Rural household energy consumption behavior with neural network approach: A case study

Rural household energy consumption behavior with neural network approach: A case study

Sheng Cheng Xiongbiao Xie Giedon Kwaku Minua Ampofo Jiping Chu 

School of Economics and Management, China University of Geosciences (Wuhan), Wuhan 430074, China

Corresponding Author Email:
19 February 2018
| |
30 May 2018
| | Citation



Rural household energy consumption is an important component of national energy consumption and plays a vital role in rural economic and ecological environment development. In this paper, the energy consumption of 1126 households in four typical agricultural provinces was investigated. In addition, multilayer perceptron neural network is adopted to conduct variables selection. Moreover, Logit, Tobit and multiple regression models are used to reveal the impact of different factors on rural resident choice and quantity behavior. The results show that family size, market distance, education level, farmland area and occupation affect farmers' energy choices and quantity consumption behavior to varying degrees. The differences of energy availability and convenience caused by the difference of geographical features are important factors that affect the energy consumption behavior of farmers. Income level is a key determinant of transition of energy consumption behavior, which however is not sensitive to coal. We hold the opinion that the key to improve rural energy structure in China is to boost the income level of rural residents. Meanwhile, rural energy consumption should be included in the national energy strategy framework. The government should increase the investment on the research and implementation of the renewable energy and use economic measures such as taxes and subsidies to reduce initial installed costs and operating costs so as to speed up the of upgrading rural energy consumption structure.


energy consumption, influencing factors, rural survey, neural network

1. Introduction
2. Literature Review
3. Survey Analysis
4. Empirical Analysis and Results
5. Conclusions & Policy Recommendations

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