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Optimizing Decentralized Exam Timetabling with a Discrete Whale Optimization Algorithm
Published 2025“…In recent years, there has been increasing interest in intelligent optimization algorithms, such as the Whale Optimization Algorithm (WOA). …”
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Optimizing decentralized exam timetabling with a discrete whale optimization algorithm
Published 2025“…—In recent years, there has been increasing interest in intelligent optimization algorithms, such as the Whale Optimization Algorithm (WOA). …”
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A discrete simulated kalman filter optimizer for combinatorial optimization problems
Published 2022“…An example of a numerical algorithm is the simulated Kalman filter (SKF). Various method has been introduced as an extension of a numerical algorithm to adapt it to a discrete search space. …”
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Developing a hybrid model for accurate short-term water demand prediction under extreme weather conditions: a case study in Melbourne, Australia
Published 2024“…Hybrid model development included the optimization of ANN coefficients (its weights and biases) using adaptive guided differential evolution algorithm. …”
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Enhanced utility accrual scheduling algorithms for adaptive real time system.
Published 2009“…Problem statement: This study proposed two utility accrual real time scheduling algorithms named as Preemptive Utility Accrual Scheduling (PUAS) and Non-preemptive Utility Accrual Scheduling (NUAS) algorithms. …”
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Acltshe-Amts: A New Adaptive Brain Tumour Enhancement And Segmentation Approaches
Published 2024“…The ACLTSHE integrates Contrast-Limited Adaptive Histogram Equalization, Multi-Objective Whale Optimization Algorithm, Discrete Entropy (DE), Peak Signal-to-Noise Ratio (PSNR), and Structure Similarity Index (SSI) to improve the quality of MR images while preserving the original structure of the MR images. …”
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Taguchi's T-method with nearest integer-based binary bat algorithm for prediction
Published 2023Article -
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Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…In this research, two novel estimation-based metaheuristic optimization algorithms, named as Simulated Kalman Filter (SKF), and single-solution Simulated Kalman Filter (ssSKF) algorithms are introduced for global optimization problems. …”
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A hybrid Q-learning sine-cosine-based strategy for addressing the combinatorial test suite minimization problem
Published 2018“…The sine-cosine algorithm (SCA) is a new population-based meta-heuristic algorithm. …”
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Variable Neighborhood Descent and Whale Optimization Algorithm for Examination Timetabling Problems at Universiti Malaysia Sarawak
Published 2025“…A constructive algorithm was developed to generate an initial feasible solution, which was subsequently refined using two primary approaches to evaluate their efficiency: Iterative Threshold Pipe Variable Neighborhood Descent (IT-PVND), and a modified Whale Optimization Algorithm (WOA). …”
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Machine-learning-based adaptive distance protection relay to eliminate zone-3 protection under-reach problem on statcom-compensated transmission lines
Published 2020“…These parameters are used to develop a standalone intelligently machine learning adaptive distance relay (ML-ADR) modification. The intelligent algorithm ML-ADR fault classifier model could discriminate 10 different far-end short circuit fault types from two network topology changes with and without midpoint integrated STATCOM on the Matlab/Simulink power grid system model. …”
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Mobile data gathering algorithms for wireless sensor networks
Published 2014“…The third proposed algorithm achieves an adaptive data gathering strategy. …”
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Two level aggregation scheme with optimization in subframes headers for IEEE 802.11n wireless networks
Published 2014“…Furthermore, a new two-level aggregation model is developed by integrating the eA-MSDU into A-MPDU and designing suitable operating algorithm. …”
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Wavelet based fault tolerant control of induction motor / Khalaf Salloum Gaeid
Published 2012“…The motor features are extracted through the proposed Discrete Wavelet Transform (DWT) based analysis method, while the wavelet inlet acts as an expert tool to adapt the right controller in accordance with the fault type. …”
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