软件技术的小型(20个人)研讨会.做在Marty旁边的人是James Gosling---Java编程语言的发明者。隔几个位置,是来自华盛顿一家大型软件公司的高级经理。在讨论过程中,研讨会的主席提出了Jini的议题,这在当时是一项新的Java技术.主席向该经理询问他的想法.他继续说,他们会持续关注这项技术,如果这项技术变得流行起来,他们会遵循公司的“接受并扩充(embrace and extend)”的策略.此时, Gosling随意地插话说“你的意思其实就是不接受且不扩充(disgrace and distend)。”

在此, Gosling的抱怨显示出，他感到这个公司会从其他公司那里拿走技术,用于他们自己的目的.但你猜这次怎么样?这次鞋子穿在了另一只脚上。Java社团没有发明这一思想----将页面设计成由静态HTML和用特殊标签标记的动态代码混合组成.。ColdFusion多年前就已经这样做了。甚至ASp(来自于前述经理所在公司的一项产品)都在JSp出现之前推广了这种方式。实际上,JSp不只采用了这种通用概念,它甚至使用许多和ASp相同的特殊标签。

因此,问题变成:为什么使用JSp,而不使用其他技术呢?我们的第一反应是我们不是在争论所有的人应该做什么。其他这些技术中,有一些也很不错,在某些情况下也的确是合情合理的选择.然而,在其他情形中,JSp明显要更好一些。下面给出几个理由。

与.NET和Active Server pages(ASp)相比

.NET是Microsoft精心设计的一项技术。ASp.NET是与servlets和JSp直接竞争的技术。JSp的优势体现在两个方面。

首先,JSp可以移植到多种操作系统和Web服务器,您不必仅仅局限于部署在Windows 和IIS上尽管核心.NET平台可以在好几种非Windows平台上运行，但ASp这一部分不可以。您不能期望可以将重要的ASp.NET应用部署到多种服务器和操作系统。对于某些应用，这种差异没有什么影响。但有些应用，这种差异却非常重要。

其次，对于某些应用，底层语言的选择至关重要。例如，尽管.NET的C#语言设计优良，且和Java类似，但熟悉核心C#语法和众多工具库的程序员很少。此外,许多开发者依旧使用最初版本的ASp。相对于这个版本,JSp在动态代码方面拥有明显的优势。使用JSp,动态部分是用Java编写的,而非VBScript过其他ASp专有的语言,因此JSp更为强劲,更适合于要求组件重用的复杂应用。

当将JSp与之前版本的ColdFusion对比时，您可能会得到相同的结论。应用JSp，您可以使用Java编写“真正的代码”，不必依赖于特定的服务器产品。然而，当前版本的ColdFusion满足J2EE服务器的环境，允许开发者容易的混合使用ColdFusion和Servlet/JSp代码。

与pHp相比

pHp（“pHp：Hypertext preprocessor”的递归字母缩写词）是免费的、开放源代码的、HTML嵌入其中的脚本语言，与ASp和JSp都有某种程度的类似。JSp的一项优势是动态部分用Java编写，而Java已经在联网、数据库访问、分布式对象等方面拥有广泛的ApI，而pHp需要学习全新的、应用相对广泛的语言。JSp的第二项优势是，和pHp相比，JSp拥有极为广泛的工具和服务器提供商的支持。

与纯Servlet相比

原则上，JSp并没有提供Servlet不能完成的功能。实际上，JSp文档在后台被自动转换成Servlet。但是编写（和修改）常规的HTML，要比无数println语句生成HTML要方便得多。另外，通过将表示与内容分离，可以为不同的人分配不同的任务：网页设计人员使用熟悉的工具构建HTML，要么为Servlet程序员留出空间插入动态内容，要么通过XML标签间接调用动态内容。

