Search Results - (( based extraction method algorithm ) OR ( parameter solution machine algorithm ))
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Digital economy tax compliance model in Malaysia using machine learning approach
Published 2021“…In predictive modeling, single and ensemble approaches are employed to find the best model and important factors contributing to the incompliance of tax payment among the digital economic retailers. Based on the validation of training data with the presence of seven single classifier algorithms, three performance improvements have been established through ensemble classification, namely wrapper, boosting, and voting methods, and two techniques involving grid search and evolution parameters. …”
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Intelligent classification algorithms in enhancing the performance of support vector machine
Published 2019“…The difference between the algorithms is the size of the solution archive. The size of the archive in ACOMV is fixed while in IACOMV, the size of solution archive increases as the optimization procedure progress. …”
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Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm
Published 2023Subjects:Conference Paper -
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Refinement of Tuned Mass Damper parameters on machine support structure using dynamic Cuckoo Search algorithm
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Estimation of optimal machining control parameters using artificial bee colony
Published 2013“…This research employed ABC algorithm to optimize the machining control parameters that lead to a minimum surface roughness (R a) value for AWJ machining. …”
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Development of cell formation algorithm and model for cellular manufacturing system
Published 2011“…Therefore, for this proposes good benchmarked algorithm, bacteria foraging algorithm is selected and developed to solve multiobjective cell formation model and traced constraints satisfaction handling to produce feasible optimal solution. …”
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Optimization of cnc turning parameters for minimizing temperature rise in aluminum using a genetic algorithm
Published 2024“…Thus, an optimization process is important to obtain optimized machining outcomes by optimizing machining parameters. …”
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Multi-objectives process optimization in end milling process of aluminium alloy 6061-T6 using genetic algorithm
Published 2024“…For future study, other methods or algorithms can be applied in other machining processes to obtain optimum machining parameters.…”
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Different mutation and crossover set of genetic programming in an automated machine learning
Published 2020“…The function of Genetic Programming is to optimize the best combination of solutions from the possible pipelines of machine learning modelling, including selection of algorithms and parameters optimization of the selected algorithm. …”
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Different mutation and crossover set of genetic programming in an automated machine learning
Published 2020“…The function of Genetic Programming is to optimize the best combination of solutions from the possible pipelines of machine learning modelling, including selection of algorithms and parameters optimization of the selected algorithm. …”
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Analytical Study Of Machine Learning Models For Stock Trading In Malaysian Market
Published 2024“…Nowadays, Machine Learning (ML) can serve as one of the solutions to accelerate the process of decision-making in forecasting daily stock market price movements. …”
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Real-time oil palm fruit bunch ripeness grading system using image processing techniques
Published 2013“…For example, the rule-based ROIs for statistical color feature extraction with KNN classifier at 94% were chosen. …”
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Fuzzy expert system modeling of laser processing
Published 2009“…Surface roughness quality has a large influence on the economics of the laser machining operation. Hence, this micro quality starts from the control of many parameters on the machine itself. …”
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A combinatorial optimization technique using genetic algorithm :a case study in machine layout problem
Published 2007“…However, it is impractical to solve combinatorial optimization problems by exploring all the possible solutions due to combinatorial explosion. Genetic Algorithms (GAs) are a powerful stochastic search in solving optimization problems. …”
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Final Year Project Report / IMRAD -
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Machine learning methods for herschel-bulkley fluids in annulus: Pressure drop predictions and algorithm performance evaluation
Published 2020“…The impact of each input parameter affecting the pressure drop is quantified using the RF algorithm. …”
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Data Analysis and Machine Learning Algorithms Evaluation for Bioliq AI-based Predictive Tool
Published 2019“…This final year project identified relevant parameters through literature research, analysis and expert interview, and evaluated different machine learning algorithms and identified linear regression as the most applicable and efficient with its R-square of 0.8015, qualifying it to be used for the development of a hybrid model for the AI-based tool for predictive process optimization for chemical plants.…”
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Final Year Project -
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Parameters optimization of surface grinding process with particles swarm optimization, gravitational search, and sine cosine algorithms: a comparative analysis
Published 2018“…The experimental results showed that PSO algorithm achieves better optimization performance in the aspect of convergence rate and accuracy of best solution. …”
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Optimization of micro-end milling process parameters of titanium alloy using non-dominated sorting genetic algorithm
Published 2013“…Optimal machining parameters were the spindle speed of 40000 rpm, the feed rate of 61-75 mm/min, and the depth of cut of 86-92 μm. …”
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