Search Results - "KHOSRAVI, Khabat"

Corrigendum: Hydrology Research 50 (6), 1645–1664: Difference in the bed load transport of graded and uniform sediments during floods: An experimental investigation, Khabat Khosravi, Amir H. N. Chegini, Andrew D. Binns, Prasad Daggupati and Luca Mao, https://doi.org/10.2166/nh.2019.078 by Khosravi, Khabat

“…The authors regret that the affiliation details for Khabat Khosravi were presented incorrectly in their original paper and apologise for any inconvenience…”
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A comparative assessment of decision trees algorithms for flash flood susceptibility modeling at Haraz watershed, northern Iran by Khosravi, Khabat, Pham, Binh Thai, Chapi, Kamran, Shirzadi, Ataollah, Shahabi, Himan, Revhaug, Inge, Prakash, Indra, Tien Bui, Dieu

“…Floods are one of the most damaging natural hazards causing huge loss of property, infrastructure and lives. Prediction of occurrence of flash flood locations…”
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Using Optimized Deep Learning to Predict Daily Streamflow: A Comparison to Common Machine Learning Algorithms by Khosravi, Khabat, Golkarian, Ali, Tiefenbacher, John P.

“…From a watershed management perspective, streamflow need to be predicted accurately using simple, reliable, and cost-effective tools. Present study…”
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Flash flood susceptibility analysis and its mapping using different bivariate models in Iran: a comparison between Shannon’s entropy, statistical index, and weighting factor models by Khosravi, Khabat, Pourghasemi, Hamid Reza, Chapi, Kamran, Bahri, Masoumeh

“…Flooding is a very common worldwide natural hazard causing large-scale casualties every year; Iran is not immune to this thread as well. Comprehensive flood…”
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A comparison between advanced hybrid machine learning algorithms and empirical equations applied to abutment scour depth prediction by Khosravi, Khabat, Khozani, Zohreh Sheikh, Mao, Luca

“…•5 new hybrid machine learning models applied to abutment scour depth prediction.•A standalone machine learning model and 2 empirical methods served as…”
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A comparative assessment of flood susceptibility modeling using Multi-Criteria Decision-Making Analysis and Machine Learning Methods by Khosravi, Khabat, Shahabi, Himan, Pham, Binh Thai, Adamowski, Jan, Shirzadi, Ataollah, Pradhan, Biswajeet, Dou, Jie, Ly, Hai-Bang, Gróf, Gyula, Ho, Huu Loc, Hong, Haoyuan, Chapi, Kamran, Prakash, Indra

“…[Display omitted] •MCDM and machine learning models were compared for flood modelling.•Results show that machine learning is more potential for flood…”
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Assessment of advanced random forest and decision tree algorithms for modeling rainfall-induced landslide susceptibility in the Izu-Oshima Volcanic Island, Japan by Dou, Jie, Yunus, Ali P., Tien Bui, Dieu, Merghadi, Abdelaziz, Sahana, Mehebub, Zhu, Zhongfan, Chen, Chi-Wen, Khosravi, Khabat, Yang, Yong, Pham, Binh Thai

“…Landslides represent a part of the cascade of geological hazards in a wide range of geo-environments. In this study, we aim to investigate and compare the…”
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Convolutional neural network approach for spatial prediction of flood hazard at national scale of Iran by Khosravi, Khabat, Panahi, Mahdi, Golkarian, Ali, Keesstra, Saskia D., Saco, Patricia M., Bui, Dieu Tien, Lee, Saro

“…•Flood susceptibility map at a scale of Iran derived based on deep learning convolutional neural networks.•15% of the entire country is highly to very highly…”
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Iterative classifier optimizer-based pace regression and random forest hybrid models for suspended sediment load prediction by Meshram, Sarita Gajbhiye, Safari, Mir Jafar Sadegh, Khosravi, Khabat, Meshram, Chandrashekhar

“…Suspended sediment load is a substantial portion of the total sediment load in rivers and plays a vital role in determination of the service life of the…”
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Novel GIS Based Machine Learning Algorithms for Shallow Landslide Susceptibility Mapping by Shirzadi, Ataollah, Soliamani, Karim, Habibnejhad, Mahmood, Kavian, Ataollah, Chapi, Kamran, Shahabi, Himan, Chen, Wei, Khosravi, Khabat, Thai Pham, Binh, Pradhan, Biswajeet, Ahmad, Anuar, Bin Ahmad, Baharin, Tien Bui, Dieu

“…The main objective of this research was to introduce a novel machine learning algorithm of alternating decision tree (ADTree) based on the multiboost (MB),…”
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Novel Hybrid Evolutionary Algorithms for Spatial Prediction of Floods by Bui, Dieu Tien, Panahi, Mahdi, Shahabi, Himan, Singh, Vijay P., Shirzadi, Ataollah, Chapi, Kamran, Khosravi, Khabat, Chen, Wei, Panahi, Somayeh, Li, Shaojun, Ahmad, Baharin Bin