这是否表示您只可以学习JSp，将Servlet丢到一边呢？当然不是！由于以下4种原因，JSp开发人员需要了解Servlet：

（1）JSp页面会转换成Servlet。不了解Servlet就无法知道JSp如何工作。

（2）JSp由静态HTML、专用的JSp标签和Java代码组成。哪种类型的Java代码呢？当然是Servlet代码！如果不了解Servlet编程，那么就无法编写这种代码。

（3）一些任务用Servlet完成比用JSp来完成要好。JSp擅长生成由大量组织有序的结构化HTML或其他字符数据组成的页面。Servlet擅长生成二进制数据，构建结构多样的页面，以及执行输出很少或者没有输出的任务（比如重定向）。

（4）有些任务更适合于组合使用Servlet和JSp来完成，而非单独使用Servlet或JSp。

与JavaScript相比

JavaScript和Java编程语言完全是两码事，前者一般用于在客户端动态生成HTML，在浏览器载入文档时构建网页的部分内容。这是一项有用的功能，一般与JSp的功能（只在服务器端运行）并不发生重叠。和常规HTML页面一样，JSp页面依旧可以包括用于JavaScript的SCRIpT标签。实际上，JSp甚至能够用来动态生成发送到客户端的JavaScript。因此，JavaScript不是一项竞争技术，它是一项补充技术。

JavaScript也可以用在服务器端，最因人注意的是SUN ONE（以前的iplanet）、IIS和BroadVision服务器。然而，Java更为强大灵活、可靠且可移植。

与WebMacro和Velocity相比

JSp决非完美。许多人都曾指出过JSp中能够改进的功能。这是一件好事，JSp的优势之一是该规范由许多不同公司组成的社团控制。因此，在后续版本中，这项技术能够得到协调的改进。

但是，一些组织已经开发出了基于Java的替代技术，试图弥补这些不足。据我们的判断，这样做是错误的。使用扩充JSp和Servlet技术的第三方工具，如Apache Structs，是一种很好的思路，只要该工具带来的好处能够补偿工具带来的额外复杂性。但是，试图使用非标准的工具代替JSp则不理想。在选择一项技术时，需要权衡许多方面的因素：标准化、可移植性、集成性、行业支持和技术特性。对于JSp替代技术的争论几乎只是集中在技术特性上，而可移植性、标准化和集成性也十分重要。例如，Servlet和JSp规范为Web应用定义了一个标准的目录结构，并提供用于部署Web应用的标准文件（.war文件）。所有JSp兼容的服务器必须支持这些标准。我们可以建立过滤器作用到任意树木的Servlet和JSp页面上，但不能用于非标准资源。Web应用安全设置也同样如此。

此外，业界对JSp和Servlet技术的巨大支持使得这两项技术都有了巨大的进步，从而减轻了对JSp的许多批评。例如，JSp标准标签库和JSp 2.0表达式语言解决了两种最广泛的批评：缺乏良好的迭代结构；不使用显式的Java代码或冗长的jsp:useBean元素难以访问动态结果。

三、对JSp的误解

忘记JSp技术是服务器端技术

下面是Marty收到的一些典型问题（大部分问题不止一次的出现）。

我们的服务器正在运行JDK1.4。我如何将Swing组件用到JSp页面中呢？

我如何将图像放到JSp页面中？我不知道读取图像文件应该使用哪些Java I/O命令。

Tomcat不支持JavaScript，当用户在图像上移动鼠标时，我如何使图像突出显示呢？

我们的客户使用不理解JSp的旧浏览器。我应该怎么做？

当我们的客户在浏览器中使用“View Source”（查看源代码）时，如何阻止他们看到JSp标签？

所有这些问题都基于浏览器对服务器端的过程在有所了解的假定之上。但事实上浏览器并不了解服务器端的过程。因此：

如果要将使用Swing组件的applet放到网页中，重要的是浏览器的Java版本，和服务器的Java版本无关。如果浏览器支持Java 2平台，您可以使用正常的AppLET（或Java插件）标签，即使在服务器上使用了非Java技术也须如此。

