.png){kind=icon}
返回
Two-step approach based multi-objective groundwater remediation using enhanced random vector functional link integrated with evolutionary marine predator algorithm
.png){kind=icon}
PRE
AI
DOI：10.1016/j.jconhyd.2023.104201.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
We here propose a two-step approach-based simulation-optimization model for multi-objective groundwater remediation using enhanced random vector functional link (ERVFL) and evolutionary marine predator algorithm (EMPA). In this study, groundwater flow and solute transport models are developed using MODFLOW and MT3DMS. The ERVFL network is used to approximate the flow and transport models, enhancing the computational performance. This study also improves the robustness of the ERVFL network using a kernel density estimator (KDE) based weighted least square approach. We further develop the EMPA by modifying the marine predator algorithm (MPA) using elite opposition-based learning, biological evolution operators, and elimination mechanisms. In the multi-objective version of EMPA, the non-dominated/Pareto-optimal solutions are stored in an external repository using an archive controller and adaptive grid mechanism to promote better convergence and diversity of the Pareto front. The proposed methodologies are applied for multi-objective groundwater remediation of a hypothetical unconfined aquifer based on the two-step method. The first step directly integrates flow and transport models with EMPA and finds the optimal locations of pumping wells by minimizing the percent of contaminant mass remaining in the aquifer. In the second step, the ERVL-based proxy model is integrated with EMPA and used for multi-objective optimization while explicitly using the pumping well locations obtained in the first step. The multi-objective optimization generates a Pareto-optimal solution representing the relationship between the rate of pumping and the amount of contaminant mass in the aquifer. Further analyses show a significant advantage of the two-step approach over a traditional method for multi-objective groundwater remediation.
Keyword:
Groundwater remediation
Multi -objective optimization
Enhanced random vector functional link~(ERVFL)
Evolutionary marine predator algorithm~(EMPA)
期刊
IF:
4.4
论文数:
3.5K
被引数:
6.5K
机构
引用论文
Physicochemical and sensory characteristics of commercial, frozen, dry, and wet-aged Hanwoo sirloins
OAAI
OAAI分享收藏分享收藏Integrated Microfluidic Sample-to-Answer System for Direct Nucleic Acid-Based Detection of Group B Streptococci in Clinical Vaginal/Anal Swab Samples.png)
ACS Sensors
ACS SensorsIF0
PREAI
分享收藏Optimal design of groundwater remediation system using a probabilistic multi-objective fast harmony search algorithm under uncertaintyJOURNAL OF HYDROLOGY
JOURNAL OF HYDROLOGYIF6.3
PREAI
分享收藏
查看更多内容