Titlebook: Knowledge-Driven Board-Level Functional Fault Diagnosis; Fangming Ye,Zhaobo Zhang,Xinli Gu Book 2017 The Editor(s) (if applicable) and The

Herbaceous

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GREEN

GOAD

Density

Adaptive Diagnosis Using Decision Trees (DT),cy and effective board repair, a large number of syndromes must be used. Therefore, the diagnosis cost can be prohibitively high due to the increase in diagnosis time and the complexity of syndrome collection/analysis. In this chapter, we apply decision trees to the problem of adaptive board-level f

Handedness

jet-lag

Handling Missing Syndromes,mes, are not available during diagnosis. Since root-cause isolation for a failing board relies on reasoning based on syndromes, any information loss (e.g., missing syndromes) during the extraction of a diagnosis log may lead to ambiguous repair suggestions. In this chapter, we propose a board-level

不公開

Knowledge Discovery and Knowledge Transfer,tomatically generate an intelligent diagnostic system from existing resources [., .]. However, knowledge acquisition is a major problem for a reasoning-based method at the initial product ramp-up stage. Machine learning-based reasoning requires an adequate database for training the reasoning engine,

獨輪車

剛毅

s what elements are needed for the initial implementation of a fundamental Enterprise Architecture...The book‘s pragmatic approach keeps existing architecture frameworks and methodologies in mind while providing instructions that are readable and applicable to all. The Enterprise Architecture Implem

去世

Fangming Ye,Zhaobo Zhang,Krishnendu Chakrabarty,Xinli Gud real-world examples.The book also examines the origins of .Implement a basic Enterprise Architecture from start to finish using a four-stage, wheel-based approach. Aided by real-world examples, this book shows what elements are needed for the initial implementation of a fundamental Enterprise Arch