您不需要Java I/O来读取图像文件，您只需将图像放在存储Web资源的目录中（即WEB-INF/classes向上两级的目录），并输出一个正常的IMG标签。

您应该用SCRIpT标签，使用客户端JavaScript创建在鼠标下会更改的图像，这不会由于服务器使用JSp而改变。

浏览器根本不“支持”JSp----它们看到的只是JSp页面的输出。因此，如同对待静态HTML页面一样，只需确保JSp输出的HTML与浏览器兼容。

当然，您不需要采取什么措施来阻止客户看到JSp标签，这些标签在服务器上进行处理，发送给客户的输出中并不出现。

混淆转换期间和请求期间

JSp页面需要转换成servlet。Servlet在编译后，载入到服务器的内容中，初始化并执行。但是每一步发生在什么时候呢？要回答这个问题，要记住以下两点：

JSp页面仅在修改后第一次被访问时，才会被转换成servlet并进行编译；

载入到内存中、初始化和执行遵循servlet的一般规则。

表1列出一些常见的情形，讲述在该种情况下每一步是否发生。最常被误解的项已经突出标示出来。在参考该表时，要注意，由JSp页面生成的servlet使用_jspService方法（GET和pOST请求都调用该函数），不是doGet或dopost方法。同样，对于初始化，它们使用jspInit方法，而非init方法。

表1 各种情况下的JSp操作

将JSp 页面转换成servlet编译Servlet 将Servlet 载入到服务器内存中调用jspInit 调用_jspService

页面初次创建

请求 1有有有有有

请求 2无无无无有

服务器重启后

请求3无无有有有

请求 4无无无无有

页面修改后

请求 5有有有有有

请求 6无无无无有

第五篇：4毕业设计(论文)外文文献翻译范文

黄石理工学院毕业设计（论文）外文文献翻译

模糊控制理论

摘自 维基百科 2011年11月20日

概述

模糊逻辑广泛适用于机械控制。这个词本身激发一个一定的怀疑,试探相当于“仓促的逻辑”或“虚假的逻辑”,但“模糊”不是指一个部分缺乏严格性的方法,而这样的事实,即逻辑涉及能处理的概念,不能被表达为“对”或“否”,而是因为“部分真实”。虽然遗传算法和神经网络可以执行一样模糊逻辑在很多情况下,模糊逻辑的优点是解决这个问题的方法,能够被铸造方面接线员能了解,以便他们的经验,可用于设计的控制器。这让它更容易完成机械化已成功由人执行。

历史以及应用

模糊逻辑首先被提出是有Lotfi在加州大学伯克利分校在1965年的一篇论文。他阐述了他的观点在1973年的一篇论文的概念,介绍了语言变量”,在这篇文章中相当于一个变量定义为一个模糊集合。其他研究打乱了,第二次工业应用中,水泥窑建在丹麦,即将到来的在线1975。

模糊系统在很大程度上在美国被忽略了,因为他们更多关注的是人工智能，一个被过分吹嘘的领域，尤其是在1980年中期年代,导致在诚信缺失的商业领域。

然而日本人对这个却没有偏见和忽略，模糊系统引发日立的Seiji Yasunobu和Soji Yasunobu Miyamoto的兴趣。,他于1985年的模拟,证明了模糊控制系统对仙台铁路的控制的优越性。他们的想法是被接受了,并将模糊系统用来控制加速、制动、和停车，当线于1987年开业。

1987年另一项促进模糊系统的兴趣。在一个国际会议在东京的模糊研究那一年,Yamakawa论证<使用模糊控制,通过一系列简单的专用模糊逻辑芯片,在一个“倒立摆“实验。这是一个经典的控制问题,在这一过程中,车辆努力保持杆安装在顶部用铰链正直来回移动。

