期刊名称：International Journal of Innovative Research in Science, Engineering and Technology
印刷版ISSN：2347-6710
电子版ISSN：2319-8753
出版年度：2015
卷号：4
期号：2
页码：616
DOI：10.15680/IJIRSET.2015.0402081
出版社：S&S Publications
摘要：A soft computing technique based on the combination of Multiple Adaptive Neuro-Fuzzy InferenceSystem (M-ANFIS) and a Genetic Algorithm (GA) has been developed for the discovery and optimization of newmaterials when exploring a high-dimensional space. This technique allows the experimental design in the search of newsolid materials with high catalytic performance when exploring simultaneously a large number of variables such aselemental composition, manufacture procedure variables, etc. This integrated architecture (M-ANFIS+GA) allows oneto strongly increase the convergence performance when compared with the performance of conventional GAs. It isdescribed how both soft-computing techniques are built to work together. The proposed optimization architecture hasbeen validated using two hypothetical functions, based on the modeled behavior of multi-component catalysts exploredin the field of combinatorial catalysis.The method consists of following stages. First, prior to feature extraction, some preprocessing techniques, Secondly,the six salient feature sets are input into the multiple ANFIS combination with genetic algorithms (GAs) for discoveryand optimization of new materials. The proposed method is applied for discovery and optimization of new materialsand testing results show that the multiple ANFIS combination can reliably recognize, discover and optimize newmaterials, which has a better performance compared to the individual GA based on ANFIS.