“…Adaptive neuro-fuzzy inference system (ANFIS) includes two novel GIS-based ensemble artificial intelligence approaches called imperialistic competitive…”
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Application and Comparison of Decision Tree-Based Machine Learning Methods in Landside Susceptibility Assessment at Pauri Garhwal Area, Uttarakhand, India by Pham, Binh Thai, Khosravi, Khabat, Prakash, Indra

“…Landslide susceptibility assessment has been conducted at the Pauri Garhwal area of Uttarakhand state, India, an area affected by numerous landslides causing…”
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Land Subsidence Susceptibility Mapping in South Korea Using Machine Learning Algorithms by Tien Bui, Dieu, Shahabi, Himan, Shirzadi, Ataollah, Chapi, Kamran, Pradhan, Biswajeet, Chen, Wei, Khosravi, Khabat, Panahi, Mahdi, Bin Ahmad, Baharin, Saro, Lee

“…In this study, land subsidence susceptibility was assessed for a study area in South Korea by using four machine learning models including Bayesian Logistic…”
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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 by Shahabi, Himan, Shirzadi, Ataollah, Ghaderi, Kayvan, Omidvar, Ebrahim, Al-Ansari, Nadhir, Clague, John J., Geertsema, Marten, Khosravi, Khabat, Amini, Ata, Bahrami, Sepideh, Rahmati, Omid, Habibi, Kyoumars, Mohammadi, Ayub, Nguyen, Hoang, Melesse, Assefa M., Ahmad, Baharin Bin, Ahmad, Anuar

“…Mapping flood-prone areas is a key activity in flood disaster management. In this paper, we propose a new flood susceptibility mapping technique. We employ new…”
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A GIS-based groundwater pollution potential using DRASTIC, modified DRASTIC, and bivariate statistical models by Khosravi, Khabat, Sartaj, Majid, Karimi, Mahshid, Levison, Jana, Lotfi, Aghdas

“…The objective of the current study is groundwater vulnerability assessment using DRASTIC, modified DRASTIC, and three statistical bivariate models (frequency…”
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Flood Spatial Modeling in Northern Iran Using Remote Sensing and GIS: A Comparison between Evidential Belief Functions and Its Ensemble with a Multivariate Logistic Regression Model by Tien Bui, Duie, Khosravi, Khabat, Shahabi, Himan, Daggupati, Prasad, Adamowski, Jan F., M.Melesse, Assefa, Thai Pham, Binh, Pourghasemi, Hamid Reza, Mahmoudi, Mehrnoosh, Bahrami, Sepideh, Pradhan, Biswajeet, Shirzadi, Ataollah, Chapi, Kamran, Lee, Saro

“…Floods are some of the most dangerous and most frequent natural disasters occurring in the northern region of Iran. Flooding in this area frequently leads to…”
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Landslide Susceptibility Mapping Using Different GIS-Based Bivariate Models by Nohani, Ebrahim, Moharrami, Meisam, Sharafi, Samira, Khosravi, Khabat, Pradhan, Biswajeet, Binh Thai Pham, Lee, Saro, Melesse, Assefa M

“…Landslides are the most frequent phenomenon in the northern part of Iran, which cause considerable financial and life damages every year. One of the most…”
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New Hybrids of ANFIS with Several Optimization Algorithms for Flood Susceptibility Modeling by Tien Bui, Dieu, Khosravi, Khabat, Li, Shaojun, Shahabi, Himan, Panahi, Mahdi, Singh, Vijay, Chapi, Kamran, Shirzadi, Ataollah, Panahi, Somayeh, Chen, Wei, Bin Ahmad, Baharin

“…This study presents three new hybrid artificial intelligence optimization models—namely, adaptive neuro-fuzzy inference system (ANFIS) with cultural…”
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Optimization of an adaptive neuro-fuzzy inference system for groundwater potential mapping by Termeh, Seyed Vahid Razavi, Khosravi, Khabat, Sartaj, Majid, Keesstra, Saskia Deborah, Tsai, Frank T.-C., Dijksma, Roel, Pham, Binh Thai

“…The main goal of this study was to optimize an adaptive neuro-fuzzy inference system (ANFIS) using three meta-heuristic optimization algorithms—genetic…”
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River Water Salinity Prediction Using Hybrid Machine Learning Models by Melesse, Assefa M., Khosravi, Khabat, Tiefenbacher, John P., Heddam, Salim, Kim, Sungwon, Mosavi, Amir, Pham, Binh Thai

“…Electrical conductivity (EC), one of the most widely used indices for water quality assessment, has been applied to predict the salinity of the Babol-Rood…”
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