The Application Of Artificial Neural Network In Solar Water Heater Market Forcasting

The solar water heater is the localization industry with independent intellectualproperty rights. The economic development and improve of social awareness ofenergy conservation vigorously promote the development of China’s solar waterheater industry.“12thFive-Year Plan” clearly take the solar energy industry as China’sstrategic emerging industry, introduce a large number of supportive policies. Thesepolicies and measures vigorously promote the development of the solar water heaterindustry. At the same time, it makes the competition increasingly fierce. The companywhich wants to win the competition in the market must provide customers productswith most reasonable costs. This forces the company to forecasting the market.Forecasting is the premise of the decision-making, and a successful decision-makingcannot be separated from the scientific prediction. The forecasting can improve theability for the company to respond to uncertain events, reduce the losses caused byadverse events and increase the benefits.In this paper, guide by the ideas and methods of industrial engineering and systemengineering, based on the actual situation of China’s solar water heater market, designand research an ANN forecasting model used in solar water heater industry. Firstly,we introduced the market forecasting theory and methods; then, we use Gompertz andExponential Smoothing model to forecast the market demand of solar water heater;thirdly, we use BP ANN model to forecast the market demand of solar water heater inChina, and compare the difference with the result of Gompertz and ExponentialSmoothing model.