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Advancing urban water-energy demand predictions with a ro... | ResearchHub
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Advancing urban water-energy demand predictions with a rotor hopfield neural network model optimized by contracted thermal exchange optimizer
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Authors
Ziming Zhao
1 more
Ziming Zhao
•
Milad Teimourian
Published
May 25, 2024
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Journal
Energy Sources Part A Recovery Utilization and Environmental Effects
Topics
Computer Science
Artificial Intelligence
Physics
Engineering
Electrical And Electronic Engineering
Show all topics
DOI
10.1080/15567036.2024.2357243
