Abstract
The application of pattern recognition (PR) techniques, artificial neural networks (ANNs), and nowadays hybrid artificial intelligence (Al) techniques in manufacturing can be regarded as consecutive elements of a process started two decades ago. The fundamental aim of the paper is to outline the importance of soft computing and hybrid AI techniques in manufacturing by introducing a genetic algorithm (GA) based dynamic job shop scheduler and the integrated use of neural, fuzzy and GA techniques for modeling, control and monitoring purposes.
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© 1998 Springer-Verlag Berlin Heidelberg
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Monostori, L., Hornyák, J., Egresits, C., Viharos, Z.J. (1998). Soft computing and hybrid AI approaches to intelligent manufacturing. In: Pasqual del Pobil, A., Mira, J., Ali, M. (eds) Tasks and Methods in Applied Artificial Intelligence. IEA/AIE 1998. Lecture Notes in Computer Science, vol 1416. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-64574-8_463
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DOI: https://doi.org/10.1007/3-540-64574-8_463
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