点击次数：

论文类型：会议论文

第一作者：Liu, Yong

合写作者：Chen, Wang,Hu, Jianjun,Zheng, Xiaojun,Shi, Yanjun

发表时间：2017-01-01

收录刊物：EI、CPCI-S、Scopus

页面范围：521-524

关键字：ensemble of surrogates; evolutionary multi-agent system; cross-validation

摘要：We herein propose an evolutionary multi-agent system (EMAS for short) to build an ensemble of surrogates for prediction. In our EMAS, we employ six kinds of basic surrogates, including Gaussian process, Kriging model, polynomial response surface, radial basis function, radial basis function neural network, and support vector regression machine. We define each surrogate as one agent and co-evolve parameters of basic surrogates to obtain the evolutionary weighted average surrogate, where sample cross-validation errors evaluate an ensemble of surrogates. The preliminary results from predicting the benchmark function with high dimension showed the effectiveness of our EMAS for an ensemble of surrogates.