摘要
一位新闻记者-机器人与机器学习的新闻编辑-每日新闻-关于人工智能的研究结果在一份新的报告中讨论。根据NewsRx编辑对印度West Be Ngal的新闻报道，研究表明，"Cooch Behar种植的黄麻作物每年因几种主要害虫如黄螨(Polyphagotarsone mus latus Banks)和Jute Semilooper(Anomis sabulifera Guen)而遭受大量的物质和经济损失"。我们的新闻记者引用了Uttar Banga Krishi Viswavidyalaya的研究:“构建的季节图显示,黄螨在55天时最大,黄麻半环虫在45天时最大。相关分析表明,当周最低气温At、滞后一周最大相对湿度、最低气温、滞后2周的最小和最大相对湿度与黄麻叶螨发病率显著相关,滞后2周的最小和最大相对湿度与黄麻叶螨发病率显著相关,分别用RMSE值拟合和验证了ARIMA、ARIMAX、SARIMA、SARIMAX和SVR预测模型。SARIMAX模型拟合效果最好，其次是SVR和SARIMA，同样，ARIMAX模型对黄螨的均方均方误差最小，其次是SVR和ARIMA。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Research findings on artificial intell igence are discussed in a new report. According to news reporting out of West Be ngal, India, by NewsRx editors, research stated, "Jute crop cultivated in Cooch Behar suffers a substantial amount of physical and economical loss every year du e to several major insect pest infestation such as Yellow Mite (Polyphagotarsone mus latus Banks) and Jute Semilooper (Anomis sabulifera Guen)." Our news journalists obtained a quote from the research from Uttar Banga Krishi Viswavidyalaya: "Constructed seasonal plots reveal that for Yellow Mite pest inc idence is maximum at 55 DAS, while for Jute Semi Looper it is at 45 DAS. Correla tion analysis indicate that the weather parameters such as minimum temperature a t current week, maximum RH at one week lag, minimum temperature, minimum and max imum RH at two week lag are significantly correlated with the incidence of Yello w Mite, while in case of Jute Semilooper maximum temperature, minimum and maximu m RH at two week lag are significantly correlated. Different forecasting models like ARIMA, ARIMAX, SARIMA, SARIMAX and SVR have been fitted and validated using RMSE values. In case of Jute Semilooper, SARIMAX model is found to be the best fitted model followed by SVR and SARIMA. Similarly, for Yellow Mite ARIMAX model produces the least RMSE value followed by SVR and ARIMA."
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