首页|G.B. Pant University of Agriculture and Technology Researchers Release New Study Findings on Machine Learning (Comparison of phenological weather indices based statistical, machine learning and hybrid models for soybean yield forecasting in ...)
G.B. Pant University of Agriculture and Technology Researchers Release New Study Findings on Machine Learning (Comparison of phenological weather indices based statistical, machine learning and hybrid models for soybean yield forecasting in ...)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Current study results on artificial in telligence have been published. According to news originating from Uttarakhand, India, by NewsRx correspondents, research stated, "Early information exchange re garding predicted crop production could play a role in lowering the danger of fo od insecurity. In this study total six multivariate models were developed using past time series yield data and weather indices viz." The news reporters obtained a quote from the research from G.B. Pant University of Agriculture and Technology: "SMLR, PCA-SMLR, ANN, PCA-ANN, SMLR-ANN and PCA-S MLR-ANN for three major soybean producing districts of Uttarakhand viz. Almora, Udham Singh Nagar and Uttarkashi. Further analysis was done by fixing 80% of the data for calibration and the remaining dataset for validation to predict soybean yield. Phenology wise average values were computed using the daily weath er data. These average values are subsequently employed in the computation of bo th weighted and unweighted weather indices. The PCA-SMLR-ANN, SMLR-ANN and PCA-A NN models were found to be the best soybean yield predictor model for Almora, Ud ham Singh Nagar and Uttarkashi districts, respectively."
G.B. Pant University of Agriculture and TechnologyUttarakhandIndiaAsiaCyborgsEmerging TechnologiesMachine Le arning
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