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model optimization » level optimization (Expand Search), motor optimization (Expand Search), monkey optimizations (Expand Search)
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1
Using genetic algorithms to optimize software quality estimation models
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Cuckoo search for portfolio optimization. (c2014)
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Metaheuristic Algorithm for State-Based Software Testing
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An Improved Genghis Khan Optimizer based on Enhanced Solution Quality Strategy for Global Optimization and Feature Selection Problems
Published 2024“…Therefore, this process can be seen as an optimization process. The primary goals of feature selection are to decrease the number of dimensions and enhance classification accuracy in many domains, such as text classification, large-scale data analysis, and pattern recognition. …”
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Comparative analysis of metaheuristic load balancing algorithms for efficient load balancing in cloud computing
Published 2023“…This paper provides a comparative analysis of various metaheuristic load balancing algorithms for cloud computing based on performance factors i.e., Makespan time, degree of imbalance, response time, data center processing time, flow time, and resource utilization. …”
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A cluster-based model for QoS-OLSR protocol
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On Higher-Order Iterative Learning Control Algorithm in Presence of Measurement Noise
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Opportunistic Throughput Optimization in Energy Harvesting Dynamic Spectrum Sharing Wireless Networks
Published 2024“…Furthermore, we propose two algorithms designed to achieve optimal throughput for each scenario. …”
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Minimizing using BBO and DFO methods
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Optimization metaheuristic for software testing
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Optimal supercharge scheduling of electric vehicles
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Eye-Clustering: An Enhanced Centroids Prediction for K-means Algorithm
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Correlation Clustering via s-Club Cluster Edge Deletion
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Scatter search for homology modeling
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A new minimum curvator multi-step method for unconstrained optimization
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Protein structure prediction in the 3D HP model
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Meta Reinforcement Learning for UAV-Assisted Energy Harvesting IoT Devices in Disaster-Affected Areas
Published 2024“…We conducted extensive simulations and compared our approach with two state-of-the-art models using traditional RL algorithms represented by a deep Q-network algorithm, a Particle Swarm Optimization (PSO) algorithm, and one greedy solution. …”
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Intelligent route to design efficient CO<sub>2</sub> reduction electrocatalysts using ANFIS optimized by GA and PSO
Published 2022“…The primary purpose of this study is to establish a new model through machine learning methods; namely, adaptive neuro-fuzzy inference system (ANFIS) combined with particle swarm optimization (PSO) and genetic algorithm (GA) for the prediction of *CO (the key intermediate) adsorption energy as the efficiency metric. …”