A hybrid artificial intelligence approach using GIS-based neural-fuzzy inference system and particle swarm optimization for forest fire susceptibility modeling at a tropical area
By D. Tien Bui, Quang-Thanh Bui, Quoc-Phi Nguyen, Biswajeet Pradhan, Haleh Nampak, P. T. Trinh. 2017
343 citations recorded by the source corpus.
Subfields: Global and Planetary Change, Management, Monitoring, Policy and Law
View Paper: https://www.semanticscholar.org/paper/cd1d7fa132422816eb6b596cf711baa309abb8fe
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
- Mahdi Panahi
- D. Tien Bui
- Binh Thai Pham
- Indra Prakash
- Biswajeet Pradhan
- Hamid Reza Pourghasemi
In Management, Monitoring, Policy and Law
- Khabat Khosravi
- Mahdi Panahi
- D. Tien Bui
- Binh Thai Pham
- Indra Prakash
- Biswajeet Pradhan
- Hamid Reza Pourghasemi
Citations in the corpus
- Spatial prediction of groundwater spring potential mapping based on an adaptive neuro-fuzzy inference system and metaheuristic optimization (2018, background): “…fuzzy logic and neural networks, i.e., an adaptive neuro-fuzzy inference system (ANFIS), has proven it is efficient in terms of high accuracy (Lohani et al., 2012; Emamgholizadeh et al., 2014; Zare and Koch, 2018; Bui et al., 2018; Nourani et al., 2016; Tien Bui et al., 2017; Pham et al., 2018a).”