A Hybrid Algorithm for the Reliability Evaluation Models of Chemical Systems

作者：Liu, Wen; Wei, Kecheng; Xu, Juanjuan; Ji, Xu^*

来源：Quality and Reliability Engineering International, 2017, 33(7): 1337-1349.

DOI：10.1002/qre.2108

• system reliability evaluation model
• grey relational analysis
• GA-BP
• Markov chain residual correction
• attribute reduction rule

Chemical processes are complex dynamic systems. With the chemical industry under pressure to introduce improvements through the greater use of automation and intelligence, the need for comprehensive reliability evaluation has become more urgent both theoretically and practically. The employment of intelligent algorithms based on factory data has been the recent research hotspots. But for complex systems with available data on a smaller scale, reliability evaluation models have suffered on such problems as a result of instability and over-fitting, which have to be resolved. The GRA-GA-BP-MCRC hybrid algorithm was proposed. It combined the two-step genetic algorithm (GA)-back propagation (BP) and grey relational analysis (GRA) with Markov chain residual correction (MCRC). Based on the technical characteristics and the management demands, 46 influential factors of process reliability were introduced, which covered man, machine, material, method, and environment. For model convergence to be assured, GRA and attribute reduction rule were introduced. Meanwhile, based on the correlation of the factors, the two-step GA-BP was proposed to resolve the over-fitting problem of artificial neural network with complex input parameters. As well, MCRC was applied to modify the GA-BP error. The resulting average relative error of the hybrid algorithm was 2.36%, while the conventional algorithm was 10.28%.

• 出版日期2017-11
• 单位四川大学