Forecasting agriculture water consumption based on PSO and SVM

Abstract

Forecasting agriculture water consumption is significant to optimize confiration of water resources. In the paper, we have combined particle swarm optimization (PSO) and support vector machines (SVM) for agriculture water consumption forecasting. Compared to GA, the advantages of PSO are that PSO is easy to implement and there are few parameters to adjust… (More)

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Cite this paper

@article{Lu2009ForecastingAW, title={Forecasting agriculture water consumption based on PSO and SVM}, author={Sheng Lu and Zhong-jinan Cai and Xiao-bin Zhang}, journal={2009 2nd IEEE International Conference on Computer Science and Information Technology}, year={2009}, pages={147-150} }