4.6 Article

Nature-Inspired Metaheuristic Regression System: Programming and Implementation for Civil Engineering Applications

期刊

出版社

ASCE-AMER SOC CIVIL ENGINEERS
DOI: 10.1061/(ASCE)CP.1943-5487.0000561

关键词

Expert computing system; Stand-alone application; Data mining; Machine learning; Nature-inspired metaheuristics; Evolutionary optimization; Civil engineering

向作者/读者索取更多资源

Developing an expert system has been considered as complex and knowledge driven process. This study proposes a natureinspired metaheuristic regression system that can find appropriate solutions. The system uses a graphical user interface but does not require a mathematical program installation. The user-friendly interface was designed in the MATLAB graphical user interface design environment (GUIDE) and was implemented by MATLAB compiler. The stand-alone system is easy to use and has many functions, including evaluation, use of an opened data file, test set selection, hold-out, cross validation, and prediction to solve many civil engineering problems with simple manipulations on the system interface. Five benchmark functions were used to evaluate the effectiveness of the optimization module. The performance of the proposed regression system was then validated by comparing its solutions obtained for civil engineering problems with those obtained by empirical methods reported previously. Five actual data sets including energy-efficient buildings, construction material strength, concrete structure shear strength, bridge scour depth, and subbase soil modulus were used as case studies. The prediction accuracy was 8.24-91.76% better than those of previously reported models. The analytical results support the feasibility of using the proposed system to solve numerous civil engineering problems. The system was also much faster at identifying the optimum parameters and solving problems. The experiments confirmed that the novel nature-inspired metaheuristic regression system proposed in this study has superior efficiency, effectiveness, and accuracy. (C) 2016 American Society of Civil Engineers.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据