This book constitutes the refereed proceedings of the 14th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2013, held in Hefei, China, in October 2013. The 76 revised full papers presented were carefully reviewed and selected from more than 130 submissions. These papers provided a valuable collection of latest research outcomes in data engineering and automated learning, from methodologies, frameworks and techniques to applications. In addition to various topics such as evolutionary algorithms, neural networks, probabilistic modelling, swarm intelligent, multi-objective optimisation, and practical applications in regression, classification, clustering, biological data processing, text processing, video analysis, including a number of special sessions on emerging topics such as adaptation and learning multi-agent systems, big data, swarm intelligence and data mining, and combining learning and optimisation in intelligent data engineering.14th International Conference, IDEAL 2013, Hefei, China, October 20-23, 2013, Proceedings Hujun Yin, Ke Tang, Yang Gao, ... Vector Regression Huaxian Pan1 , Guojian Cheng2, and Jian Ding3 1 Xingzhi College, Xia#39;an University of Finace and ... Support Vector Machine (SVR) is used to predict the drilling cost of oil and gas in this paper. ... SaDE is also compared with three parameter optimization methods, Differential Evolution(DE), Grid Search(GS) and Genetic Algorithms(GA ).
|Title||:||Intelligent Data Engineering and Automated Learning -- IDEAL 2013|
|Author||:||Hujun Yin, Ke Tang, Yang Gao, Frank Klawonn, Minho Lee, Bin Li, Thomas Weise, Xin Yao|
|Publisher||:||Springer - 2013-10-16|