首页|Study Data from Army Engineering University Update Knowledge of Machine Learning (Enhancing Building Energy Efficiency: an Integrated Approach To Predicting Hea ting and Cooling Loads Using Machine Learning and Optimization Algorithms)
Study Data from Army Engineering University Update Knowledge of Machine Learning (Enhancing Building Energy Efficiency: an Integrated Approach To Predicting Hea ting and Cooling Loads Using Machine Learning and Optimization Algorithms)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews - New research on Machine Learning is the subject o f a report. According to news originating fromJiangsu, People’s Republic of Chi na, by NewsRx correspondents, research stated, “Predicting cooling andheating l oads is essential for efficient building energy management in order to maintain indoor comfort.This study employs machine learning methods containing Support V ector Regression (SVR), ExtremeGradient Boosting (XGB), and a Dempster-Shafer T heory-based ensemble model using a dataset of 768samples. 5-fold cross-validati on selects 80 % of the dataset for training, with optimization alg orithmslike Coot, Dingo, and Sea-Horse Optimizers fine-tuning model applicabili ty.”
JiangsuPeople’s Republic of ChinaAsi aAlgorithmsCyborgsEmerging TechnologiesMachine LearningOptimization Al gorithmsArmy Engineering University
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