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以一維最佳粒子群模糊演算法建置最佳再生能源組合推薦系統
Thesis

以一維最佳粒子群模糊演算法建置最佳再生能源組合推薦系統

龔俐
Masters, National Tsing Hua University
2015

Abstract

推薦系統一維搜尋法模糊粒子群演算法使用者經驗 recommender systemclustering analysisone-dimension Particle Swarm OptimizationFuzzy C-meansUser Experience
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.

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