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- W2348486579 abstract "In order to optimize the complex process involving multi-factor, high noise, non-linear relationship between the process of process and fuzzy objects, an intelligent optimal model which integrates a variety of calculating methods was proposed. The model based on multi-Agent technology was divided into layers, the system reconfiguration layer and data integration layer. The communication between the Agents of this model was realized by Ontology. In modeling, the model parameters were calculated by using Chebyshev polynomials orthogonal and partial least-squares regression method. In the interactive mode, the fuzzy optimal solution was calculated by the optimization Agent using the improved genetic algorithm. BP (Back propagation) neural network was trained by injection data obtained from MOLDFLOW software. The results show that the average prediction accuracy of this system increases by 3.23%, compared with that of BP neural network." @default.
- W2348486579 created "2016-06-24" @default.
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- W2348486579 date "2009-01-01" @default.
- W2348486579 modified "2023-09-25" @default.
- W2348486579 title "Complex process optimal model based on multi-agent and multi-method integration" @default.
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