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- W1557706798 abstract "Publisher Summary Fuzzy art with add clustering technique (FACT) is a new clustering algorithm based on the neural network techniques and fuzzy logic concept. In this chapter, structure and application of this algorithm with respect to the group technology (GT) problem is described. Characteristics and abilities of the algorithm are shown through several examples. To evaluate the quality of the clustering results, two sets of performance measures are considered in the chapter. The first set evaluates performance of the clustering results independent of the GT application. The second set includes three GT-dependent measures. These measures are used for evaluating performance of the FACT algorithm with respect to several GT clustering algorithms. Cluster analysis approaches group objects (parts or machines) into homogeneous clusters (groups) based on object features. The existing clustering approaches to the GT problem can be classified as matrix based methods, mathematical programming algorithms, graph theory based methods, pattern recognition techniques, fuzzy logic approaches, expert system based methods, and neural network based methods. All the methods, with the exception of neural network based methods, are serial algorithms requiring significant time for processing. Moreover, these methods also require storage and manipulation of large matrices and virtually always focus on binary attributes. The chapter presents information required by a GT clustering algorithm. The structure of the FACT algorithm and performance measures used to evaluate goodness of the clustering results are discussed in the chapter." @default.
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- W1557706798 date "1995-01-01" @default.
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- W1557706798 title "Adaptive clustering algorithm for group technology: An application of the fuzzy ART neural network" @default.
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- W1557706798 doi "https://doi.org/10.1016/s1572-4417(06)80045-8" @default.
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