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In this paper, we discuss an identification and realization method of discrete event systems modeled by the timed Petri nets using neural networks. First, we propose a strict neural network representation of the timed Petri nets. By using the proposed representation, the realization problem of the Petri nets can be formulated as a combinatorial optimization problem. We propose a method for solving the problem using the genetic algorithm. Numerical experiments are performed to demonstrate the performance of the proposed method.

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Identification and Realization of a Class of Discrete Event Systems by Neural Networks–Timed Petri Nets

  • 会议论文

  • 发表日期：

    2026年

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  • Yasuaki Kuroe

摘要

In this paper, we discuss an identification and realization method of discrete event systems modeled by the timed Petri nets using neural networks. First, we propose a strict neural network representation of the timed Petri nets. By using the proposed representation, the realization problem of the Petri nets can be formulated as a combinatorial optimization problem. We propose a method for solving the problem using the genetic algorithm. Numerical experiments are performed to demonstrate the performance of the proposed method.