Artificial Intelligence Tools: Decision Support Systems in Condition Monitoring and DIagnosis Hardcover

Artificial Intelligence Tools: Decision Support Systems in Condition Monitoring and Diagnosis discusses various white- and black-box approaches to fault diagnosis in condition monitoring (CM). This indispensable resource:

• Addresses nearest-neighbor-based, clustering-based, statistical, and information theory-based techniques
• Considers the merits of each technique as well as the issues associated with real-life application
• Covers classification methods, from neural networks to Bayesian and support vector machines
• Proposes fuzzy logic to explain the uncertainties associated with diagnostic processes
• Provides data sets, sample signals, and MATLAB® code for algorithm testing

Artificial Intelligence Tools: Decision Support Systems in Condition Monitoring and Diagnosis delivers a thorough evaluation of the latest AI tools for CM, describing the most common fault diagnosis techniques used and the data acquired when these techniques are applied.

《人工智慧工具：條件監測和診斷中的決策支援系統》討論了在條件監測（CM）中進行故障診斷的各種白盒和黑盒方法。這是一個不可或缺的資源，具有以下特點：

- 探討基於最近鄰、基於聚類、統計和信息理論的技術。
- 考慮每種技術的優點以及與實際應用相關的問題。
- 包括從神經網絡到貝葉斯和支持向量機的分類方法。
- 提出模糊邏輯來解釋診斷過程中的不確定性。
- 提供數據集、樣本信號和MATLAB®代碼進行算法測試。

《人工智慧工具：條件監測和診斷中的決策支援系統》全面評估了最新的人工智慧工具在條件監測中的應用，描述了常用的故障診斷技術以及應用這些技術時獲得的數據。