摘要
由一位新闻记者-机器人与机器学习的工作人员新闻编辑每日新闻-关于人工智能的最新研究结果已经发表。根据NewsRx记者从印度Uttarakhand发回的消息，研究表明：“早期信息交换对预测的作物产量可以起到降低不安全风险的作用。在本研究中，利用过去的时间序列产量数据和天气指数，共建立了六个多变量模型，即：。”新闻记者从g.b.那里获得了这项研究的一句话。潘特农业与技术大学：Uttarakhand三个主要大豆产区的SMLR、PCA-SMLR、ANN、PCA-ANN、SMLR-ANN和PCA-S MLR-ANNUdham Singh Nagar和Uttarkashi。进一步分析通过固定80%的校准数据和剩余的验证数据来预测大豆产量。利用每日Weather数据计算物候平均值。这些平均值随后用于计算加权和未加权天气指数。PCA-SMLR-ANN，SMLR-ANN模型和PCA-A神经网络模型分别是Almora、Ud Ham Singh Nagar和Uttarkashi地区大豆产量的最佳预测模型。
Abstract
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."
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