標題: Accuracy Analysis Mechanism for Agriculture Data Using the Ensemble Neural Network Method
作者: Kung, Hsu-Yang
Kuo, Ting-Huan
Chen, Chi-Hua
Tsai, Pei-Yu
資訊管理與財務金融系 註:原資管所+財金所
Department of Information Management and Finance
關鍵字: ensemble neural network;data mining;multiple regression analysis;stepwise regression;yield prediction models
公開日期: 八月-2016
摘要: With the rise and development of information technology (IT) services, the amount of data generated is rapidly increasing. Data from many different places are inconsistent. Data capture, storage and analysis have major challenges. Most data analysis methods are unable to handle such large amounts of data. Many studies employ neural networks, mostly specifying the number of hidden layers and neurons according to experience or formula. Different sets of network topologies have different results, and the best network model is selected. This investigation proposes a system based on the ensemble neural network (ENN). It creates multiple network models, each with different numbers of hidden layers and neurons. A model that does not achieve the accuracy rate is discarded. The proposed system derives the weighted average of all remaining network models to improve the accuracy of the prediction. This study applies the proposed method to generate agricultural yield predictions. The agricultural production process in Taiwan is more complex than those of manufacturing or other industries. The Council of Agriculture provides agricultural forecasting primarily based on the planted area and experience to predict the yield, but without consideration of the overall planting environment. This work applies the proposed data analysis method to agriculture. The method based on ENN has a much lower error rate than traditional back-propagation neural networks, while multiple regression analysis has an error rate of 12.4%. Experimental results reveal that the ENN method is better than traditional back-propagation neural networks and multiple regression analysis.
URI: http://dx.doi.org/10.3390/su8080735
http://hdl.handle.net/11536/134108
ISSN: 2071-1050
DOI: 10.3390/su8080735
期刊: SUSTAINABILITY
Volume: 8
Issue: 8
顯示於類別:期刊論文