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首页> 外文期刊>The Indian Journal of Agricultural Sciences >Forecasting of wheat (Triticum aestivum) yield using ordinal logistic regression
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Forecasting of wheat (Triticum aestivum) yield using ordinal logistic regression

机译:运用序数逻辑回归预测小麦(Triticum aestivum)产量

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摘要

In this study, uses of ordinal logistic model based on weather data has been attempted for forecasting wheat (Triticum aestivum L.) yield in Kanpur district of Uttar Pradesh. Weekly weather data (1971-72 to 2009-10) on maximum temperature, minimum temperature, morning relative humidity, evening relative humidity and rainfall for 16 weeks of the crop cultivation along with the yield data of wheat crop have been considered in the study. Crop years were divided into two and three groups based on the detrended yield. Yield forecast models have been developed using probabilities obtained through ordinal logistic regression along with year as regressors for different weeks. Data from 1971-72 to 2006-07 have been utilized for model fitting and subsequent three years (2007-08 to 2009-10) were used for the validation of the model. Evaluation of the performance of the models developed at different weeks has been done by Adj R-2, PRESS (Predicted error sums of squares) and number of misclassifications. Evaluation of the forecasts were done by RMSE (Root mean square error) and MAPE (Mean absolute percentage error) of forecast
机译:在这项研究中,已经尝试使用基于天气数据的序数逻辑模型来预测北方邦坎普尔地区的小麦(Triticum aestivum L.)单产。研究中考虑了作物生长的16周的最高温度,最低温度,早晨相对湿度,晚上相对湿度和降雨量的每周天气数据(1971-72至2009-10)以及小麦作物的产量数据。根据减产趋势,将作物年分为两组和三组。已使用通过序数逻辑回归获得的概率以及年份作为不同周的回归值来开发产量预测模型。 1971-72年至2006-07年的数据已用于模型拟合,随后三年(2007-08年至2009-10年)用于模型验证。对Adj R-2,PRESS(预测的误差平方和)和错误分类的数量进行了评估,以评估在不同星期开发的模型的性能。通过RMSE(均方根误差)和MAPE(平均绝对百分比误差)对预测进行评估

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