这次展示给观察者家们留下了深刻的印象,以及后来的实验,他登上一Yamakawa酒杯包含水或甚至一只活老鼠的顶部的钟摆。该系统在两种情况下,保持稳定。Yamakawa最终继续组织自己的fuzzy-systems研究实验室帮助利用自己的专利在田地里的时候。

黄石理工学院毕业设计（论文）外文文献翻译

展示之后,日本工程师开发出了大范围的模糊系统用于工业领域和消费领域的应用。1988年,日本建立了国际模糊工程实验室,建立合作安排48公司进行模糊控制的研究。

松下吸尘器使用微控制器运行模糊算法去控制传感器和调整吸尘力。日立洗衣机用模糊控制器Load-Weight,Fabric-Mix和尘土传感器及自动设定洗涤周期来最佳利用电能、水和洗涤剂。

佳能研制出的一种上相机使用电荷耦合器件(CCD)测量中的图像清晰的六个区域其视野和使用提供的信息来决定是否这个影像在焦点上(清晰)。它也可以追踪变化的速率在镜头运动的重点,以及它的速度以防止控制超调。相机的模糊控制系统采用12输入,6个输入了解解现行清晰所提供的数据和其他6个输入测量CCD镜头的变化率的运动。输出的位置是镜头。模糊控制系统应用13条规则,需要1.1 千字节记忆信息。

另外一个例子是,三菱工业空调设计采用25加热规则和25冷却规则。温度传感器提供输入,输出一个控制逆变器,一个压缩机气阀,风扇电机。和以前的设计相比,新设计的模糊控制器增加五次加热冷却速度,降低能耗24%,增加温度稳定性的一个因素两个,使用较少的传感器。

日本人对模糊逻辑的人情是反映在很广泛的应用范围上,他们一直在研究或实现:例如个性和笔迹识别光学模糊系统,机器人,声控机器人直升飞机。

模糊系统的相关研究工作也在美国和欧洲进行着。美国环境保护署分析了模糊控制节能电动机,美国国家航空和宇宙航行局研究了模糊控制自动太空对接。仿真结果表明,模糊控制系统可大大降低燃料消耗。如波音公司、通用汽车、艾伦-布拉德利、克莱斯勒、伊顿,和漩涡了模糊逻辑用于低功率冰箱、改善汽车变速箱。在1995年美泰克公司推出的一个“聪明” 基于模糊控制器洗碗机，“一站式感应模块”包括热敏电阻器,用来温度测量;电导率传感器,用来测量离子洗涤剂水平存在于洗;分散和浊度传感器用来检测透射光测量失禁的洗涤,以及一个磁致伸缩传感器来读取旋转速率。这个系统确定最优洗周期任何载荷,获得最佳的结果用最少的能源、洗涤剂、和水。

研究和开发还继续模糊应用软件,作为反对固件设计,包括模糊专家系统模糊逻辑与整合神经网络和所谓的自适应遗传软件系统,其最终目的是建立“自主学习”模糊控制系统。

黄石理工学院毕业设计（论文）外文文献翻译

模糊集

输入变量在一个模糊控制系统是集映射到一般由类似的隶属度函数,称为“模糊集”。转换的过程中,一个干脆利落的输入值模糊值称为“模糊化”。

一个控制系统也有各种不同的类型开关或“开关”,连同它的模拟输入输入,而这样的开关输入当然总有一个真实的价值等于要么1或0,但该方案能对付他们,简单的模糊函数,要么发生一个值或另一个。

赋予了“映射输入变量的隶属函数和进入真理价值,单片机然后做出决定为采取何种行动基于一套“规则”,每一组的形式。

在一个例子里,有两个输入变量是“刹车温度”和“速度”,定义为模糊集值。输出变量,“制动压力” ,也定义为一个模糊集,有价值观像“静”、“稍微增大” “略微下降”,等等。

