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1701
Multipath Branch Model-Aided Differential Evolution Algorithm Based on Regional Error
Published 2024-01-01“…In order to overcome the defect of a single model in the adaptive antenna optimization problem and improving the efficiency and accuracy of the model, a method called multipath branching model-aided differential evolution algorithm analysis (MMDEA-RE) is proposed. …”
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1702
Multi class aerial image classification in UAV networks employing Snake Optimization Algorithm with Deep Learning
Published 2025-07-01“…Furthermore, the integration of Snake Optimization algorithms assists in fine-tuning the classification process, improving accuracy. …”
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1703
Design and Analysis of SSSC-Based Damping Controller: A Novel Modified Zebra Optimization Algorithm Approach
Published 2024-01-01“…The suggested study distinguishes between the mZOA method, traditional ZOA, and conventional PSO algorithms. Based on the simulation findings, it can be inferred that the modified approach that has been suggested is the most effective method for defining the said damping controller by considering the percentage improvement in the objective function value.…”
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1704
Dynamic response force control of electrohydraulic servo actuator of active suspension based on intelligent optimization algorithm.
Published 2025-01-01“…To address these challenges, a fractional-order PID (FOPID) controller optimization method based on the Multi-Strategy Improved Beluga Whale Optimization (MSIBWO) algorithm is proposed. …”
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1705
Research on optimization design method of ship's living compartment layout based on multi-population genetic algorithm
Published 2025-02-01“…It combines emergency evacuation needs to establish a compartment layout optimization model. Additionally, adaptive improvements are made to the genetic operations of the multi-population genetic algorithm, enhancing its applicability to the optimization design of multi-layered ship compartments. …”
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1706
Path planning algorithm for WCE with joint energy replenishment and data collection based on multi-objective optimization
Published 2018-10-01“…Considering limited energy of the wireless charging equipment (WCE) in wireless rechargeable sensor network,an energy replenishment strategy and a data collection strategy are designed.On the basis of these,a path planning model for WCE with functions of joint energy replenishment and data collection based on multi-objective optimization is constructed with two optimization objectives,maximizing the total energy utility of WCE and minimizing the average delay of data transmission of all the sensor nodes in the network.To deal with it,a multi-objective ant colony optimization algorithm based on elitist strategy was proposed,where the state transition strategy and the pheromone updating strategy were improved.Then,the Pareto set was obtained in terms of this multi-objective optimization problem.The parameter setting of ant colony algorithm’s effects on the proposed algorithm were analyzed under 20 sensor nodes.50 groups of contrastive experiments show that the average number of energy utilization obtained by ES-MOAC algorithm is 4.53% higher than that of NSGA-II algorithm.The average number of average delay of all node data transmission obtained by ES-MOAC algorithm is 5.12% lower than that of NSGA-II algorithm.…”
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1707
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1708
Optimizing Solid Rocket Missile Trajectories: A Hybrid Approach Using an Evolutionary Algorithm and Machine Learning
Published 2024-11-01“…This paper introduces a novel approach for modeling and optimizing the trajectory and behavior of small solid rocket missiles. …”
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1709
Research on multi-objective optimization method for bullet full trajectory based on SA-PSO hybrid algorithm
Published 2025-08-01“…The results demonstrate that this approach converges to the optimal solution more efficiently compared to traditional algorithms. …”
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1710
An optimized feature selection using triangle mutation rule and restart strategy in enhanced slime mould algorithm
Published 2025-06-01“…This paper proposes an improved feature selection method based on an improved Slime Mould Algorithm (SMA), called the Triangular Mutation Rule Restart Strategy Slime Mould Algorithm (TRSMA), to overcome some of the shortcomings of the SMA, including premature convergence, poor population diversity, and local optima entrapment. …”
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1711
Optimal Reactive Power Generation for Radial Distribution Systems Using a Highly Effective Proposed Algorithm
Published 2021-01-01“…In this paper, a proposed modified stochastic fractal search algorithm (MSFS) is applied to find the most appropriate site and size of capacitor banks for distribution systems with 33, 69, and 85 buses. …”
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1712
A comparative study of the performance of ten metaheuristic algorithms for parameter estimation of solar photovoltaic models
Published 2025-01-01“…The Friedman test was utilized to rank the performance of the various algorithms, revealing the Growth Optimizer as the top performer across all the considered models. …”
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1713
Applications of Metaheuristic Algorithms in Solar Air Heater Optimization: A Review of Recent Trends and Future Prospects
Published 2021-01-01“…Therefore, this paper clearly shows that the use of all six proposed metaheuristic algorithms results in significant efficiency improvements through the selection of the optimal design set and operating parameters for SAHs. …”
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1714
PCA-FSA-MLR Model and Its Application in Runoff Forecast
Published 2021-01-01“…To improve the accuracy of runoff forecast,and establish a runoff forecast model combining principal component analysis (PCA),future search algorithm (FSA),and multiple linear regression (MLR),this paper reduces the dimensionality of the sample data by PCA,selects 8 standard test functions and simulates and verifies FSA under different dimensional conditions,optimizes MLR constant terms and partial regression coefficients by FSA,proposes a PCA-FSA-MLR runoff forecast model,constructs PCA-LS-MLR,PCA-FSA-SVM,and PCA-SVM models with dimensionality reduction processing by PCA and FSA-MLR,LS-MLR,FSA-SVM,and SVM without dimensionality reduction processing as a comparison model,and verifies each model through forecasting the annual runoff and monthly runoff in December of Longtan station in Yunnan Province.The results show that:①FSA has better optimization accuracy and global extremum search ability under different dimensional conditions;②The average absolute relative error of the annual runoff and monthly runoff in December of Longtan station through PCA-FSA-MLR model are 1.63% and 3.91% respectively,and its forecast accuracy is better than the other 7 models,with higher forecast accuracy and stronger generalization ability;③For the same model,the forecast accuracy after dimensionality reduction processing by PCA is better than that without dimensionality reduction processing,so the data dimensionality reduction by PCA is helpful to improve the forecast accuracy of models.…”
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1715
Enhancing image retrieval through optimal barcode representation
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1716
The Optimal Cost Design of Reinforced Concrete Beams Using an Artificial Neural Network—The Effectiveness of Cost-Optimized Training Data
Published 2025-05-01“…This study presents a method for the automated design of reinforced concrete (RC) beam cross-sections using an artificial neural network (ANN) trained with cost-optimized data generated by the crow search algorithm (CSA). …”
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1717
An optimized informer model design for electric vehicle SOC prediction.
Published 2025-01-01“…Therefore, based on the health assessment algorithm, a new optimized Informer model is proposed to predict SOC. …”
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1718
Machine learning-based coalbed methane well production prediction and fracturing parameter optimization
Published 2025-04-01“…The model employs a random forest algorithm integrated with a multi-task learning strategy and utilizes a particle swarm optimization (PSO) algorithm to optimize fracturing parameters. …”
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1719
An Intelligent 5G Unmanned Aerial Vehicle Path Optimization Algorithm for Offshore Wind Farm Inspection
Published 2025-01-01“…We propose a novel Sea Wind-Aware Improved A*-Guided Genetic Algorithm (SWA-IAGA), which integrates an improved A* algorithm to guide the genetic algorithm for efficient path planning, with the assistance of relevant graphical knowledge. …”
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1720
Volute Optimization Based on Self-Adaption Kriging Surrogate Model
Published 2022-01-01“…Optimizing the volute performance can effectively improve the efficiency of a centrifugal fan by changing the volute geometric parameter, so the self-adaption Kriging surrogate model is used to optimize the volute geometric parameter. …”
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