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<div><p>To improve the intelligent and refined management level of power distribution systems in equipment operation and maintenance as well as emergency support, this work proposes an integrated “prediction-optimization” model that combines genetic algorithm (GA) with machine learning m...

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Bibliographic Details
Main Author:	Qingbo Tu (22641033) (author)
Other Authors:	Hongyang Zhang (1447096) (author), Weiwei Li (364036) (author), Jing Duan (503000) (author), Chao Kong (838413) (author)
Published:	2025
Subjects:	Science Policy Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified transmission system operators temporal fusion transformer single machine learning refined management level objective coupling imbalance machine learning methods integrated &# 8220 extreme weather scenarios determination reaches 0 certain practical value traditional fragmented optimization optimization &# 8221 redundant inventory ratio average inventory level time series forecasting power distribution systems optimize model parameters fusion model based unit prediction error model significantly reduces model performance based method uses ga inventory optimization stage combines genetic algorithm typical equipment prediction inventory optimization model reduces genetic algorithm distribution equipment prediction stage inventory decisions demand forecasting comprehensive performance heuristic algorithm equipment operation prediction link xlink "> work proposes load fluctuations european network empirical support emergency support dynamically integrates dataset shows beats ). 41 %,
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