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- W1186655525 abstract "Publisher Summary Knowledge-based hybrid systems (KBHSs) play an increasing role in industrial applications. New techniques of artificial intelligence (AI) such artificial neural networks (ANNs), genetic algorithms (GEs), machine learning (ML), or the fuzzy set theory have created new ways of solving problems. Most of these new techniques, however, are not appropriate for handling complex tasks alone; therefore, their integration with or connection to other systems is obligatory. The different types of KBHSs are the result of this development trend, as in their case the goal is to solve complex problems of a well-defined limited area. This chapter defines and classifies KBHSs, including the integration possibilities with simulation. Several examples of industrial applications of various types of KBHSs are described. KBHSs will have an increasing role in industry in future, as they are a significant source of support for users in a variety of applications. The representation, design, and control of dynamic, stochastic, and complex systems (like manufacturing systems) can be intensively supported by KBHSs." @default.
- W1186655525 created "2016-06-24" @default.
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- W1186655525 date "2000-01-01" @default.
- W1186655525 modified "2023-10-17" @default.
- W1186655525 title "Knowledge-Based Hybrid Techniques Combined with SimulationApplication to Robust Manufacturing Systems" @default.
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- W1186655525 doi "https://doi.org/10.1016/b978-012443875-0/50026-4" @default.
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