Structural and empirical knowledge driven multi-objective evolutionary algorithm for urban drainage system design-Reference-Cited by-同舟云学术

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Structural and empirical knowledge driven multi-objective evolutionary algorithm for urban drainage system design

Published:2024-09 Issue: Volume:249 Page:123461
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Wu Yali^ORCID,Zheng Shuailong,Liu Qing,Dong Ang,Li Qiyue

Publisher

Elsevier BV

Reference60 articles.

1. Optimization models for layout and pipe design for storm sewer systems;Alfaisal;Water Resources Management,2021

2. Comparison of the performance of a surrogate based gaussian process, NSGA2 and PSO multi-objective optimization of the operation and fuzzy structural reliability of water distribution system: Case study for the city of Asmara, Eritrea;Balekelayi;Water Resources Management,2022

3. Urban drainage decision model for storm emergency management based on multi-objective optimization;Bao;Stochastic Environmental Research and Risk Assessment,2023

4. A surrogate-assisted reference vector guided evolutionary algorithm for computationally expensive many-objective optimization;Chugh;IEEE Transactions on Evolutionary Computation,2018

5. Hybrid many-objective particle swarm optimization algorithm for green coal production problem;Cui;Information Sciences,2020

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1. Deep Learning-Based Approach for Optimizing Urban Commercial Space Expansion Using Artificial Neural Networks;Applied Sciences;2024-04-30

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