Genetic algorithms: foundations and applications
Annals of Operations Research
Ensemble of structure-adaptive self-organizing maps for high performance classification
Information Sciences: an International Journal - methods and systems for intelligent human—computer interaction
Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control and Artificial Intelligence
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms
Classifying inventory using an artificial neural network approach
Computers and Industrial Engineering
Design of structural modular neural networks with genetic algorithm
Advances in Engineering Software
A neural-network approach for an automatic LED inspection system
Expert Systems with Applications: An International Journal
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The clustering phenomenon of defects usually occurs in semiconductor manufacturing. However, previous studies did not pay much attention to the influence of clustering phenomenon for estimating fraction nonconforming of a wafer. Thus, this paper presents a systematic estimation model with considering relevant variables about clustering defects for fraction nonconforming of a wafer. The method combines back-propagation neural network (BPNN) with genetic algorithm (GA) to obtain an estimation model. In this study, GA aims to optimize the parameters of BPNN. Five relevant variables: number of defects (ND), squared coefficient of angle variation (SCV"A) for defects, squared coefficient of distance variation (SCV"D) for defects, defect cluster index (CI"M), and the number of cluster groups (NCG) for defects by self-organized map (SOM) are utilized as inputs for GA-BPNN. Finally, a simulation case and a real-world case are used to confirm the effectiveness of proposed method.