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On-line fault diagnose of distribution system based on modified rough sets reduction algorithm. (Chinese. English summary) Zbl 1174.94422

Summary: A rough sets reduction algorithm based on genetic algorithms is presented to the puzzle problem of key data acquirement in the real complex distribution system fault diagnosis with thousands of data. By this approach, we can get the right diagnosis conclusion with less information. The genetic algorithm effect of genetic parameters to the evolutionary process is analyzed. Furthermore the fitness function, punishing function and punishing factor are emphasized to study. The reduction method with utilization of the capability of searching for global optimum of genetic algorithm achieves better reduction result compared with classical rough sets reduction algorithm. An example of America PG&E distribution power system with 69 nodes shows that the attribute reduction by genetic algorithm accelerates the evolutionary process and avoids premature convergence effectively for the system with 202 attributes and 319 records. According to the example, it shows that this method makes the feasibility of fault diagnosis in complex distribution system with thousands of data.

MSC:

94C12 Fault detection; testing in circuits and networks
68T37 Reasoning under uncertainty in the context of artificial intelligence
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