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281
Optimization of distribution networks using quantum annealing for loss reduction and voltage improvement in electrical vehicle parking management
Published 2025-09-01“…Traditional optimization techniques like Genetic Algorithms (GA) and Particle Swarm Optimization (PSO) often struggle with the nonlinear, high-dimensional nature of EV-grid interaction problems. …”
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282
Applying Genetic Algorithm for test pattern generation process optimization
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283
Ship’s Trajectory Planning Based on Improved Multiobjective Algorithm for Collision Avoidance
Published 2019-01-01“…In this paper, the optimization of ship collision avoidance strategies is realized by both an improved multiobjective optimization algorithm NSGA-II and the ship domain under the condition of a wide sea area without any external disturbances. …”
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284
Design of improved JAYA algorithm for cigarette finished product logistics delivery
Published 2025-12-01“…In response to these challenges, this study proposes an improved Jaya algorithm that integrates a reverse learning mechanism and a cosine similarity strategy to enhance optimization performance. …”
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285
A binary grasshopper optimization algorithm for solving uncapacitated facility location problem
Published 2025-05-01“…The Uncapacitated Facility Location Problem (UFLP) is a real-world binary optimization problem that aims to find the number of facilities to open, minimizing the total cost of exchange between customers and facilities, as well as the opening costs of these facilities. …”
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286
Improved grey wolf optimizer for optimal reactive power dispatch with integration of wind and solar energy
Published 2025-01-01“…The aim of this paper is to present a new improved grey wolf optimizer (IGWO) to solve the optimal reactive power dispatch (ORPD) problem with and without penetration of renewable energy resources (RERs). …”
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287
Path Planning of Quadrupedal Robot Based on Improved RRT-Connect Algorithm
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288
An Improved Hybrid Genetic Algorithm with a New Local Search Procedure
Published 2013-01-01“…One important challenge of a hybrid genetic algorithm (HGA) (also called memetic algorithm) is the tradeoff between global and local searching (LS) as it is the case that the cost of an LS can be rather high. …”
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289
An intelligent comprehensive scoring approach based on improved differential evolution algorithm
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290
An intelligent comprehensive scoring approach based on improved differential evolution algorithm
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291
Insulator Defect Detection Algorithm Based on Improved YOLOv11n
Published 2025-02-01Get full text
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292
Availability and uncertainty-aware optimal placement of capacitors and DSTATCOM in distribution network using improved exponential distribution optimizer
Published 2025-04-01“…The decision variables include the installation location and the capacity of compensators, which are defined by a novel meta-heuristic algorithm termed the improved exponential distribution optimizer (IEDO). …”
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293
Research of a spam filter based on improved naive Bayes algorithm
Published 2017-03-01“…In spam filtering filed,naive Bayes algorithm is one of the most popular algorithm,a modified using support vector machine(SVM)of the native Bayes algorithm :SVM-NB was proposed.Firstly,SVM constructs an optimal separating hyperplane for training set in the sample space at the junction two types of collection,Secondly,according to its similarities and differences between the neighboring class mark for each sample to reduce the sample space also increase the independence of classes of each samples.Finally,using naive Bayesian classification algorithm for mails.The simulation results show that the algorithm reduces the sample space complexity,get the optimal classification feature subset fast,improve the classification speed and accuracy of spam filtering effectively.…”
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294
Optimal geometrical selection of skin mesh: experimental analysis and numerical optimization
Published 2025-07-01“…Hyperelastic properties of healthy and meshed skin were obtained through uniaxial tensile tests, and different geometries were analyzed using Abaqus. The optimal mesh geometry was then determined using genetic algorithms in Abaqus and MATLAB. …”
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295
AC Optimal Power Flow Problem Considering Wind Energy by an Improved Particle Swarm Optimization
Published 2024-02-01“…To solve the AC-OPF model, an Improved Particle Swarm Optimization (IPSO) is presented. …”
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296
An Improved Spectral Clustering Community Detection Algorithm Based on Probability Matrix
Published 2020-01-01“…The similarity graphs of most spectral clustering algorithms carry lots of wrong community information. …”
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297
YOLOGX: an improved forest fire detection algorithm based on YOLOv8
Published 2025-01-01“…Finally, the proposed Focal-SIoU loss function replaces the original loss function, effectively reducing directional errors by combining angle, distance, shape, and IoU losses, thus optimizing the model training process. YOLOGX was evaluated on the D-Fire dataset, achieving a mAP@0.5 of 80.92% and a detection speed of 115 FPS, surpassing most existing classical detection algorithms and specialized fire detection models. …”
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298
IGWO-MSVR model for predicting stress in coal seam during drilling process
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299
Operation Optimization Strategy of Commercial Combined Electric Heating System Based on Particle Swarm Optimization Algorithm
Published 2023-02-01“… In order to improve the energy efficiency of the electric heating system, a particle swarm optimization (PSO, Particle Swarm Optimization)-based operation optimization strategy for the direct storage combined electric heating system is proposed.A mathematical model of influencing factors inside and outside the walls of electric heating buildings is established, and the simulink toolbox in matlab is used to build the overall system under the premise of determining the quantity of electric heating.Combining demand response ideas, the objective function is to establish the minimum heating and electricity cost of the user, and different sub-modules are selected to form the control module to achieve simulation verification, and the inverse cosine method is used to update the improved particle swarm algorithm to update the learning factor to solve the set objective function.Finally, through a calculation example of electricity consumption data of an enterprise in Jinan, Shandong, comparing energy consumption and economy can be obtained: the total energy consumption throughout the day is lower than the actual energy consumption, and the electricity bill is reduced by 17.16% compared with the unoptimized time.…”
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300