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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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Multi-Objective Discrete Particle Swarm Optimisation Algorithm for Integrated Assembly Sequence Planning and Assembly Line Balancing
Published 2016“…In order to optimise an integrated assembly sequence planning and assembly line balancing, this work proposes a multi-objective discrete particle swarm optimisation algorithm that used discrete procedures to update its position and velocity in finding Pareto optimal solution. …”
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Intergrated multi-objective optimisation of assembly sequence planning and assembly line balancing using particle swarm optimisation
Published 2013“…The aim of this research is to establish a methodology and algorithm for integrating ASP and ALB optimisation using Particle Swarm Optimisation. …”
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Improved Bat Algorithm for faster convergence in solving optimisation problem
Published 2021“…The results show that the IBA performs better than Harmony Search (HS), Particle Swarm Optimisation (PSO) and Genetic Algorithm (GA). …”
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Linear-PSO with binary search algorithm for DNA Motif Discovery / Hazaruddin Harun
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Linear-pso with binary search algorithm for DNA motif discovery / Hazaruddin Harun
Published 2015“…The Linear-PSO algorithm was the first version of improvement. However due to the longer time required for complete execution of this algorithm, the Binary Search technique was integrated and a new version of the algorithm was developed, namely the Linear-PSO with Binary Search (LPBS) algorithm. …”
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Comparison of Sequential and Integrated Optimisation Approaches for ASP and ALB
Published 2017“…An algorithm named Multi-Objective Discrete Particle Swarm Optimisation (MODPSO) is applied in both approaches. …”
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A genetic algorithm to minimise the maximum lateness on a single machine family scheduling problem
Published 2009“…In this study, we propose an Optimised Crossover Genetic Algorithm (OCGA) for the problem. …”
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Study and Implementation of Data Mining in Urban Gardening
Published 2019“…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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Dynamic modelling of a flexible beam structure using feedforward neural networks for active vibration control
Published 2019“…A non-parametric modelling approach of the system was proposed based on feed-forward neural networks (FNNs) while its weight and bias parameters were optimised using chaotic-enhanced stochastic fractal search (SFS) algorithm. …”
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Mining Sequential Patterns using I-PrefixSpan
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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Mining Sequential Patterns Using I-PrefixSpan
Published 2007“…In this paper, we propose an improvement of pattern growth-based PrefixSpan algorithm, called I-PrefixSpan. The general idea of I-PrefixSpan is to use the efficient data structure for general tree-like framework and separator database to reduce the execution time and memory usage. …”
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AI powered asthma prediction towards treatment formulation: an android app approach
Published 2022“…We utilized eight robust machine learning algorithms to analyze this dataset. We found that the Decision tree classifier had the best performance, out of the eight algorithms, with an accuracy of 87%. …”
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AI powered asthma prediction towards treatment formulation : An android app approach
Published 2022“…We utilized eight robust machine learning algorithms to analyze this dataset. We found that the Decision tree classifier had the best performance, out of the eight algorithms, with an accuracy of 87%. …”
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