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Opposition-based learning simulated kalman filter for Numerical optimization problems
Published 2016“…Using CEC2014 benchmark suite, it is found that the SKF with opposition-based learning outperforms the original SKF algorithm in most cases. …”
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A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution
Published 2018“…Simulation results reveal the proposed algorithm’s ability to produce real and well-distributed Pareto optimum fronts for all considered multi-objective optimization cases. …”
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A Hybrid of Ant Colony Optimization Algorithm and Simulated Annealing for Classification Rules
Published 2013“…In the first proposed algorithm, SA is used to optimize the rule's discovery activity by an ant. …”
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On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing
Published 2015“…Specifically, these algorithms require extensive tuning before optimal solution can be obtained. …”
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Opposition- based simulated kalman filters and their application in system identification
Published 2017“…Among the various kinds of optimization algorithms, Simulated Kalman Filter (SKF) is a new population-based optimization algorithm inspired by the estimation capability of Kalman Filter. …”
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7
Enhancing generality of meta-heuristic algorithms through adaptive selection and hybridization
Published 2018“…Many meta-heuristic algorithms have been developed to date (e.g. Simulated Annealing (SA), Particle Swarm Optimization (PSO), Teaching Learning based Optimization (TLBO), Grey Wolf Optimizer(GWO) to name a few). …”
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Distributed learning based energy-efficient operations in small cell networks
Published 2023“…Collaboration and autonomous operation among network devices are imperative in addressing these use cases. Several solutions proposed in the literature are limited to addressing the cooperation problem and resource management issues. …”
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A new machine learning-based hybrid intrusion detection system and intelligent routing algorithm for MPLS network
Published 2023“…Machine Learning (ML) is seen as a promising application that offers autonomous learning and provides optimized solutions to complex problems. …”
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Opposition-Based Quantum Bat Algorithm to Eliminate Lower-Order Harmonics of Multilevel Inverters
Published 2021“…The results are verified using both simulation and experimental studies. The results showed substantial improvement and superiority compared to other available algorithms both in terms of the harmonics reduction of harmonics and finding the correct solutions. …”
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Opposition-Based Quantum Bat Algorithm to Eliminate Lower-Order Harmonics of Multilevel Inverters
Published 2021“…The results are verified using both simulation and experimental studies. The results showed substantial improvement and superiority compared to other available algorithms both in terms of the harmonics reduction of harmonics and finding the correct solutions. …”
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12
Parallel CFD Simulations of Multiphase Systems: Jet into a Cylindrical Bath and Rotary Drum on a Rectangular Bath.
Published 2001“…For commercial CFD packages, in many cases the solution algorithms are black boxes, even though parallel computing helps in many cases to overcome the limitations, as shown here. …”
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Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks
Published 2025thesis::doctoral thesis -
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Development of optimized damage prediction method for health monitoring of ultra high performance fiber-reinforced concrete communication tower
Published 2018“…The modal frequencies of the tower are evaluated under various conditions of damage in concrete and connection in different parts of the tower by using finite element simulation. The results are used to develop the hybrid learning algorithm based on the AdaBoost, Bagging, and RUSBoost methods to predict the damage in the tower based on dynamic frequency domain. …”
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15
Nature-Inspired cognitive evolution to play Ms. Pac-Man
Published 2011“…The focus of this research is to explore the hybridization of nature-inspired computation methods for optimization of neural network-based cognition in video games, in this case the combination of a neural network with an evolutionary algorithm. …”
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Industrial datasets with ICS testbed and attack detection using machine learning techniques
Published 2021“…The deep learning (DL) techniques has been used recently for enhanced OT intrusion detection performances.…”
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Investigating the Performance of Deep Reinforcement Learning-Based MPPT Algorithm under Partial Shading Condition
Published 2024“…These DRL-based algorithms optimize the local and global maximum power point (MPP) using deep Q-learning and deep deterministic policy gradient (DDPG). …”
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Deriving Optimal Operation Rule for Reservoir System Using Enhanced Optimization Algorithms
Published 2025Subjects:Article -
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Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof
Published 2019“…From the simulation result, by using these sensors information the AUTOWiSARD algorithm can successfully differentiate and classify states without supervision, while the Q-learning algorithm is able to produce and optimized states-actions policy. …”
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Enhancing simulated kalman filter algorithm using current optimum opposition-based learning
Published 2019“…Simulated Kalman filter (SKF) is a new population-based optimization algorithm inspired by estimation capability of Kalman filter. …”
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