A Mamdani Adaptive Neural Fuzzy Inference System for Improvement of Groundwater Vulnerability-Reference-Cited by-同舟云学术

A Mamdani Adaptive Neural Fuzzy Inference System for Improvement of Groundwater Vulnerability

Published:2018-01-23 Issue:6 Volume:56 Page:978-985
ISSN:0017-467X
Container-title:Groundwater
language:en
Short-container-title:Groundwater

Author:

Agoubi Belgacem,Dabbaghi Radhia¹,Kharroubi Adel¹

Affiliation:

1. Higher Institute of Water Sciences and Techniques; University of Gabes, Campus Universitaire; Gabès 6072 Tunisia

Publisher

Wiley

Subject

Computers in Earth Sciences,Water Science and Technology

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1111/gwat.12634/fullpdf

Reference22 articles.

1. Aller , L. 1985

2. Modeling the risk of groundwater contamination using modified DRASTIC and GIS in Amman-Zerqa Basin;Al-Rawabdeh;Central European Journal of Engineering,2014

3. Application of groundwater vulnerability overlay and index methods to the Jijel plain area;Boufekane;Groudwater,2017

4. Evaluating the rate of aggregative risk in software development using fuzzy set theory;Chen;Cybernetics and Systems: International Journal,1999

Cited by 13 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Geophysical contribution using electrical resistivity to study the Triassic sandstone aquifer, southeastern Tunisia;Journal of African Earth Sciences;2024-02

2. Multi-criteria evaluation (MCE) of groundwater prospect and vulnerability index mapping from Second-order geo-electric indices: A case study of coastal environments;2023-09-22

3. Application of neuro-fuzzy ensembles across domains: A systematic review of the two last decades (2000–2022);Engineering Applications of Artificial Intelligence;2023-09

4. Assessment of Urbanization Impacts on Coastal Aquifer Vulnerability by Seawater Intrusion Using GIS-Based Modified GALDIT-B Model: A Case Study of South Chennai Coastal Region, Tamil Nadu, India.;2023-04-06

5. Groundwater quality for irrigation in an arid region—application of fuzzy logic techniques;Environmental Science and Pollution Research;2022-11-23