H
Hojat Karami
Researcher at Semnan University
Publications - 109
Citations - 2040
Hojat Karami is an academic researcher from Semnan University. The author has contributed to research in topics: Evolutionary algorithm & Particle swarm optimization. The author has an hindex of 20, co-authored 98 publications receiving 1171 citations. Previous affiliations of Hojat Karami include Amirkabir University of Technology.
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Flow Direction Algorithm (FDA): A Novel Optimization Approach for Solving Optimization Problems
TL;DR: A new optimization algorithm named Flow Direction Algorithm (FDA), which is a physics-based algorithm that mimics the flow direction to the outlet point with the lowest height in a drainage basin, demonstrates the superior performance of the FDA in solving challenging problems.
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Reservoir operation based on evolutionary algorithms and multi-criteria decision-making under climate change and uncertainty
Mohammad Ehteram,Sayed-Farhad Mousavi,Hojat Karami,Saeed Farzin,Vijay P. Singh,Kwok Wing Chau,Ahmed El-Shafie +6 more
TL;DR: In this article, the authors investigated reservoir operation under climate change for a base period (1981-2000) and future period (2011-2030) and different climate change models, based on A2 scenario, were used and the HAD-CM3 model was found to be the best model.
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Optimizing dam and reservoirs operation based model utilizing shark algorithm approach
TL;DR: Investigation of the potential of shark algorithm is examined as an optimization algorithm for reservoir operation and showed that the proposed shark algorithm outperformed the other algorithms and achieved higher reliability index and lesser vulnerability index.
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Prediction of Water Quality Parameters Using ANFIS Optimized by Intelligence Algorithms (Case Study: Gorganrood River)
TL;DR: In this paper, the performance of adaptive neuro-fuzzy inference system (ANFIS) for evaluating the quality parameters of Gorganroud River water, such as Electrical Conductivity (EC), Sodium Absorption Ratio (SAR), and Total Hardness (TH), was investigated.
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Hybrid ANFIS-PSO approach for predicting optimum parameters of a protective spur dike
Hossein Basser,Hojat Karami,Shahaboddin Shamshirband,Shatirah Akib,Mohsen Amirmojahedi,Rodina Ahmad,Afshin Jahangirzadeh,Hossein Javidnia +7 more
TL;DR: A novel hybrid approach was developed, combining adaptive-network-based fuzzy inference system and particle swarm optimization (ANFIS-PSO) to predict protective spur dike's parameters in order to control scouring around a series of spur dikes.