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A framework of test case prioritisation in regression testing using particle swarm-artificial bee colony algorithm
Published 2024“…The research’s primary objective is to construct a framework for prioritising test cases in regression testing using swarm intelligence that enhances test efficiency and effectiveness. …”
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Modeling Of Curves And Surfaces Using Ght-Bernstein Basis Functions And Using Optimization Methods To Construct Developable Surfaces
Published 2024“…A class of GHT-Bézier developable surfaces is constructed by using the principle of duality between the planes and points. …”
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Optimization of COCOMO model using particle swarm optimization
Published 2021“…Software effort and cost estimation are crucial parts of software project development. It determines the budget, time, and resources needed to develop a software project. …”
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An elitist-flower pollination-based strategy for constructing sequence and sequence-less t-way test suite
Published 2018“…In line with the upcoming of a new field called search-based software engineering (SBSE), many newly developed t-way strategies adopting meta-heuristic algorithms can be seen in the literature for constructing interaction test suite (such as simulated annealing (SA), genetic algorithm (GA), ant colony optimisation algorithm (ACO), particle swarm optimisation (PSO), harmony search (HS) and cuckoo search (CS). …”
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Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing
Published 2011“…A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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An Orchestrated Survey on T-Way Test Case Generation Strategies Based on Optimization Algorithms
Published 2014“…This paper presents an orchestrated survey of the existing OpA t-way strategies as Simulated Annealing (SA), Genetic Algorithm (GA), Ant Colony Algorithm (ACA), Particle Swarm Optimization based strategy (PSTG), and Harmony Search Strategy (HSS). …”
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Modelling of river flow using particle swarm optimized cascade-forward neural networks: A case study of kelantan river in malaysia
Published 2023“…This paper presents river flow modelling based on meteorological and weather data in the Sungai Kelantan region using a cascade-forward neural network trained with particle swarm optimization algorithm (CFNNPSO). The result is compared with those trained with the Levenberg�Marquardt (LM) and Bayesian Regularization (BR) algorithm. …”
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Mayfly Algorithm for Modelling a Horizontal Flexible Plate Structure
Published 2024“…Researchers have devised various approaches to suppress unwanted vibrations, with contemporary studies often employing system identification techniques utilizing swarm intelligence algorithms to construct dynamic models of flexible structures. …”
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Bouc-Wen model parameter identification for a new magneto-rheologigal fluid damper using particle swarm optimization
Published 2014“…The objectives are succinct in three main criteria starting with the development of MR fluid damper, then a representation of hysteresis model and lastly optimizing these parameters by inducing PSO algorithm. …”
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Model Identification Using Neuro-Fuzzy Approach
Published 2018“…Last section of the chapter deals with three different model training algorithms Least squares based, back-propagation and particle swarm optimization. …”
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Model Identification Using Neuro-Fuzzy Approach
Published 2018“…Last section of the chapter deals with three different model training algorithms Least squares based, back-propagation and particle swarm optimization. …”
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Productivity enhancement and modelling of a new double-slope solar still with rubber scrapers in low latitude areas
Published 2018“…Experimental results obtained from the DSSSHS were used to construct the prediction models using the linear regression method and particle swarm optimization (PSO) algorithm with the aid of MATLAB software. …”
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An ensemble of neural network and modified grey wolf optimizer for stock prediction
Published 2019“…Grey Wolf Optimizer (GWO) is a recently developed meta-heuristic algorithm which is appealing to researcher owing to its demonstrated performance as cited in the scientific literature. …”
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3D prediction of tunneling-induced ground movements based on a hybrid ANN and empirical methods
Published 2019“…To overcome these problems, the use of optimization algorithms to train ANNs is of advantage. In this paper, a hybrid particle swarm optimization (PSO) algorithm-based ANN is developed to predict the maximum surface settlement and inflection points in transverse and longitudinal directions. …”
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