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Crop Yield Forecasting by Adaptive Neuro Fuzzy Inference System

机译:自适应神经模糊推理系统预测作物产量

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Meteorological uncertainties affect crop yield portentously during different stages of crop growing seasons, therefore several studies have been carried out to forecast crop yield using climatic parameters with empirical statistical regression equations relating regional yield with predictor variables. In this study an attempt has been made to develop Crop Yield Forecasting models to map relation between climatic data and crop yield. Present study was undertaken for forecasting rice yield by adaptive neuro fuzzy inference system (ANFIS) technique based on time series data of 27 years, yield and weather data (w.e.f. 1981-82 to 2007-08) obtained from G. B. Pant University of Agriculture and Technology, Pantnagar, District Udham Singh Nagar, Uttarakhand, India.
机译:气象不确定性在农作物生长季节的不同阶段会严重影响农作物的产量,因此,已经进行了一些研究,利用气候参数和经验统计回归方程将农作物的产量与预测变量联系起来,以预测农作物的产量。在这项研究中,已经尝试开发作物产量预测模型,以绘制气候数据和作物产量之间的关系。目前的研究是基于27年的时间序列数据,从GB Pant农业技术大学获得的产量和天气数据(1981-82年至2007-08年),利用自适应神经模糊推理系统(ANFIS)技术预测水稻产量。 ,Pantnagar,区Udham Singh Nagar,印度北阿坎德邦。

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