Fuzzy if-then Rules in Computational Intelligence pdf epub mobi txt 电子书下载 2026

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出版者:Kluwer Academic Pub

作者:Ruan, Da (EDT)/ Kerre, Etienne E. (EDT)

出品人:

页数:332

译者:

出版时间:2000-4

价格:$ 231.65

装帧:HRD

isbn号码:9780792378204

丛书系列:

图书标签:

模糊逻辑
计算智能
IF-THEN规则
专家系统
人工智能
机器学习
控制系统
决策制定
知识工程
模式识别

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具体描述

During the last three decades, interest has increased significantly in the representation and manipulation of imprecision and uncertainty. Perhaps the most important technique in this area concerns fuzzy logic or the logic of fuzziness initiated by L. A. Zadeh in 1965. Since then, fuzzy logic has been incorporated into many areas of fundamental science and into the applied sciences. More importantly, it has been successful in the areas of expert systems and fuzzy control. The main body of this book consists of so-called IF-THEN rules, on which experts express their knowledge with respect to a certain domain of expertise. Fuzzy IF-THEN Rules in Computational Intelligence: Theory and Applications brings together contributions from leading global specialists who work in the domain of representation and processing of IF-THEN rules. This work gives special attention to fuzzy IF-THEN rules as they are being applied in computational intelligence. Included are theoretical developments and applications related to IF-THEN problems of propositional calculus, fuzzy predicate calculus, implementations of the generalized Modus Ponens, approximate reasoning, data mining and data transformation, techniques for complexity reduction, fuzzy linguistic modeling, large-scale application of fuzzy control, intelligent robotic control, and numerous other systems and practical applications. This book is an essential resource for engineers, mathematicians, and computer scientists working in fuzzy sets, soft computing, and of course, computational intelligence.

该图书以探索智能系统中的模糊逻辑思想为核心主题，深入分析了如何在实际应用中运用这种非确定性推理规则来处理不精确信息与复杂决策问题。书中详细介绍了传统计算机逻辑的局限性，以及模糊系统理论在提升决策灵活性方面的突破。作者系统梳理了从基础概念到具体应用的多种方法，探讨了如何通过定义适当的隶属度函数和规则库来构建有效的智能推断模型。内容涵盖了一系列实际案例，展示了模糊如果-然后规则在医疗诊断、金融预测、工业控制等领域的具体作用和效果。书中不仅注重理论探讨，还强调实验验证与优化过程，帮助读者理解这些方法在不同场景下的适用性和优劣。此外，作者详细分析了数据集构建、模型训练与验证的重要步骤，指出如何通过不断迭代调整参数，提升推理系统的准确性与鲁棒性。内容还引入了相关研究的最新进展，如结合机器学习算法优化模糊规则体系，强调跨学科融合在提升智能系统性能中的价值。这本书适合对计算智能、知识表示和推理机制感兴趣的专业读者，无论是学术研究者，还是希望深入理解复杂决策问题的人士，都会找到有用的参考。在内容设计上，作者力求通俗易懂，同时避免过于技术化，以便不同背景的读者能充分理解并从中获得启发。整体结构合理，逻辑清晰，每一章均围绕实际应用和理论深度展开，为读者提供全面的知识框架和实践指导。简介部分强调了图书在填补模糊推理领域空白方面的重要意义，通过系统化的论述和丰富的实例，使读者对这类智能方法有深入而清晰的认识。这一书不仅为研究提供理论支持，也为实际工程应用带来了可操作的思路，具有很强的参考价值。