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161
Multiobjective Optimization of Irreversible Thermal Engine Using Mutable Smart Bee Algorithm
Published 2012-01-01“…The results have been checked with some of the most common optimizing algorithms like Karaboga’s original artificial bee colony, bees algorithm (BA), improved particle swarm optimization (IPSO), Lukasik firefly algorithm (LFFA), and self-adaptive penalty function genetic algorithm (SAPF-GA). …”
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162
Research on kd-tree Cache Optimization Based on Particle Index Sorting Algorithm
Published 2024-01-01“…Consequently, the cache access pattern is optimized, leading to fewer cache misses and improved search times. …”
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163
Multiobjective Optimization Method for Polymer Injection Molding Based on a Genetic Algorithm
Published 2019-01-01“…A mathematical model considering an objective and impact factors is developed using the response surface method. The optimal combination of the impact parameters is determined using a multiobjective genetic algorithm. …”
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164
Optimization of Communication Quality for Energy-Limited Inspection AAV: A Hybrid Algorithm
Published 2024-01-01“…Numerical results show that the proposed algorithm is effective in optimizing the communication quality of the inspection AAV with limited energy, and its performance is improved by about 15%-50% compared with other benchmarks.…”
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165
Exploring Evolutionary Algorithms for Optimal Power Flow: A Comprehensive Review and Analysis
Published 2024-10-01“…It has been more than five decades since optimum power flow (OPF) emerged as one of the most famous and frequently used nonlinear optimization problems in power systems. …”
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166
Reducing hydrogen consumption in hybrid electric vehicles using aquila optimization algorithm
Published 2025-04-01“…The aquila optimization algorithm is one of the most recent and efficient algorithms. …”
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167
Prediction and optimization of robot processing technology based on neural network and genetic algorithm
Published 2025-04-01“…Finally, the genetic algorithm was applied to optimize grinding process parameters with material removal rates as the indicator.ResultsThe grinding process parameters have significant effects on grinding forces, but the order of major and secondary effects of different parameters varies with grinding force components. …”
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168
An Enhanced PSO-Based Clustering Energy Optimization Algorithm for Wireless Sensor Network
Published 2016-01-01“…Maximizing the lifetime of the Wireless Sensor networks, energy conservation measures are essential for improving the performance of WSNs. This paper proposes an Enhanced PSO-Based Clustering Energy Optimization (EPSO-CEO) algorithm for Wireless Sensor Network in which clustering and clustering head selection are done by using Particle Swarm Optimization (PSO) algorithm with respect to minimizing the power consumption in WSN. …”
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169
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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170
Optimizing concrete strength: How nanomaterials and AI redefine mix design
Published 2025-07-01“…XGB was identified as the most effective ML algorithm for predicting compressive strength among others in this study (R2=0.974). …”
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171
An Improved Particle Swarm Optimization for Solving Bilevel Multiobjective Programming Problem
Published 2012-01-01“…An improved particle swarm optimization (PSO) algorithm is proposed for solving bilevel multiobjective programming problem (BLMPP). …”
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172
An Improved LEACH Protocol for Optimizing Cluster Head Selection and In-cluster Selection
Published 2024-10-01“…This protocol initially employs the root mean square (RMS) of distance within the energy consumption model to determine the optimal number of cluster heads. …”
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173
Daily runoff forecasting using novel optimized machine learning methods
Published 2024-12-01“…This study addresses these challenges by introducing a novel bio-inspired metaheuristic algorithm, Artificial Rabbits Optimization (ARO), integrated with various machine learning (ML) models for runoff forecasting in the Carson and Chehalis River basins. …”
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174
Healthcare Prediction Using Novel Machine Learning Methods and Metaheuristic Algorithm
Published 2025-06-01“…Four models ETSA, ETCH, SVSA, and SVCH were developed in this study by integrating the ETC and SVC models with two optimization algorithms the CHS and SAO. Upon analyzing the performance of these models, it was found that the ETSA model had a high precision of 0.806 in normal conditions.…”
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175
Improved Butterfly Optimizer-Configured Extreme Learning Machine for Fault Diagnosis
Published 2021-01-01“…The model is mainly based on an improved butterfly optimizer algorithm- (BOA-) optimized kernel extreme learning machine (KELM) model. …”
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176
Innovative Hybrid Algorithm for Solving Vehicle Routing Problem with Time Window
Published 2025-03-01“…Hybrid approaches combine multiple optimization techniques to improve the quality and efficiency of solutions. …”
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177
Development of an Improved KOA Algorithm for Solving Task Allocation in Hilly Orchards With Weeding Robots
Published 2025-01-01Get full text
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178
Improving the Solving of Optimization Problems: A Comprehensive Review of Quantum Approaches
Published 2025-01-01Get full text
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179
Optimizing Bi-LSTM networks for improved lung cancer detection accuracy.
Published 2025-01-01“…We employed traditional hand-crafted features, such as Gray Level Co-occurrence Matrix (GLCM) features, in conjunction with traditional machine learning algorithms. To explore the potential of deep learning, we also optimized and implemented a Bidirectional Long Short-Term Memory (Bi-LSTM) network for lung cancer detection. …”
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180
Combining 3-Opt and Improved Discrete Cuckoo Search Algorithm for the Traveling Salesman Problem
Published 2024-01-01“…For 500 iterations, the average best solution of the proposed method differed from the average optimal solution by 0.07%. In the results of the improved discrete cuckoo search algorithm (CSA), this rate was calculated to be 0.08%. …”
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