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HEALTH CLAIM INSURANCE PREDICTION USING SUPPORT VECTOR MACHINE WITH PARTICLE SWARM OPTIMIZATION
Published 2023-06-01“…Parameter selection of SVM is normally done by trial and error so that the performance is less than optimal. Some optimization algorithms based heuristic optimization can be used to determine the best parameter values of SVM, for example Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). …”
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322
Enhanced particle swarm optimization for feature selection in SVM-based Alzheimer’s disease diagnosis
Published 2025-07-01“…In this paper, an enhanced Particle Swarm Optimization (PSO) algorithm, which integrates opposition-based Latin squares sampling initialization (OL) with dynamic inertia weights and learning factors (D), termed OLDPSO, is proposed to improve feature selection and classification within a Support Vector Machine (SVM) model for AD diagnosis using magnetic resonance imaging (MRI) data. …”
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323
ClipQ: Clipping Optimization for the Post-Training Quantization of Convolutional Neural Network
Published 2025-04-01“…Channel information entropy and principal component analysis are used to characterize the channel attention and spatial attention of activations, respectively. In addition, the particle swarm algorithm is applied in weight clipping to adjust the search step size and direction adaptively. …”
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324
A Solution Quality Assessment Method for Swarm Intelligence Optimization Algorithms
Published 2014-01-01“…To validate the proposed method, some intelligent algorithms such as ant colony optimization (ACO), particle swarm optimization (PSO), and artificial fish swarm algorithm (AFS) were taken to solve traveling salesman problem. …”
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325
Chameleon swarm algorithm with Morlet wavelet mutation for superior optimization performance
Published 2025-04-01“…Five performance metrics—average energy consumption, total energy consumption, total residual energy, dead node and cluster head frequency are taken into consideration when evaluating the performances against state-of-the-art algorithms. For nine different simulation scenarios, the proposed algorithm mCSAMWL outperforms the Atom Search Optimization (ASO), Hybrid Particle Swarm Optimization and Grey Wolf Optimization (PSO-GWO), Bald Eagle Search Algorithm (BES), the African Vulture Optimization Algorithm (AVOA), and the Chameleon Swarm Algorithm (CSA) in terms of average energy consumption and total energy consumption by 50.9%, 52.6%, 45%, 42.4%, 50.1% and 51.4%, 53.3%, 45.6%, 42.4%, 50.7%.…”
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326
Systematic Review: Particle Swarm Optimization (PSO) based Load Balancing for Cloud Computing
Published 2024-06-01“…The objective of this systematic review is to study the utilization of Particle Swarm Optimization method along with its proposed variations to distribute the incoming traffic evenly with efficient resource utilization. …”
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327
Research on Scheduling Algorithm of Agricultural Machinery Cooperative Operation Based on Particle Swarm Neural Network
Published 2022-01-01“…The outer layer of the algorithm uses the improved particle swarm algorithm IPSO module, the inner layer uses the simplex algorithm SIM module, and the optimal solution of the MINLP problem is obtained through the iterative update of the inner and outer modules. …”
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328
Optimization of Backpropagation (BP) Weight Values Using Particle Swarm Optimization (PSO) to Predict KIP Scholarship Recipients
Published 2025-03-01“…To overcome this, the Particle Swarm Optimization (PSO) algorithm is used to optimize the weights of the BP artificial neural network. …”
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329
Optimization Strategies for Urban Waterlogging Warning in Complex Environments: Based on Particle Swarm Optimization and Deep Neural Networks
Published 2024-01-01“…To better address these issues, this article combines particle swarm optimization (PSO) and deep neural networks (DNN) to explore the construction of early warning models in depth. …”
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330
Suppression of Strong Cultural Noise in Magnetotelluric Signals Using Particle Swarm Optimization-Optimized Variational Mode Decomposition
Published 2024-12-01“…To effectively separate strong cultural noise in Magnetotelluric (MT) signals under strong interference conditions and restore the true forms of apparent resistivity and phase curves, this paper proposes an improved method for suppressing strong cultural noise based on Particle Swarm Optimization (PSO) and Variational Mode Decomposition (VMD). …”
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331
RAM analysis and performance optimization of paper manufacturing plant using nature-inspired algorithms
Published 2025-03-01Subjects: Get full text
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332
Cluster Partitioning Method for High-PV-Penetration Distribution Network Based on mGA-PSO Algorithm
Published 2025-02-01Subjects: Get full text
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333
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334
Image Fusion Techniques Based on Optimization Algorithms: A Review
Published 2024-01-01Subjects: Get full text
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335
Self-adapted task allocation algorithm with complicated coalition in wireless sensor network
Published 2014-03-01“…Considering the real-time requirement and some specific limitations (e.g.insufficient computing resource,energy constraint,etc) in task scheduling of wireless sensor networks,different priorities were assigned to tasks according to their deadline,and an adaptive task allocation algorithm with complicated coalition was designed through analyzing historical information.Moreover,a discrete particle swarm optimization algorithm was designed via employing binary matrix coding form.The proposed optimization algorithm generates coalitions in parallel and then performs subtask allocation algorithm based on load and energy balance.Finally,the experimental results show that the proposed algorithm strikes a good balance between local solution and global exploration,and achieves a satisfactory result within a short period of time.…”
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336
Self-adapted task allocation algorithm with complicated coalition in wireless sensor network
Published 2014-03-01“…Considering the real-time requirement and some specific limitations (e.g.insufficient computing resource,energy constraint,etc) in task scheduling of wireless sensor networks,different priorities were assigned to tasks according to their deadline,and an adaptive task allocation algorithm with complicated coalition was designed through analyzing historical information.Moreover,a discrete particle swarm optimization algorithm was designed via employing binary matrix coding form.The proposed optimization algorithm generates coalitions in parallel and then performs subtask allocation algorithm based on load and energy balance.Finally,the experimental results show that the proposed algorithm strikes a good balance between local solution and global exploration,and achieves a satisfactory result within a short period of time.…”
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337
Optimizing XGBoost Hyperparameters for Credit Scoring Classification Using Weighted Cognitive Avoidance Particle Swarm
Published 2025-01-01“…Therefore, to automate this process, weighted cognitive avoidance particle swarm optimization (WCAPSO) is employed for hyperparameter optimization. …”
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338
Multi-Criteria Optimization of a Hybrid Renewable Energy System Using Particle Swarm Optimization for Optimal Sizing and Performance Evaluation
Published 2025-03-01“…The major challenges in designing a Hybrid Renewable Energy System (HRES) include selecting appropriate renewable energy sources and storage systems, accurately sizing each component, and defining suitable optimization criteria. This study addresses these challenges by employing Particle Swarm Optimization (PSO) within a multi-criteria optimization framework to design an HRES in Kern County, USA. …”
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339
Image cluster algorithm of hybrid encoding method
Published 2017-02-01Subjects: “…image cluster analysis;hybrid encoding;rain forest algorithm;quantum particle swarm optimization…”
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340
Application of the metaheuristic algorithms to quantify the GSI based on the RMR classification
Published 2025-08-01“…This study addresses this challenge by analyzing data from fourteen different rock types and employing three metaheuristic optimization algorithms, namely Particle Swarm Optimization (PSO), Simulated Annealing (SA), and Grey Wolf Optimization (GWO), to develop predictive models for quantifying GSI based on the RMR. …”
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