An improved Grey Model based on using Particle Swarm Optimization and Exponential Smoothing for International Tea Consumption
| Autor: | Tran Thi Thu Trang, 陳氏秋莊 |
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| Rok vydání: | 2016 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 104 Tea is one of the agricultural goods which is playing a big role in economic and social security, tea also one of the oldest beverages in world drinking history. Coming with the improving of awareness about health, citizen intend to approach the new life by using tea as healthy drink for a good health or diet. The tea consumption will be concern as a target for countries and companies plan in strategy of how to focus on manufacturing and trading. In fact, the planning process will base on the previous data and estimated next year result. According to the needs, the problems is figured out is how to estimate the tea consumption for future manufacturing, and allocating resources to reach the idea about high quality goods with expecting import and export quantity which directly effect on forecasting. In addition to that problem, this study is aim to find a new way to get prediction volume of International tea consumption for the future. The statistic data provided by Food and Agriculture Organization of the United Nations from 2006-08 to 2013 and used by applying Grey System Theory- GM(1,1) with the change come from Particle Swarm Optimization (PSO) and Exponential Smoothing to see the different from new method and reality data. The outcomes of this procedure are valuable when also based on the careful analysis on gradual change. Through that study can show out that the amount of tea consumption will be increased in the future. The results approximately reach the actual data when the real data is quite big or quite small. This study can provide organizations, companies or individual a good way to plan the strategy, allocate resources for manufacturing and trading in the impending years. Further work is assessed the tea plan, applied for other areas in tea trading since the achievement results from this study |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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