S
Sinan Q. Salih
Researcher at Duy Tan University
Publications - 67
Citations - 2292
Sinan Q. Salih is an academic researcher from Duy Tan University. The author has contributed to research in topics: Computer science & Artificial neural network. The author has an hindex of 22, co-authored 55 publications receiving 1130 citations. Previous affiliations of Sinan Q. Salih include Information Technology University & Universiti Malaysia Pahang.
Papers
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Development of multivariate adaptive regression spline integrated with differential evolution model for streamflow simulation
TL;DR: This research presents the implementation of a novel hybrid model called Multivariate Adaptive Regression Spline integrated with Differential Evolution (MARS-DE) to forecast streamflow pattern in semi-arid region and exhibited an excellent hybrid predictive modeling capability.
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Deep Learning Data-Intelligence Model Based on Adjusted Forecasting Window Scale: Application in Daily Streamflow Simulation
TL;DR: Experimental data show that not only does the developed LSTM model have obvious advantages in processing steady streamflow data in the dry season but it also shows good ability to capture data features in the rapidly fluctuant streamflowData in the rainy season.
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Thin and sharp edges bodies-fluid interaction simulation using cut-cell immersed boundary method
Sinan Q. Salih,Mohammed Suleman Aldlemy,Mohammad Rasidi Mohammad Rasani,Ahmad Kamal Ariffin,T.M.Y.S. Tuan Ya,Nadhir Al-Ansari,Zaher Mundher Yaseen,Kwok Wing Chau +7 more
TL;DR: The new developed AMR-IBM algorithm is validated using a benchmark data of fluid past a cylinder and the results show that there is good agreement under laminar flow, confirming the robustness of the new algorithms in simulating flow characteristics in the boundary layers of thin structures.
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Modeling monthly pan evaporation process over the Indian central Himalayas: application of multiple learning artificial intelligence model
Anurag Malik,Anil Kumar,Sungwon Kim,Mahsa H. Kashani,Vahid Karimi,Ahmad Sharafati,Mohammad Ali Ghorbani,Nadhir Al-Ansari,Sinan Q. Salih,Zaher Mundher Yaseen,Kwok-Wing Chau +10 more
TL;DR: The results showed that the proposed MM-ANN-1 and MGGP-1 models were more successful than the other techniques during testing period to simulate the monthly pan evaporation at both Ranichauri and Pantnagar stations, and will help to the local stakeholders in terms of water resources management.
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A new algorithm for normal and large-scale optimization problems: Nomadic People Optimizer
TL;DR: A novel swarm-based metaheuristic algorithm which depends on the behavior of nomadic people was developed and demonstrated the potential high convergence, lower iterations, and less time-consuming required for finding the current best solution for the NPO algorithm.