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contributor authorAlsumaiei, Abdullah A.
date accessioned2026-08-20T21:27:42Z
date available2026-08-20T21:27:42Z
date copyright2025/11/26
date issued2026
identifier otherJCCEE5.CPENG-7139.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4314491
description abstractAbstractThis study presents a robust computational framework that integrates long short-term memory (LSTM) neural networks with four advanced metaheuristic optimization algorithms: Nondominated Sorting Genetic Algorithm II (NSGA-II), Particle Swarm ...
publisherAmerican Society of Civil Engineers
titleQuantifying Irrigation Water Demand through Optimized Daily Vapor Pressure Deficit Forecasting Using LSTM and Metaheuristic Algorithms
typeJournal Article
journal volume40
journal issue2
journal titleJournal of Computing in Civil Engineering
identifier doi10.1061/JCCEE5.CPENG-7139
journal fristpage04025155-1
journal lastpage04025155-13
page13
treeJournal of Computing in Civil Engineering:;2026:;Volume ( 040 ):;issue: 002
contenttypeFulltext


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