首页|University of Sulaimani Researcher Describes Research in Machine Learning (Forec asting daily rainfall in a humid subtropical area: an innovative machine learnin g approach)
University of Sulaimani Researcher Describes Research in Machine Learning (Forec asting daily rainfall in a humid subtropical area: an innovative machine learnin g approach)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Researchers detail new data in artific ial intelligence. According to news originating from Sulaymaniyah, Iraq, by News Rx correspondents, research stated, “ABSTRACT: Hydrological modeling is one of t he most complicated tasks in sustainable water resources management, particularl y in terms of predicting rainfall.” The news correspondents obtained a quote from the research from University of Su laimani: “Predicting rainfall is critical to build a sustainable society in term s of hydropower operations, agricultural planning, and flood control. In this st udy, a hybrid model based on the integration of k-nearest neighbor (KNN), XGBoos t (XGB), decision tree (DCT), and Random Forest (RF) has been developed and impl emented for forecasting daily rainfall for the first time at Sydney airport, Aus tralia. Daily rainfall, temperature, evaporation, and humidity have been selecte d as input parameters. Three statistical measurements, namely, root mean square error (RMSE), Coefficient of determination (R2), mean absolute error (MAE), and Normalized Root Mean Square Error (NRMSE) have been utilized in order to check t he accuracy of the proposed model.”
University of SulaimaniSulaymaniyahI raqCyborgsEmerging TechnologiesMachine Learning
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