这条规则本身很莫名其妙,因为它看起来好像可以使用，会干扰到与模糊,但要记住,这个决定是基于一套规则。

所有的规则都调用申请,使用模糊隶属度函数和诚实得到输入值,确定结果的规则。这个结果将被映射成一个隶属函数和控制输出变量的真值。

这些结果相结合,给出了具体的(“脆”)的答案,实际的制动压力,一个过程被称为解模糊化，结合了模糊操作规则 “推理“描述”模糊专家系统”。

传统的控制系统是基于数学模型的控制系统,描述了使用一个或更多微分方程确定系统回应其输入。这类系统通常被作为“PID控制器”他们是产品的数十年的发展建设和理论分析,是非常有效的。

如果PID和其他传统的控制系统是如此的先进,何必还要模糊控制吗?它有一些优点。在许多情况下,数学模型的控制过程可能不存在,或太“贵”的认识论的计算机处理能力和内存,与系统的基于经验规则可能更有效。

此外,模糊逻辑都适合低成本实现基于廉价的传感器、低分辨率模拟/数字转换器,或8位单片机芯片one-chip 4比特。这种系统可以很容易地通过增加新的规则升级来提高性能或添加新功能。在许多情况下,模糊控制可以用来改善现有的传统控制器系统通过增加了额外的情报电流控制方法。

模糊控的细节

模糊控制器是很简单的理念上。它们是由一个输入阶段,一个处理阶段,一个输

黄石理工学院毕业设计（论文）外文文献翻译

出阶段。地图传感器输入级或其他输入,比如开关等等,到合适的隶属函数和真理的价值。每一个适当的加工阶段调用规则和产生的结果对每个人来说,然后结合结果的规则。最后,将结果输出阶段相结合的具体控制输出回他的价值。

最常见的形状是三角形的隶属度函数,尽管梯形和贝尔曲线也使用,但其形状通常比数量更重要曲线及其位置。从三人至七人通常是适当的覆盖曲线所需要的范围的一个输入值,或“宇宙的话语“在模糊术语。

作为讨论之前,加工阶段是基于规则的集合的形式逻辑IFThen规则。作为一个例子,解释一个规则,因为如果(温度是“冷”),那么(加热器是“高”)由第一阶表达式冷(x)→高(y)和假设r是一个输入这样冷(r)是假的。然后公式冷(r)→高(t)是适用于任何一个师,因此任何不正确的控制提供了一种给r。很明显,如果我们考虑系统的先例的规则类定义一个分区这样一个自相矛盾的现象不会出现。在任何情况下它有时是不考虑两个变量x和y在一条规则没有某种功能的依赖。严谨的逻辑正当化中给出的模糊控制Hajek的书,被描绘成一个模糊控制理论的基本Hajek逻辑。在2005 Gerla模糊控制逻辑方法,提出了一种基于以下的想法。f模糊函数表示的系统与模糊控制相结合,即:给定输入r,s(y)f(r,y)是模糊集合可能的输出。然后给出一个可能的输出的t,我们把f(r,t)为真理程度的表示。更多的是任何系统的If-Then规则可转化为一个模糊的程序,在这种情况下模糊函数f模糊谓词的解释很好(x,y)在相关的最小模糊Herbrand

模型。以这样一种方式成为一个章模糊控制的模糊逻辑编程。学习过程成为一个问题属于归纳逻辑理论。

黄石理工学院毕业设计（论文）外文文献翻译

Fuzzy Control From Wikipedia November 2011

Overview

Fuzzy logic is widely used in machine control.The term itself inspires a certain skepticism, sounding equivalent to ”half-baked logic“ or ”bogus logic“, but the ”fuzzy“ part does not refer to a lack of rigour in the method, rather to the fact that the logic involved can deal with concepts that cannot be expressed as ”true“ or ”false“ but rather as ”partially true“.Although genetic algorithms and neural networks can perform just as well as fuzzy logic in many cases, fuzzy logic has the advantage that the solution to the problem can be cast in terms that human operators can understand, so that their experience can be used in the design of the controller.This makes it easier to mechanize tasks that are already successfully performed by humans.History and applications

