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Energy-efficient routing using novel optimization with Tabu techniques for Wireless Sensor Network
Published 2022“…Sensor node clustering is a popular approach for WSN. …”
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New global maximum power point tracking and modular voltage equalizer topology for partially shaded photovoltaic system / Immad Shams
Published 2022“…In terms of controller-based, in this work, a new global maximum power point tracking (GMPPT) algorithm based on a modified butterfly optimization algorithm (MBOA) has been proposed. …”
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Green anaconda optimization based energy aware clustering protocol for 6G wireless communication systems
Published 2023“…The selection of proper CHs using metaheuristic algorithms fnds useful in design of energy-efcient WSNs. …”
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A contactless computer vision system for underwater walking and jogging gait analysis using YOLO-pose and Multi-CNN BiLSTM architecture
Published 2025“…A comparison of hyperparameter optimization algorithms was conducted, with the combination of multivariate tree-structured Parzen estimators (MultiTPE) and Hyperband identified as the optimal approach. …”
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Modeling and optimization of cold extrusion process by using response surface methodology and metaheuristic approaches
Published 2018“…Subsequently, the analytical approach and metaheuristic algorithms, specifically the particle swarm optimization, cuckoo search algorithm (CSA) and flower pollination algorithm, were applied to optimize the extrusion process parameters. …”
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Modelling of optimal placement and sizing of battery energy storage system using hybrid whale optimization algorithm and artificial immune system for total system losses reduct...
Published 2023“…Besides, an optimization algorithm with high efficiency is important to ensure the attainment of optimal solutions, where the optimization algorithms like genetic algorithm and particle swarm optimization are known to have high possibility of being trapped in local optimal points. …”
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A centralized localization algorithm for prolonging the lifetime of wireless sensor networks using particle swarm optimization in the existence of obstacles
Published 2017“…Particle Swarm Optimization has been used in the proposed algorithm to minimize the fitness function. …”
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Sediment load forecasting from a biomimetic optimization perspective: Firefly and Artificial Bee Colony algorithms empowered neural network modeling in �oruh River
Published 2025“…The hybrid model is a novel approach for estimating sediment load based on various input variables. …”
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Optimal under voltage load shedding based on stability index by using artificial neural network
Published 2020“…Nevertheless, to obtain the lowest amount to be shed in order to avoid voltage instability, optimization is required. An algorithm was developed to shed the optimal load by considering the load priority whereby the load with least priority will be shed first. …”
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Hybrid ant colony optimization algorithm for container loading problem
Published 2012“…This approach is called, the Hybrid Ant Colony Optimization with Tower Building Heuristic (HACO). …”
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The Determination of Pile Capacity Using Artificial Neural-net: An Optimization Approach
Published 2001“…From standard static formula for bearing capacity of a single pile foundation, an algorithm using a reliability approach for the determination of service load was developed. …”
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Optimization of neural network architecture using genetic algorithm for load forecasting
Published 2014“…In this paper, a computational intelligent technique genetic algorithm (GA) is implemented for the optimization of artificial neural network (ANN) architecture. …”
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An optimal load shedding approach for transmission networks using Particle Swarm Optimization (PSO) technique / Mohd Farid Mohd Rawi
Published 2009“…This thesis presents an optimal load shedding approach for transmission networks using Particle Swarm Optimization (PSO). …”
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Simulated Kalman Filter optimization algorithm for maximization of wireless sensor networks coverage
Published 2019“…It had been successfully used for optimization of many engineering problems. …”
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Node placement optimization using extended virtual force and cuckoo search algorithm in wireless sensor network
Published 2014“…This study proposed Extended Virtual Force and Cuckoo Search (EVFCS) algorithm with a combination of EVFA and CS algorithm to find an optimal node placement. …”
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Optimising cloud computing performance with an enhanced dynamic load balancing algorithm for superior task allocation
Published 2024“…Furthermore, the EDLB algorithm enhances load balancing by 46.46%. These results highlight the effectiveness of the EDLB algorithm in addressing critical load balancing issues and surpassing existing methods. …”
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Cluster head selection optimization in wireless sensor network via genetic-based evolutionary algorithm
Published 2020“…Genetic-based evolutionary algorithms such as Genetic Algorithm (GA) and Differential Evolution (DE) have been popularly used to optimize cluster head selection in WSN to improve energy efficiency for the extension of network lifetime. …”
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Voltage Regulation Planning Based on Optimal Grid-Connected Renewable Energy Allocation Using Nature-Inspired Algorithms to Reduce Switching Cycles of On-Load Tap Changing Transfor...
Published 2023“…The framework has been applied to the IEEE 57-bus and 118-bus systems with different load levels. The performance of the proposed approach has been benchmarked by comparing it with the genetic optimization algorithm to identify the higher potential buses for renewable generation allocation. …”
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Global optimization method for continuous - Time sensor scheduling
Published 2010“…We consider a situation in which several sensors are used to collect data for signal processing since operating multiple sensors simultaneously canses system interference, only one sensor can be active at any one time.The problem of scheduling a discrete-valued optimal control problem.This problem cannot be solved using conventional optimization problem.The Transformed problem is then decomposed into a bi-level optimization problem, which is solved using a discreate filled function method in conjunction with a conventional optimal control algorithm.Numerical results show that our algorithm is robust, efficient, and reliable in attaining a near globally optimal solution.…”
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