Flood susceptibility assessment in Hengfeng area coupling adaptive neuro-fuzzy inference system with genetic algorithm and differential evolution.
By Haoyuan Hong, Mahdi Panahi, Ataollah Shirzadi, Tianwu Ma, Junzhi Liu, A-Xing Zhu, Wei Chen, I. Kougias, N. Kazakis. Science of the Total Environment, 2018
389 citations recorded by the source corpus.
Subfields: Global and Planetary Change, Water Science and Technology
View Paper: https://www.semanticscholar.org/paper/078055c3ec6a8724293f722bc3dccea1e14ef641
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Global and Planetary Change
- Khabat Khosravi
- Ataollah Shirzadi
- Himan Shahabi
- Baharin bin Ahmad
- D. Tien Bui
- Mahdi Panahi
- N. Al‐Ansari
- Omid Rahmati
In Water Science and Technology
Citations in the corpus
- Flood Detection and Susceptibility Mapping Using Sentinel-1 Remote Sensing Data and a Machine Learning Approach: Hybrid Intelligence of Bagging Ensemble Based on K-Nearest Neighbor Classifier (2020, background): “Rainfall has an obvious and direct effect on flood occurrence [9,16,17,37,92] and, for flood susceptibility mapping, is most commonly expressed as annual rainfall [93].”
- Spatial prediction of groundwater spring potential mapping based on an adaptive neuro-fuzzy inference system and metaheuristic optimization (2018, background): “SWARA has received great attention in various fields in the last 5 years (Alimardani et al., 2013; Hong et al., 2018).”