Application of Generalized Regression Neural Network to the Agricultural Machinery Demand Forecasting-Reference-Cited by-同舟云学术

Application of Generalized Regression Neural Network to the Agricultural Machinery Demand Forecasting

Published:2013-01 Issue: Volume:278-280 Page:2177-2182
ISSN:1662-7482
Container-title:Applied Mechanics and Materials
language:
Short-container-title:AMM

Author:

Luo Wei¹,Fu Zhuo¹

Affiliation:

1. Central South University

Abstract

Proposed an agricultural machinery demand forecasting model based on the generalized regression neural network. This model is based on GRNN, using the circulation testing algorithm combined with k-fold cross validation for parameters optimization and network training, and achieves satisfying forecasting precision in the case of small samples. By using the data of total power agricultural machinery and relevant factors from the year 1995 to 2010 in Guangxi province, we tested and verified the effectiveness of the model.

Publisher

Trans Tech Publications, Ltd.

Link

https://www.scientific.net/AMM.278-280.2177.pdf

Reference8 articles.

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