2013Unpublished venueRequires access

Forecasting the Rural Per Capita Living Consumption Based on Matlab BP Neural Network

Qian Guo

Open publisher page 7 citations

Abstract

Resident consumption is the important for the rapid and sustainable economic growth in China, and the number of rural residents is almost half of the total number, and forecasting the rural residents per capita living consumption accurately and reliably provide important basis for the government to establish new development strategies. Therefore, prediction of rural per capita living consumption is one of the important contents of the analysis of Chinese economy development in the future. In recent years, there are many prediction methods about the consumption, but some is low accuracy. In this paper, the BP neural network based on Matlab simulates the rural residents per capita living consumption, and forecasts the consumption expenditure in future three years through the actual data test and empirical analysis. Prediction results show that this method has high prediction accuracy; the model is feasible and effective in the application of forecast residents living consumption.

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What this paper is about

Resident consumption is the important for the rapid and sustainable economic growth in China, and the number of rural residents is almost half of the total number, and forecasting the rural residents per capita living consumption accurately and reliably provide important basis for the government to establish new development strategies. Therefore, prediction of rural per capita living consumption is one of the important contents of the analysis of Chinese economy development in the future. In recent years, there are many prediction methods about the consumption, but some is low accuracy. In this paper, the BP neural network based on Matlab simulates the rural residents per capita living consumption, and forecasts the consumption expenditure in future three years through the actual data test and empirical analysis. Prediction results show that this method has high prediction accuracy; the model is feasible and effective in the application of forecast residents living consumption.

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OpenAlex reports 7 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Resident consumption is the important for the rapid and sustainable economic growth in China, and the number of rural residents is almost half of the total number, and forecasting the rural residents per capita living consumption accurately and reliably provide important basis for the government to establish new development strategies. Therefore, prediction of rural per capita living consumption is one of the important contents of the analysis of Chinese economy development in the future. In recent years, there are many prediction methods about the consumption, but some is low accuracy. In this paper, the BP neural network based on Matlab simulates the rural residents per capita living consumption, and forecasts the consumption expenditure in future three years through the actual data test and empirical analysis. Prediction results show that this method has high prediction accuracy; the model is feasible and effective in the application of forecast residents living consumption.

Key concepts: Per capita, Consumption (sociology), Government (linguistics), China, Sustainable development, Artificial neural network, Economics, Rural area

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