Fuzzy logic was first proposed by Lotfi A.Zadeh of the University of California at Berkeley in a 1965 paper.He elaborated on his ideas in a 1973 paper that introduced the concept of ”linguistic variables“, which in this article equates to a variable defined as a fuzzy set.Other research followed, with the first industrial application, a cement kiln built in Denmark, coming on line in 1975.Fuzzy systems were largely ignored in the U.S.because they were associated with artificial intelligence, a field that periodically oversells itself, especially in the mid-1980s, resulting in a lack of credibility within the commercial domain.The Japanese did not have this prejudice.Interest in fuzzy systems was sparked by Seiji Yasunobu and Soji Miyamoto of Hitachi, who in 1985 provided simulations that demonstrated the superiority of fuzzy control systems for the Sendai railway.Their ideas were adopted, and fuzzy systems were used to control accelerating, braking, and stopping when the line opened in 1987.Another event in 1987 helped promote interest in fuzzy systems.During an international meeting of fuzzy researchers in Tokyo that year, Takeshi Yamakawa demonstrated the use of fuzzy control, through a set of simple dedicated fuzzy logic chips, in an ”inverted pendulum“ experiment.This is a classic control problem, in which a vehicle tries to keep a pole mounted on its top by a hinge upright by moving back and forth.Observers were impressed with this demonstration, as well as later experiments by Yamakawa in which he mounted a wine glass containing water or even a live mouse to the top of the pendulum.The system maintained stability in both cases.Yamakawa eventually went on to organize his own fuzzy-systems research lab to help exploit his patents in the field.Following such demonstrations, Japanese engineers developed a wide range of fuzzy systems for both industrial and consumer applications.In 1988 Japan established

黄石理工学院毕业设计（论文）外文文献翻译

the Laboratory for International Fuzzy Engineering(LIFE), a cooperative arrangement between 48 companies to pursue fuzzy research.Matsushita vacuum cleaners use micro controllers running fuzzy algorithms to interrogate dust sensors and adjust suction power accordingly.Hitachi washing machines use fuzzy controllers to load-weight, fabric-mix, and dirt sensors and automatically set the wash cycle for the best use of power, water, and detergent.Canon developed an autofocusing camera that uses a charge-coupled device(CCD)to measure the clarity of the image in six regions of its field of view and use the information provided to determine if the image is in focus.It also tracks the rate of change of lens movement during focusing, and controls its speed to prevent overshoot.The camera's fuzzy control system uses 12 inputs: 6 to obtain the current clarity data provided by the CCD and 6 to measure the rate of change of lens movement.The output is the position of the lens.The fuzzy control system uses 13 rules and requires 1.1 kilobytes of memory.As another example of a practical system, an industrial air conditioner designed by Mitsubishi uses 25 heating rules and 25 cooling rules.A temperature sensor provides input, with control outputs fed to an inverter, a compressor valve, and a fan motor.Compared to the previous design, the fuzzy controller heats and cools five times faster, reduces power consumption by 24%, increases temperature stability by a factor of two, and uses fewer sensors.The enthusiasm of the Japanese for fuzzy logic is reflected in the wide range of other applications they have investigated or implemented: character and handwriting recognition;optical fuzzy systems;robots, voice-controlled robot helicopters Work on fuzzy systems is also proceeding in the US and Europe.The US Environmental Protection Agency has investigated fuzzy control for energy-efficient motors, and NASA has studied fuzzy control for automated space docking: simulations show that a fuzzy control system can greatly reduce fuel consumption.Firms such as Boeing, General Motors, Allen-Bradley, Chrysler, Eaton, and Whirlpool have worked on fuzzy logic for use in low-power refrigerators, improved automotive transmissions, and energy-efficient electric motors.In 1995 Maytag introduced an ”intelligent“ dishwasher based on a fuzzy controller and a ”one-stop sensing module“ that combines a thermistor, for temperature measurement;a conductivity sensor, to measure detergent level from the ions present in the wash;a turbidity sensor that measures scattered and transmitted light to measure the soiling of the wash;and a magnetostrictive sensor to read spin rate.The system determines the optimum wash cycle for any load to obtain the best results with the least amount of energy, detergent, and water.Research and development is also continuing on fuzzy applications in software, as opposed to firmware, design, including fuzzy expert systems and integration of fuzzy logic with neural-network and so-called adaptive ”genetic“ software systems, with the ultimate goal of building ”self-learning“ fuzzy control systems.黄石理工学院毕业设计（论文）外文文献翻译

