首页|Necmettin Erbakan University Researcher Broadens Understanding of Machine Learni ng (Are Supervised Learning Methods Suitable for Estimating Crop Water Consumpti on under Optimal and Deficit Irrigation?)
Necmettin Erbakan University Researcher Broadens Understanding of Machine Learni ng (Are Supervised Learning Methods Suitable for Estimating Crop Water Consumpti on under Optimal and Deficit Irrigation?)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on ar tificial intelligence. According to news reporting out of Necmettin Erbakan Univ ersity by NewsRx editors, research stated, “This study examined the performance of random forest (RF), support vector machine (SVM) and adaptive boosting (AB) m achine learning models used to estimate daily potato crop evapotranspiration adj usted (ETc-adj) under full irrigation (I100), 50% of full irrigati on supply (I50) and rainfed cultivation (I0).”
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