文化差分进化算法及其在化工过程建模中的应用

提出了一种新的文化差分进化算法，该算法将差分进化算法作为文化算法的种群空间，在文化算法的信念空间和影响函数设计中提出了基于多种知识源的设计方法，通过多种知识指导差分进化的变异操作和交叉操作，使知识的表达和指导种群进化的能力得到加强。函数测试结果表明，基于知识机制的引入使得文化差分进化算法在寻优性能上比差分进化算法有了较大的提高，而对参数的敏感性却相对较小。将文化差分进化算法用于训练补偿模糊神经网络，建立乙烯精馏塔产品质量软测量模型。通过训练与泛化能力的比较结果表明，基于文化差分进化算法的补偿模糊神经网络软测量模型在建模精度和泛化性能上均优于常规补偿模糊神经网络、模糊神经网络以及采用遗传算法优化的模型，具有更好的应用前景。

Cultural differential evolution algorithm and its application in chemical process modeling

A novel cultural differential evolution algorithm(CDEA) was proposed.In CDEA,differential evolution algorithm(DEA) was applied as population space of cultural algorithm(CA).The designs of belief space and influence functions adopted a variety of knowledge sources which were applied to supervising variation and mutation operation of DEA.The expression of knowledge and the role of knowledge supervising the evolution of population were strengthened.The test results of function showed that CDEA produced more co...