Decision Systems: Integrating Machine Learning, Fuzzy Logic, and Artificial Neural Networks
暫譯: 決策系統:整合機器學習、模糊邏輯與人工神經網絡
Vijay Chavan, Pallavi, Balani, Nisha, Mangrulkar, Ramchandra
- 出版商: Morgan Kaufmann
- 出版日期: 2025-07-28
- 售價: $5,800
- 貴賓價: 9.5 折 $5,510
- 語言: 英文
- 頁數: 270
- 裝訂: Quality Paper - also called trade paper
- ISBN: 0443337284
- ISBN-13: 9780443337284
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相關分類:
Machine Learning、人工智慧
海外代購書籍(需單獨結帳)
相關主題
商品描述
Decision Systems: Integrating Machine Learning, Fuzzy Logic, and Artificial Neural Networks provides readers with a comprehensive understanding of the principal techniques used to build effective decision-making systems. This book covers the fundamental principles and concepts of machine learning, fuzzy logic, and artificial neural networks, and explains how these techniques can be used to build intelligent decision-making systems that can learn from data, reason, and make accurate predictions. The book also presents a wide range of applications of machine learning, fuzzy logic, and artificial neural networks in various domains, such as engineering, medicine, finance, and robotics. The book also provides practical guidance on how to design and implement effective decision-making systems using these techniques and discusses the potential challenges and limitations of machine learning, fuzzy logic, and artificial neural networks, and how to overcome them. The book provides a stepwise approach to provide readers with the knowledge and tools they need to build intelligent decision-making systems, including a robust introduction to the mathematical concepts and principles necessary to understand the concepts and applications of Decision Systems and Machine Learning algorithms. Next, the book provides readers with an in-depth explanation and demonstration of two of the major machine learning techniques - Fuzzy Logic/Fuzzy Set Theory and Artificial Neural Networks - followed by an in-depth look at more advanced topics that play essential roles in making machine learning algorithms more useful in practice, including creating full-fledged Recurrent Networks and their mathematical foundations, Associative Memories, and Deep Learning networks such as Convolutional Neural Networks, Generative Adversarial Networks, Radial Basis Function Networks, Multilayer Perceptrons, and Self-Organizing Maps. The lynchpin of the book provides readers with an understanding of how the various types of techniques can be integrated to create dynamic Decision Systems. The book wraps up with coverage of challenges and opportunities in Decision Systems along with real-world applications of Decision Systems with case studies in healthcare, finance, education, social media, and agriculture.
商品描述(中文翻譯)
《決策系統:整合機器學習、模糊邏輯與人工神經網路》為讀者提供了建立有效決策系統所需的主要技術的全面理解。本書涵蓋了機器學習、模糊邏輯和人工神經網路的基本原則和概念,並解釋了如何利用這些技術來構建能夠從數據中學習、推理並做出準確預測的智能決策系統。本書還展示了機器學習、模糊邏輯和人工神經網路在工程、醫學、金融和機器人等各個領域的廣泛應用。本書提供了如何設計和實施有效決策系統的實用指導,並討論了機器學習、模糊邏輯和人工神經網路的潛在挑戰和限制,以及如何克服這些挑戰。本書採取逐步的方法,為讀者提供建立智能決策系統所需的知識和工具,包括對理解決策系統和機器學習算法所需的數學概念和原則的堅實介紹。接下來,本書深入解釋和演示了兩種主要的機器學習技術——模糊邏輯/模糊集合理論和人工神經網路,隨後深入探討在實踐中使機器學習算法更有用的更高級主題,包括創建完整的遞迴網路及其數學基礎、聯想記憶,以及深度學習網路,如卷積神經網路、生成對抗網路、徑向基函數網路、多層感知器和自組織映射。本書的核心部分使讀者理解各種技術如何整合以創建動態決策系統。本書最後涵蓋了決策系統中的挑戰和機會,以及決策系統在醫療、金融、教育、社交媒體和農業等領域的實際應用案例研究。