Search Results - (( java implementation clustering algorithm ) OR ( parameter programming model algorithm ))
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Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…This project will use fuzzy k-means clustering algorithm to cluster the data because it is easy to implement and have many advantages. …”
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Image clustering comparison of two color segmentation techniques
Published 2010“…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
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A Toolkit for Simulation of Desktop Grid Environment
Published 2014“…A simulator for desktop grid environment has been developed using Java as the implementation language due to its wide popularity. …”
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Final Year Project -
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A web-based implementation of k-means algorithms
Published 2022“…Firstly, k-luster could incorporate additional clustering algorithms, or even classification algorithms in the future. …”
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Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform
Published 2009“…The development of this architecture is based on several programming language as it involves algorithm implementation on C, parallelization using Parallel Virtual Machine (PVM) and Java for web services development. …”
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A genetic algorithm for capital budgeting problem with fuzzy parameters
Published 2010“…Thereupon, a fuzzy simulation-based genetic algorithm is provided for solving chance constrained integer programming model with fuzzy parameters.…”
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Neural network modeling and optimization for spray-drying coconut milk using genetic algorithm and particle swarm optimization
Published 2022“…The ANN model is further improved using GA and PSO. Each algorithm has its own parameters and is further optimized using RSM. …”
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Explicit solution of parameter estimate using multiparametric programming for boost converter
Published 2023“…A multiparametric programming (MPP) algorithm is fundamental to the suggested methodology, which aims to develop parameters as explicit functions of measurements. …”
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Parameter estimation of multivariable system using Fuzzy State Space Algorithm / Razidah Ismail … [et al.]
Published 2011“…The main feature of the model is the development of the Fuzzy State Space Algorithm (FSSA) for determination of input parameters that can be applied to any multivariable dynamic system. …”
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Research Reports -
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Fuzzy state space modeling for solving inverse problems in multivariable dynamic systems
Published 2005“…This model is used for optimization of input parameters in multivariable dynamic systems. …”
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Formulating and solving stochastic truck and trailer routing problems using meta-heuristic algorithms / Seyedmehdi Mirmohammadsadeghi
Published 2015“…The solutions have been significantly improved by the algorithms. This issue has been formulated under chance constrained programming (CCP) model and stochastic programming model with recourse (SPR). …”
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Controller And Circuitry Design And Implementation For Fire Fighting Robot For MIROC 2014 Competition
Published 2014“…This algorithm is designed using an iterative design model, whereby the program is continually tested and improved. …”
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Final Year Project -
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Quality of service in mobile IP networks with parametric multi-channel routing algorithms based on linear programming approach
Published 2018“…This approach tunes the parameters of the linear programming models that are used in the other algorithms by using a dynamic element. …”
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Software for modelling the static and dynamic flux linkage - current characteristics of A 6/4 SRM
Published 1996“…Program in C language was developed to validate the algorithm provided by Torrey [5,7].…”
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Student Project -
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Different mutation and crossover set of genetic programming in an automated machine learning
Published 2020“…One of the progressing works for automated machine learning improvement is the inclusion of evolutionary algorithm such as Genetic Programming. 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“…One of the progressing works for automated machine learning improvement is the inclusion of evolutionary algorithm such as Genetic Programming. 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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Novice programmers’ emotion and competency assessments using machine learning on physiological data / Fatima Jannat
Published 2022“…The Long Short-term Memory (LSTM) deep learning model was chosen for classifying programming learners according to their performance. …”
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