S
Shahab S. Band
Researcher at National Yunlin University of Science and Technology
Publications - 168
Citations - 2407
Shahab S. Band is an academic researcher from National Yunlin University of Science and Technology. The author has contributed to research in topics: Computer science & Engineering. The author has an hindex of 10, co-authored 87 publications receiving 358 citations. Previous affiliations of Shahab S. Band include Duy Tan University & Hungarian Academy of Sciences.
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Flash Flood Susceptibility Modeling Using New Approaches of Hybrid and Ensemble Tree-Based Machine Learning Algorithms
Shahab S. Band,Saeid Janizadeh,Subodh Chandra Pal,Asish Saha,Rabin Chakrabortty,Assefa M. Melesse,Amirhosein Mosavi +6 more
TL;DR: Topographical and hydrological parameters, e.g., altitude, slope, rainfall, and the river’s distance, were the most effective parameters in the flash flood susceptibility modeling of Kalvan watershed.
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Novel Ensemble Approach of Deep Learning Neural Network (DLNN) Model and Particle Swarm Optimization (PSO) Algorithm for Prediction of Gully Erosion Susceptibility
Shahab S. Band,Shahab S. Band,Saeid Janizadeh,Subodh Chandra Pal,Asish Saha,Rabin Chakrabortty,Manouchehr Shokri,Amirhosein Mosavi +7 more
TL;DR: It can be concluded that the DLNN model and its ensemble with the PSO algorithm can be used as a novel and practical method to predict gully erosion susceptibility, which can help planners and managers to manage and reduce the risk of this phenomenon.
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Principal Component Analysis to Study the Relations between the Spread Rates of COVID-19 in High Risks Countries
Mohammad Reza Mahmoudi,Mohammad Hossein Heydari,Sultan Noman Qasem,Sultan Noman Qasem,Amirhosein Mosavi,Shahab S. Band,Shahab S. Band +6 more
TL;DR: In this article, the number of patients with Covid-19 and number of deaths due to this disease in France, Germany, Iran, Italy, Spain, United Kingdom, and Unites States America are considered.
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A New Online Learned Interval Type-3 Fuzzy Control System for Solar Energy Management Systems
TL;DR: In this article, an interval type-3 fuzzy logic system (IT3-FLS) and an online learning approach are designed for power control and battery charge planing for photovoltaic (PV)/battery hybrid systems.
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Data Science in Economics: Comprehensive Review of Advanced Machine Learning and Deep Learning Methods
Saeed Nosratabadi,Amir Mosavi,Puhong Duan,Pedram Ghamisi,Ferdinánd Filip,Shahab S. Band,Uwe Reuter,João Gama,Amir H. Gandomi +8 more
TL;DR: The findings reveal that the trends follow the advancement of hybrid models, which outperform other learning algorithms, and are expected to converge toward the evolution of sophisticated hybrid deep learning models.