Evolving Intelligent Systems: Methodology and Applications (Hardcover)

From theory to techniques, the first all-in-one resource for EIS

There is a clear demand in advanced process industries, defense, and Internet and communication (VoIP) applications for intelligent yet adaptive/evolving systems. Evolving Intelligent Systems is the first self- contained volume that covers this newly established concept in its entirety, from a systematic methodology to case studies to industrial applications. Featuring chapters written by leading world experts, it addresses the progress, trends, and major achievements in this emerging research field, with a strong emphasis on the balance between novel theoretical results and solutions and practical real-life applications.

• Explains the following fundamental approaches for developing evolving intelligent systems (EIS):

  • the Hierarchical Prioritized Structure

  • the Participatory Learning Paradigm

  • the Evolving Takagi-Sugeno fuzzy systems (eTS+)

  • the evolving clustering algorithm that stems from the well-known Gustafson-Kessel offline clustering algorithm

• Emphasizes the importance and increased interest in online processing of data streams

• Outlines the general strategy of using the fuzzy dynamic clustering as a foundation for evolvable information granulation

• Presents a methodology for developing robust and interpretable evolving fuzzy rule-based systems

• Introduces an integrated approach to incremental (real-time) feature extraction and classification

• Proposes a study on the stability of evolving neuro-fuzzy recurrent networks

• Details methodologies for evolving clustering and classification

• Reveals different applications of EIS to address real problems in areas of:

  • evolving inferential sensors in chemical and petrochemical industry

  • learning and recognition in robotics

• Features downloadable software resources

Evolving Intelligent Systems is the one-stop reference guide for both theoretical and practical issues for computer scientists, engineers, researchers, applied mathematicians, machine learning and data mining experts, graduate students, and professionals.

從理論到技術，首本全方位的EIS資源

在先進的製程工業、國防、互聯網和通信（VoIP）應用中，對智能而又適應/演進系統有明顯需求。《演進智能系統》是第一本自成一體的專書，全面介紹了這一新興概念，從系統方法論到案例研究再到工業應用。本書由領先的世界專家撰寫，探討了這一新興研究領域的進展、趨勢和重大成就，強調了新穎理論成果和解決方案與實際應用之間的平衡。

- 解釋了開發演進智能系統（EIS）的以下基本方法：
- 分層優先結構
- 參與式學習範式
- 演進高木-菅野模糊系統（eTS+）
- 源於著名的Gustafson-Kessel離線聚類算法的演進聚類算法

- 強調了對數據流的在線處理的重要性和日益增加的興趣

- 概述了使用模糊動態聚類作為可演進信息粒度基礎的一般策略

- 提出了一種開發強健且可解釋的演進模糊規則系統的方法論

- 引入了一種增量（實時）特徵提取和分類的綜合方法

- 提出了一項關於演進神經模糊循環網絡穩定性的研究

- 詳細介紹了演進聚類和分類的方法論

- 揭示了EIS在以下領域解決實際問題的不同應用：
- 化學和石油化工行業中的演進推理傳感器
- 機器人學中的學習和識別

- 提供可下載的軟件資源

《演進智能系統》是計算機科學家、工程師、研究人員、應用數學家、機器學習和數據挖掘專家、研究生和專業人士的一站式參考指南，涵蓋了理論和實踐問題。