Search Results - (( developing case selection algorithm ) OR ( java application stemming algorithm ))
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Minimization of Test Cases and Fault Detection Effectiveness Improvement through Modified Reduction with Selective Redundancy Algorithm
Published 2007“…To achieve such goal, this research modifies and improves the Reduction with Selective Redundancy (RSR) algorithm. In the modify algorithm, test cases would be selected according to the branch coverage if they covered different branch combination. …”
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An interactive analytics approach for sustainable and resilient case studies: a machine learning perspective
Published 2023“…The selected cases are the river pollution problem, the urban transit network design problem, and the resilience problem. …”
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Firefly algorithm for optimal sizing of Standalone Photovoltaic System / Nurizzati Abdul Aziz
Published 2016“…In addition, sizing algorithm with FA was also discovered to outperform sizing algorithm with selected computational intelligence, i.e. …”
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Firefly algorithm for optimal sizing of stand-alone photovoltaic system / Nur Izzati Abdul Aziz
Published 2016“…In addition, sizing algorithm with FA was also discovered to outperform sizing algorithm with selected computational intelligence, i.e. …”
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Hybrid Artificial Bees Colony algorithms for optimizing carbon nanotubes characteristics
Published 2018“…Chemical Vapor Deposition (CVD) is the most efficient method for CNTs production.However,using CVD method encounters crucial issues such as customization,time and cost.Therefore,Response Surface Methodology (RSM) is proposed for modeling and the ABC-βHC is proposed for optimization purpose to address such issues.The selected CNTs characteristics are CNTs yield and quality represented by the ratio of the relative intensity of the D and G-bands (ID/IG).Six case studies are generated from collected dataset including four cases of CNTs yield and one case of ID/IG as single objective optimization problems,while the sixth case represents multi-objective problem.The input parameters of each case are a subset from the set of input parameters including reaction temperature,duration,carbon dioxide flow rate,methane partial pressure,catalyst loading,polymer weight and catalyst weight.The models for the first three case studies were mentioned in the original work.RSM is proposed to develop polynomial models for the output responses in the other three cases and to identi significant process parameters and interactions that could affect the CNTs output responses.The developed models are validated using t-test,correlation and pattern matching.The predictive results have a good agreement with the actual experimental data.The models are used as objective functions in optimization techniques.For multi-objective optimization,this study proposes Desirability Function Approach (DFA) to be integrated with other proposed algorithms to form hybrid techniques namely RSM-DFA,ABC-DFA and ABC-βHC-DFA.The proposed algorithms and other selected well-known algorithms are evaluated and compared on their CNTs yield and quality.The optimization results reveal that ABC-βHC and ABC-βHC-DFA obtained significant results in terms of success rate,required time,iterations,and function evaluations number compared to other well-known algorithms.Significantly,the optimization results from this study are better than the results from the original work of the collected dataset.…”
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An integrated algorithm of analytical network process with case-based reasoning to support the selection of an ideal football team formation and players
Published 2021“…A new combined decision model which integrates Analytical Network Process and Case-based Reasoning was developed. The algorithm converts the model to coding, structures the process of entering data, automates the calculations and presents the results in a well-organized and suitable interfaces for the team managerial review purposes. …”
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Intership supervisor selection using genetic algorithms
Published 2015“…By using genetic algorithm approach, the priority factors for the assigning faculty supervisor to internship student has been identified and also development model of selection has been done to fulfill the criteria for the selection specified by the FTMK. …”
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Enhancing generality of meta-heuristic algorithms through adaptive selection and hybridization
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Modelling and optimization of catalytic-dielectric barrier discharge plasma reactor for methane and carbon dioxide conversion using hybrid artificial neural network - genetic algor...
Published 2007“…Pareto optimal solutions and the corresponding optimal operating parameter range based on multi-objective scan be suggested for two cases, i.e., simultaneous maximization of CH4 conversion and C2+ selectivity (Case 1), and H-2 selectivity and H-2/CO ratio (Case 2). …”
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Dengue classification system using clonal selection algorithm / Karimah Mohd
Published 2012“…This project focused on three main objectives: to investigate dengue data and Clonal Selection Algorithm for classification of Dengue, to design and develops Clonal Selection Classification System (CSCS) and to evaluate Clonal Selection Classification System symptoms. …”
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Improving the accuracy of AIRS by incorporating real world tournament selection in resource competition phase
Published 2009“…The combination of cross validation and t test is used as evaluation method. Algorithms tested on benchmark datasets of the UCI machine learning repository show that RWTSAIRS obtained higher accuracy than AIRS in all cases and that the difference between accuracies of two algorithms was significant in majority of cases.…”
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An experimental study of neighbourhood based metaheuristic algorithms for test case generation satisfying the modified condition / decision coverage criterion
Published 2018“…Performance of each algorithm is compared in terms of number of test cases generated as well as the run time required. …”
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Computer Lab Timetabling Using Genetic Algorithm Case Study - Unit ICT
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An improved diabetes risk prediction framework : An Indonesian case study
Published 2018“…Pre-processing resolves the issue of missing data and hence normalizes the data.Outlier treatment employs k-mean clustering to validate the class.Suitable components were selected through comparison of classifier algorithms and feature selection.Attribute weighting based feature selection was selected for assigning weightage.Weighted risk factor was used on training dataset in order to improve accuracy and computation time of the prediction. …”
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Computational dynamic support model for social support assignments around stressed individuals among graduate students
Published 2020“…The algorithm complexity analysis was used to measure the execution time in the worst case. …”
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CTJ: Input-output based relation combinatorial testing strategy using Jaya algorithm
Published 2019“…Thus, IOR combinatorial testing is selected to be studied in this research. To overcome the combinatorial optimization problem, Jaya algorithm is proposed to apply in this project since metaheuristic algorithm is fast in optimization and this strategy is named as CTJ. …”
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Undergraduates Project Papers -
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Optimization of assembly line balancing with energy efficiency by using tiki-taka algorithm
Published 2023“…Lastly, a study of the industrial case was performed as a validation of the developed model and algorithm. …”
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The Development of an Algorithm to Determine Axial Capacity of Piles from SPT N-Values
Published 2000“…The developed IT was used for all cases of algorithm testing. …”
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