| Summary: | 碩士 === 國立交通大學 === 工業工程與管理系所 === 101 === Energy is an essential element of economic development for all countries. Energy consumption has become an important economic index in recent years. Time-series models were frequently used to construct energy consumption model, because it only needs the information of energy consumption. Many studies have developed time-series prediction models for energy consumption using Box-Jenkins models, Autoregressive Integrated Moving Average (ARIMA) or gray models. However, energy consumption would be affected by economic indicators such as population, economic policy, and industrialization of a country, etc. Therefore, a cause-result prediction model is more suitable for forecasting the energy consumption. This study employs GMDH and modified gray model to construct a cause-result prediction model for energy consumption model to enhance the accuracy of existing time-series forecasting models.
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