Data Engineering: Fuzzy Mathematics in Systems Theory and Data Analysis (Hardcover)

Olaf Wolkenhauer

  • 出版商: Wiley
  • 出版日期: 2001-07-11
  • 售價: $6,260
  • 貴賓價: 9.5$5,947
  • 語言: 英文
  • 頁數: 296
  • 裝訂: Hardcover
  • ISBN: 0471416568
  • ISBN-13: 9780471416562
  • 相關分類: Data Science
  • 海外代購書籍(需單獨結帳)

買這商品的人也買了...

相關主題

商品描述

A survey of the philosophical implications and practical applications of fuzzy systems

Fuzzy mathematical concepts such as fuzzy sets, fuzzy logic, and similarity relations represent one of the most exciting currents in modern engineering and have great potential in applications ranging from control theory to bioinformatics. Data Engineering guides the reader through a number of concepts interconnected by fuzzy mathematics and discusses these concepts from a systems engineering perspective to showcase the continuing vitality, attractiveness, and applicability of fuzzy mathematics.

The author discusses the fundamental aspects of data analysis, systems modeling, and uncertainty calculi. He avoids a narrow discussion of specialized methodologies and takes a holistic view of the nature and application of fuzzy systems, considering principles, paradigms, and methodologies along the way. This broad coverage includes:

  • Fundamentals of modeling, identification, and clustering
  • System analysis
  • Uncertainty techniques
  • Random-set modeling and identification
  • Fuzzy inference engines
  • Fuzzy classification, control, and mathematics

In the important emerging field of bioinformatics, the book sets out how to encode a natural system in mathematical models, describes methods to identify interrelationships and interactions from data, and thereby helps the practitioner to decide which variables to measure and why.

Data Engineering serves as an up-to-date and informative survey of the theoretical and practical tools for analyzing complex systems. It offers a unique treatment of complex issues that is accessible to students and researchers from a variety of backgrounds.

Table of Contents

Preface.

Acknowledgments.

Introduction.

System Analysis.

Uncertainty Techniques.

Learning from Data: System Identification.

Propositions as Subsets of the Data Space.

Fuzzy Systems and Identification.

Random-Set Modelling and Identification.

Certain Uncertainty.

Fuzzy Inference Engines.

Fuzzy Classification.

Fuzzy Control.

Fuzzy Mathematics.

Summary.

Appendices.

Index.

 

商品描述(中文翻譯)

一項關於模糊系統的哲學意涵與實際應用的調查

模糊數學概念,如模糊集合、模糊邏輯和相似性關係,代表了現代工程中最令人興奮的趨勢之一,並在從控制理論到生物資訊學的應用中具有巨大潛力。《數據工程》引導讀者了解多個由模糊數學相互連結的概念,並從系統工程的角度討論這些概念,以展示模糊數學持續的活力、吸引力和適用性。

作者討論了數據分析、系統建模和不確定性計算的基本方面。他避免狹隘地討論專門的方法論,而是從整體的角度看待模糊系統的性質和應用,考慮原則、範式和方法論。這種廣泛的涵蓋包括:

- 建模、識別和聚類的基本原理
- 系統分析
- 不確定性技術
- 隨機集合建模和識別
- 模糊推理引擎
- 模糊分類、控制和數學

在生物資訊學這一重要的新興領域中,本書闡述了如何將自然系統編碼為數學模型,描述了從數據中識別相互關係和互動的方法,從而幫助實務工作者決定應該測量哪些變數及其原因。

《數據工程》作為一部最新且具資訊性的調查,提供了分析複雜系統的理論和實踐工具。它對複雜問題提供了獨特的處理方式,對來自各種背景的學生和研究人員都能夠輕鬆理解。

目錄

前言

致謝

引言

系統分析

不確定性技術

從數據中學習:系統識別

作為數據空間子集的命題

模糊系統與識別

隨機集合建模與識別

確定的不確定性

模糊推理引擎

模糊分類

模糊控制

模糊數學

總結

附錄

索引