Fuzzy sets

The input variables in a fuzzy control system are in general mapped into by sets of membership functions similar to this, known as ”fuzzy sets“.The process of converting a crisp input value to a fuzzy value is called ”fuzzification“.A control system may also have various types of switch, or ”ON-OFF“, inputs along with its analog inputs, and such switch inputs of course will always have a truth value equal to either 1 or 0, but the scheme can deal with them as simplified fuzzy functions that happen to be either one value or another.Given ”mappings“ of input variables into membership functions and truth values, the microcontroller then makes decisions for what action to take based on a set of ”rules“, each of the form.In one example, the two input variables are ”brake temperature“ and ”speed“ that have values defined as fuzzy sets.The output variable, ”brake pressure“, is also defined by a fuzzy set that can have values like ”static“, ”slightly increased“, ”slightly decreased“, and so on.This rule by itself is very puzzling since it looks like it could be used without bothering with fuzzy logic, but remember that the decision is based on a set of rules:

All the rules that apply are invoked, using the membership functions and truth values obtained from the inputs, to determine the result of the rule.This result in turn will be mapped into a membership function and truth value controlling the output variable.These results are combined to give a specific(”crisp“)answer, the actual brake pressure, a procedure known as ”defuzzification“.This combination of fuzzy operations and rule-based ”inference“ describes a ”fuzzy expert system“.Traditional control systems are based on mathematical models in which the control system is described using one or more differential equations that define the system response to its inputs.Such systems are often implemented as ”PID controllers“(proportional-integral-derivative controllers).They are the products of decades of development and theoretical analysis, and are highly effective.If PID and other traditional control systems are so well-developed, why bother with fuzzy control? It has some advantages.In many cases, the mathematical model of the control process may not exist, or may be too ”expensive“ in terms of computer processing power and memory, and a system based on empirical rules may be more effective.Furthermore, fuzzy logic is well suited to low-cost implementations based on cheap sensors, low-resolution analog-to-digital converters, and 4-bit or 8-bit one-chip microcontroller chips.Such systems can be easily upgraded by adding new rules to improve performance or add new features.In many cases, fuzzy control can be used to improve existing traditional controller systems by adding an extra layer of intelligence to the current control method.黄石理工学院毕业设计（论文）外文文献翻译

