基于多方法集成的复杂工艺优化

Research on Complex Techniques System Optimal Design Based on Multi Method Integration

介绍了基于模式识别、神经网络、遗传算法、非线性回归等多种智能技术集成的复杂工艺过程优化系统的设计思想、体系结构、关键技术和实现方法,主要解决多因子、高噪声、非线性、非高斯分布和非均匀的复杂工艺系统难题。采用Agent技术设计系统的体系结构,用偏最小二乘法和Chelyshev多项式建立领域模型,通过演化计算进行最优问题求解,并用正交实验取得模型学习的样本数。实际应用证明,利用这些方法可以在很少的实验情况下,使建立的模型能在较大误差范围内指导生产实践。

The paper introduces intelligent software system on optimal formula of production processing with multivariate factors based on pattern recognition, artificial neural network,genetic algorithm and nonlinear regression method. Narrates basic principle,key technology and means of realization. And the meaning is to solve questions on multiple- factor,high noise, nonlinear,non- Gaussian distribution and non- uniform distribution in optimal industrial complicated craft process. The domain model is solved by the least square method and Chebyshev,and the optimal solution of model is solved by the evolutional algorithm,and learning sample data is gained by the orthogonal test. By its application,these methods can direct the industrial production in allowable error.