An Approach of 1-Dimension PSO with Fuzzy C-means for the Optimal Combination of Energy Resources in a Recommender System

• Main Authors: Kung, Li, 龔俐
• Other Authors: Wang, Hsiao Fan
• Format: Others
• Language: en_US
• Published: 2016
• Online Access: http://ndltd.ncl.edu.tw/handle/94876413672375928356

碩士 === 國立清華大學 === 工業工程與工程管理學系 === 104 === Owing to the over-exploitation of fossil fuels, many governments and companies have been promoting renewable energy to resolve the limitation of fossil energy and environmental issues. Nevertheless, lacks of systematic analysis to provide useful information. A Recommender System is a popular approach to promote products in Electronic Commerce. Till now there is no research developed a recommender system for environmental protection. In addition, user-friendly interface of recommender system is still lacking. Therefore, this research aims to construct an enterprise-oriented web recommender system to cope with environmental issues. In order to identify the users, the system has proposed a modules of clustering analysis called one-dimension Particle Swarm Optimization with Fuzzy C-means. The proposed web recommender system has integrated data-module and model-module for electricity, renewable energy prediction and generation. Based on the forecasted electricity consumption, a case of National Tsing Hua University is provided as an enterprise with the recommendation of the best investment of renewable energy to illustrate and validate the system.