Fuzzy control in detail

Fuzzy controllers are very simple conceptually.They consist of an input stage, a processing stage, and an output stage.The input stage maps sensor or other inputs, such as switches, thumbwheels, and so on, to the appropriate membership functions and truth values.The processing stage invokes each appropriate rule and generates a result for each, then combines the results of the rules.Finally, the output stage converts the combined result back into a specific control output value.The most common shape of membership functions is triangular, although trapezoidal and bell curves are also used, but the shape is generally less important than the number of curves and their placement.From three to seven curves are generally appropriate to cover the required range of an input value, or the ”universe of discourse“ in fuzzy jargon.As discussed earlier, the processing stage is based on a collection of logic rules in the form of IF-THEN statements, where the IF part is called the ”antecedent“ and the THEN part is called the ”consequent“.This rule uses the truth value of the ”temperature“ input, which is some truth value of ”cold“, to generate a result in the fuzzy set for the ”heater“ output, which is some value of ”high“.This result is used with the results of other rules to finally generate the crisp composite output.Obviously, the greater the truth value of ”cold“, the higher the truth value of ”high“, though this does not necessarily mean that the output itself will be set to ”high“ since this is only one rule among many.In some cases, the membership functions can be modified by ”hedges“ that are equivalent to adjectives.Common hedges include ”about“, ”near“, ”close to“, ”approximately“, ”very“, ”slightly“, ”too“, ”extremely“, and ”somewhat“.These operations may have precise definitions, though the definitions can vary considerably between different implementations.”Very“, for one example, squares membership functions;since the membership values are always less than 1, this narrows the membership function.”Extremely“ cubes the values to give greater narrowing, while ”somewhat“ broadens the function by taking the square root.In practice, the fuzzy rule sets usually have several antecedents that are combined using fuzzy operators, such as AND, OR, and NOT, though again the definitions tend to vary: AND, in one popular definition, simply uses the minimum weight of all the antecedents, while OR uses the maximum value.There is also a NOT operator that subtracts a membership function from 1 to give the ”complementary“ function.There are several ways to define the result of a rule, but one of the most common and simplest is the ”max-min“ inference method, in which the output membership function is given the truth value generated by the premise.Rules can be solved in parallel in hardware, or sequentially in software.The results of all the rules that have fired are ”defuzzified“ to a crisp value by one of several methods.There are dozens in theory, each with various advantages and drawbacks.The ”centroid“ method is very popular, in which the ”center of mass“ of the result provides the crisp value.Another approach is the ”height“ method, which takes the value of the biggest contributor.The centroid method favors the rule with the output of

黄石理工学院毕业设计（论文）外文文献翻译

greatest area, while the height method obviously favors the rule with the greatest output value.The diagram below demonstrates max-min inferring and centroid defuzzification for a system with input variables ”x“, ”y“, and ”z“ and an output variable ”n“.Note that ”mu“ is standard fuzzy-logic nomenclature for ”truth value“:

Fuzzy control system design is based on empirical methods, basically a methodical approach to trial-and-error.The general process is as follows:

1.Document the system's operational specifications and inputs and outputs.2.Document the fuzzy sets for the inputs.3.Document the rule set.4.Determine the defuzzification method.5.Run through test suite to validate system, adjust details as required.6.Complete document and release to production.Logical interpretation of fuzzy control In spite of the appearance there are several difficulties to give a rigorous logical interpretation of the IF-THEN rules.As an example, interpret a rule as IF(temperature is ”cold“)THEN(heater is ”high“)by the first order formula Cold(x)→High(y)and assume that r is an input such that Cold(r)is false.Then the formula Cold(r)→High(t)is true for any t and therefore any t gives a correct control given r.Obviously, if we consider systems of rules in which the class antecedent define a partition such a paradoxical phenomenon does not arise.In any case it is sometimes unsatisfactory to consider two variables x and y in a rule without some kind of functional dependence.A rigorous logical justification of fuzzy control is given in Hájek's book ,where fuzzy control is represented as a theory of Hájek's basic logic.Also in Gerla 2005 a logical approach to fuzzy control is proposed based on the following idea.Denote by f the fuzzy function associated with the fuzzy control system, i.e., given the input r, s(y)= f(r,y)is the fuzzy set of possible outputs.Then given a possible output 't', we interpret f(r,t)as the truth degree of the claim ”t is a good answer given r".More formally, any system of IF-THEN rules can be translate into a fuzzy program in such a way that the fuzzy function f is the interpretation of a vague predicate Good(x,y)in the associated least fuzzy Herbrand model.In such a way fuzzy control becomes a chapter of fuzzy logic programming.The learning process becomes a question belonging to inductive logic theory.