Advancing urban water-energy demand predictions with a rotor hopfield neural network model optimized by contracted thermal exchange optimizer
Author:
Affiliation:
1. School of Urban Economics and Public Administration, Capital University of Economics and Business, Beijing, China
2. Tehran Branch, Islamic Azad University, Tehran, Iran
3. College of Technical Engineering, The Islamic University, Najaf, Iraq
Funder
no funding associated
Publisher
Informa UK Limited
Link
https://www.tandfonline.com/doi/pdf/10.1080/15567036.2024.2357243
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1. Experimental modeling of PEM fuel cells using a new improved seagull optimization algorithm
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3. A new methodology to estimate future water‐energy nexus based on artificial neural networks
4. A new biomass-based hybrid energy system integrated with a flue gas condensation process and energy storage option: An effort to mitigate environmental hazards
5. Optimal modeling of combined cooling, heating, and power systems using developed African Vulture Optimization: a case study in watersport complex
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