計(jì)算智能

前言

Several computational analytic tools have matured in the last 10 to 15 years that facilitate solving problems that were previously difficult or impossible to solve. These new analytical tools, known collectively as computational intelligence tools, include artificial neural networks, fuzzy systems, and evolutionary computation. They haverecently been combined among themselves as well as with more traditional approa-ches, such as statistical analysis, to solve extremely challenging problems. Diagnos-tic systems, for example, are being developed that include Bayesian, neural network, and rule-based diagnostic modules, evolutionary algorithm-based explanation facil-ities, and expert system shells. All of these components work together in a "seamless" way that is transparent to the user, and they deliver results that significantly exceed what is available with any single approach.At a system prototype level, computational intelligence （CI） tools are capable of yielding results in a relatively short time. For instance, the implementation of a conventional expert system often takes one to three years and requires the active participation of a "knowledge engineer" to build the knowledge and rule bases. In contrast, computational intelligence system solutions can often be prototyped in a few weeks to a few months and are implemented using available engineering and computational resources. Indeed, computational intelligence tools are capable of being applied in many instances by "domain experts" rather than solely by "computer gurus."This means that biomedical engineers, for example, can solve problems in biomedical engineering without relying on outside computer science expertise such as that required to build knowledge bases for classical expert systems. Furthermore, innovative ways to combine CI tools are cropping up every day. For example, tools have been developed that incorporate knowledge elements with neural networks, fuzzy logic, and evolutionary computing theory. Such tools are able to solve quickly classification and clustering problems that would be extremely time consuming using other techniques.

內(nèi)容概要

本書面向智能系統(tǒng)學(xué)科的前沿領(lǐng)域，系統(tǒng)地討論了計(jì)算智能的理論、技術(shù)及其應(yīng)用，比較全面地反映了計(jì)算智能研究和應(yīng)用的最新進(jìn)展。書中涵蓋了模糊控制、神經(jīng)網(wǎng)絡(luò)控制、進(jìn)化計(jì)算以及其他一些技術(shù)及應(yīng)用的內(nèi)容。本書提供了大量的實(shí)用案例，重點(diǎn)強(qiáng)調(diào)實(shí)際的應(yīng)用和計(jì)算工具，這些對(duì)于計(jì)算智能領(lǐng)域的進(jìn)一步發(fā)展是非常有意義的。本書取材新穎，內(nèi)容深入淺出，材料豐富，理論密切結(jié)合實(shí)際，具有較高的學(xué)術(shù)水平和參考價(jià)值。　　本書可作為高等院校相關(guān)專業(yè)高年級(jí)本科生或研究生的教材及參考用書，也可供從事智能科學(xué)、自動(dòng)控制、系統(tǒng)科學(xué)、計(jì)算機(jī)科學(xué)、應(yīng)用數(shù)學(xué)等領(lǐng)域研究的教師和科研人員參考。

作者簡(jiǎn)介

作者：(美國(guó))埃伯哈特 (Russell C.Eberhart) (美國(guó))史玉回 (Yuhui Shi)Russell C.Eberhart，普度大學(xué)電子與計(jì)算機(jī)工程系主任，IEEE會(huì)士。與James Kennedy共同提出了粒子群優(yōu)化算法。曾任IEEE神經(jīng)網(wǎng)絡(luò)委員會(huì)的主席。除了本書之外。他還著有《群體智能》（影印版由人民郵電出版社出版）等。Yuhui Shi（史玉回），國(guó)際計(jì)算智能領(lǐng)域?qū)＜?，現(xiàn)任Journal of Swarm Intelligence編委，IEEE CIS群體智能任務(wù)組主席，西交利物浦大學(xué)電子與電氣工程系教授。1992年獲東南大學(xué)博士學(xué)位，先后在美國(guó)、韓國(guó)、澳大利亞等地從事研究工作，曾任美國(guó)電子資訊系統(tǒng)公司專家長(zhǎng)達(dá)9年。他還是《群體智能》一書的作者之一。

書籍目錄

chapter one　Foundationschapter two　Computational Intelligencechapter three　Evolutionary Computation Concepts and Paradigmschapter four　Evolutionary Computation Implementationschapter five　Neural Network Concepts and Paradigmschapter six　Neural Network Implementationschapter seven　Fuzzy Systems Concepts and Paradigmschapter eight　Fuzzy Systems Implementationschapter nine　Computational Intelligence Implementationschapter ten　Performance Metricschapter eleven　Analysis and ExplanationBibliographyIndexAbout the Authors

章節(jié)摘錄

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媒體關(guān)注與評(píng)論

“這是第一部如此全面的計(jì)算智能教科書，包括了大量的實(shí)踐示例?！薄　　猄hun-ichi Amari，日本理化研究所腦科學(xué)研究機(jī)構(gòu)“本書強(qiáng)調(diào)計(jì)算智能的基礎(chǔ)是演化計(jì)算，這種全新的視角使其獨(dú)樹(shù)一幟。本書有非常豐富的實(shí)際應(yīng)用和計(jì)算工具，對(duì)于計(jì)算智能領(lǐng)域的發(fā)展意義重大。”　　——Xin Yao，伯明翰計(jì)算智能與應(yīng)用研究中心

編輯推薦

《計(jì)算智能:從概念到實(shí)現(xiàn)(英文版)》是計(jì)算智能領(lǐng)域的經(jīng)典著作，第一作者是著名的群體智能算法——粒子群優(yōu)化算法的提出者。書中系統(tǒng)地討論了計(jì)算智能的理論、技術(shù)及其應(yīng)用，包括神經(jīng)網(wǎng)絡(luò)、模糊系統(tǒng)和演化計(jì)算等內(nèi)容，比較全面地反映了計(jì)算智能研究和應(yīng)用的最新進(jìn)展，并提出了一種行之有效的思考和使用計(jì)算智能的方法。 《計(jì)算智能:從概念到實(shí)現(xiàn)(英文版)》不僅學(xué)術(shù)水平較高，而且理論結(jié)合實(shí)際，很具實(shí)用價(jià)值。不但有豐富的案例研究和習(xí)題，而且提供了教輔和C／C++代碼(源代碼可以在圖靈網(wǎng)站《計(jì)算智能:從概念到實(shí)現(xiàn)(英文版)》網(wǎng)頁(yè)免費(fèi)注冊(cè)下載)，非常適合作為高校教材使用。

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