Indicators Forecasting and Empirical Analysis of Regional Economic Development Based on Neural Network

Abstract:

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Based on neural network method and by using the relevant social and economic development history index data, this paper establishes the mathematical model and neural network model that is used to predict future land resource demand, and the network is trained by using data from 1992 to 2005. Accordingly, the trend analysis model, which is to predict and analyses the indicators of population, production value, GDP, etc., is also established, and applied to predict the construction land demand from 2010 to 2020. Here, taking the trend forecasting data of the population, production value and GDP as trained network input, it calculates the future land demand. The simulation result of this method is proved to be satisfactory after comparing it with traditional statistical model forecasting results.

Info:

Periodical:

Edited by:

Qi Luo

Pages:

1154-1161

DOI:

10.4028/www.scientific.net/AMM.58-60.1154

Citation:

Y. L. Liu and J. Q. Yang, "Indicators Forecasting and Empirical Analysis of Regional Economic Development Based on Neural Network", Applied Mechanics and Materials, Vols. 58-60, pp. 1154-1161, 2011

Online since:

June 2011

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Price:

$35.00

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