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101
Genetic Algorithm for Optimal Control Design to Gust Response for Elastic Aircraft
Published 2025-05-01Get full text
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102
Optimized Negative Selection Algorithm for Image Classification in Multimodal Biometric System
Published 2023-04-01“…Hence, this work developed an Optimized Negative Selection Algorithm (ONSA) for image classification in biometric systems. …”
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103
Optimization of the Offshore Wind Turbines Layout Using Cuckoo Search Algorithm
Published 2024-06-01“…After-which a cuckoo search algorithm technique is employed in the wind farm model to optimize the optimization problem (minimizing the wake effect while improving power output and cost). …”
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104
Optimal performance design of bat algorithm: An adaptive multi‐stage structure
Published 2025-06-01“…Abstract The bat algorithm (BA) is a metaheuristic algorithm for global optimisation that simulates the echolocation behaviour of bats with varying pulse rates of emission and loudness, which can be used to find the globally optimal solutions for various optimisation problems. …”
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105
Causal Diagnosability Optimization Design for UAVs Based on Maximum Mean Covariance Difference and the Gray Wolf Optimization Algorithm
Published 2025-05-01“…Finally, a diagnosability optimization technique utilizing the GWO algorithm is proposed. …”
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106
Investigation of a Multi-Strategy Ensemble Social Group Optimization Algorithm for the Optimization of Energy Management in Electric Vehicles
Published 2022-01-01“…A multi-strategy ensemble social group optimization algorithm (ME-SGO) to improve the exploration for complex and composite landscapes through distance-based strategy adaption and success-based parameter adaption while incorporating linear population reduction is proposed. …”
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107
Scheduling optimization based on particle swarm optimization algorithm in emergency management of long-distance natural gas pipelines.
Published 2025-01-01“…The experimental results show that compared with the traditional particle swarm optimization algorithm, NACFPSO performs well in both convergence speed and scheduling time, with an average convergence speed of 81.17 iterations and an average scheduling time of 200.00 minutes; while the average convergence speed of the particle swarm optimization algorithm is 82.17 iterations and an average scheduling time of 207.49 minutes. …”
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108
An Improved Particle Swarm Optimization Algorithm forOptimal Allocation of Distributed Generation Units in Radial Power Systems
Published 2020-01-01“…The minimum value of fitness losses using the applied algorithm is found to be 0.0.0406 while the average elapsed time is 62.2325 s. …”
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109
Optimal adaptive heuristic algorithm based energy optimization with flexible loads using demand response in smart grid.
Published 2024-01-01“…MATLAB is used to do a load scheduling simulation for home appliances based on the OAWDO algorithm. By contrasting it with other algorithms, including the genetic algorithm (GA), the whale optimization algorithm (WOA), the fire-fly optimization algorithm (FFOA), and the wind-driven optimization (WDO) algorithms, the effectiveness of the OAWDO technique is supported. …”
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110
RUL Prediction of Rolling Bearings Based on Fruit Fly Optimization Algorithm Optimized CNN-LSTM Neural Network
Published 2025-02-01“…In addition, introducing FOA enables the model to dynamically adjust the hidden layers and thresholds while optimizing the optimal path, thereby finding the best solution. …”
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111
Optimized conductor selection and phase balancing in unbalanced distribution networks: Economic optimization via the vortex search algorithm
Published 2025-09-01“…This methodology is compared against the hurricane optimization algorithm, the sine cosine algorithm, and the salp swarm optimization algorithm. …”
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112
Optimizing energy constrained target localization and tracking with radial bias and seeker optimization algorithms in wireless sensor networks
Published 2025-06-01“…This paper proposes a novel approach combining Radial Bias (RB) with the Seeker Optimization Algorithm (SOA) to address the challenges of energy-constrained target localization and tracking. …”
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113
Rethinking Metaheuristics: Unveiling the Myth of “Novelty” in Metaheuristic Algorithms
Published 2025-07-01“…While nature-inspired optimization methods show promise for various applications, their effectiveness is often limited by metaphor-driven design, structural biases, and a lack of sufficient theoretical foundation. …”
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114
A novel robust multi-objective evolutionary optimization algorithm based on surviving rate
Published 2025-02-01“…Despite the success of multi-objective evolutionary optimization algorithms in addressing complex optimization problems, research focusing on input disturbances remains limited. …”
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115
Colonial bacterial memetic algorithm and its application on a darts playing robot
Published 2025-03-01“…Abstract In this paper, we present the Colonial Bacterial Memetic Algorithm (CBMA), an advanced evolutionary optimization approach for robotic applications. …”
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116
Microservice combination optimisation based on improved gray wolf algorithm
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117
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A New Hybrid Grasshopper Optimization - Backpropagation for Feedforward Neural Network Training
Published 2023-02-01“… The Grasshopper optimization algorithm showed a rapid converge in the initial phases of the global search, however while being around the global optimum, the searching process became so slow. …”
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119
Bayesian optimization with Optuna for enhanced soil nutrient prediction: a comparative study with genetic algorithm and particle swarm optimization
Published 2025-12-01“…In addition, it examines 2,000 random surface soil samples, ranging from 0 to 20 cm, that were optimized using genetic algorithms (GA), particle swarm optimization (PSO), and Optuna. …”
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120
Space Trajectory Planning with a General Reinforcement-Learning Algorithm
Published 2025-04-01“…The proposed framework integrates Monte Carlo Tree Search with a neural network to efficiently explore and optimize space trajectories. While developed for space trajectory planning, the algorithm is broadly applicable to any problem involving hybrid action spaces. …”
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