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parallel implementation of the pso algorithm  (MathWorks Inc)


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    MathWorks Inc parallel implementation of the pso algorithm
    Parallel Implementation Of The Pso Algorithm, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/pso+implementation/10__1016_slash_j__tsep__2024__102585-290-8-11
    Average 90 stars, based on 1 article reviews
    parallel implementation of the pso algorithm - by Bioz Stars, 2026-09
    90/100 stars

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    Article Title: Inverse identification of thermal behaviour of a paraffin-based phase change material in complete and partial phase change cycles
    Article Snippet: From the macroscopic point of view, phase change hysteresis (PCH) means that a phase change process (e.g. solidification) does not follow the same temperature-enthalpy path as the opposite phase change process (melting).. Although the PCH is observed in most phase change materials (PCMs), it is often neglected in computational models, resulting in discrepancies when compared to experimental data.. The PCH can particularly be an issue in the modelling of latent heat thermal energy storage systems, where incomplete (partial) phase transitions are quite common.

    Article Title: Photovoltaic Power Generation Forecasting Using a Novel Hybrid Intelligent Model in Smart Grid
    Article Snippet: The implementation of the hybrid ANN-SVM-PSO model using MATLAB helps to obtain the results of the performance of the model based on the input data consisting of irradiance, wind speed, temperature, humidity, and load.

    Article Title: Proposing suitable data imputation methods by adopting a Stage wise approach for various classes of smart meters missing data – Practical approach
    Article Snippet: In recent years, the prediction model developed from smart meter data has been essential to analyze the load behavior of the customer, and to ensure reliability, it is necessary to have complete time-series data.. However, due to practical limitations, there occur missing values in the smart meter data affecting the accuracy of the prediction model. Customers dealt in literature so far mostly belonged to residential, commercial, and industrial categories.. In this paper, a stage-wise missing value treatment approach involving particle swarm optimization (PSO) comprising six stages has been proposed for the identification, classification, and imputation of missing values through multiple algorithms of data imputation in the smart meter dataset of an Indian institution.

    Article Title: AC‐coupled hybrid power system optimisation for an Australian remote community
    Article Snippet: Peer Review The peer review history for this article is available at https://publons.com/publon/ 10.1002/2050-7038.12503.. Summary This paper investigates the operation of various optimised AC-coupled hybrid power systems for an isolated community in South Australia.. In addition to diesel generators, various combinations of distributed generators and storage technologies are considered to form different hybrid power systems.

    Article Title: On the Identification of Orthotropic Elastic Stiffness Using 3D Guided Wavefield Data
    Article Snippet: For the implementation of PSO, the MATLAB Global Optimization ToolboxTM is used.

    Article Title: Predictive modeling of drug effects on electrocardiograms.
    Article Snippet: Whole electrocardiogram (ECG) waveform analysis is a technique for evaluating aggregate arrhythmic risks of drugs.. In this paper, we propose methods for exploring changes to ECG morphology due to drug effects using Gaussian model parameters, and predict patient specific post-drug ECG based on pre-drug ECG.. We evaluate the proposed methods using clinical ECG recordings from subjects under the effect of anti-arrhythmic drugs Dofetilide, Quinidine, Ranolazine, and Verapamil, from the ECGRVDQ database on PhysioNet.

    Article Title: Social group optimization algorithm for civil engineering structural health monitoring
    Article Snippet: Social group optimization (SGO) is a human-based metaheuristic optimization technique which shows accurate results for different benchmark functions but has not been studied for civil engineering structural health monitoring problems.. This article deals with the use of SGO for damage analysis of different modelled civil engineering structures and a real-life American Society of Civil Engineers (ASCE) benchmark structure using a stiffness-based objective function.. It is observed that SGO is not able to identify the damage in the structures owing to the algorithm becoming trapped in local optima.

    Control:

    Article Title: Structural Model Identification Using a Modified Electromagnetism-Like Mechanism Algorithm
    Article Snippet: .. There is a built-in function for PSO algorithm implementation in MATLAB, and the control parameters are set as default values. .. The computing hardware of the numerical experiment was a laptop with Intel Core i7-8650U @ 1.90 GHz and 16 GB RAM, and the software environment was MATLAB R2019b on Windows 10 platform.



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