Search Results - (( (variable OR variables) e learning algorithm ) OR ( java simulation optimization algorithm ))
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Feasibility analysis for predicting the compressive and tensile strength of concrete using machine learning algorithms
Published 2024“…In this research, machine learning algorithms including regression models, tree regression models, support vector regression (SVR), ensemble regression (ER), and gaussian process regression (GPR) were utilized to predict the compressive and tensile concrete strength. …”
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…The simulation is implemented with iFogSim and java programming language. …”
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Ensemble-based machine learning algorithms for classifying breast tissue based on electrical impedance spectroscopy
Published 2020“…In addition, the ranked order of the variables based on their importance differed across the ML algorithms. …”
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Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing
Published 2011“…Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources. 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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Ant colony optimization algorithm for load balancing in grid computing
Published 2012“…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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Multi-stage thermal-economical optimization of compact heat exchangers: A new evolutionary-based design approach for real-world problems
Published 2015“…Furthermore, the proposed algorithm has shown a superior performance in finding the near-optimum solution for this task when it is compared to the most popular evolutionary algorithms in engineering applications, i.e. genetic algorithm (GA) and particle swarm optimization (PSO).…”
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A machine learning approach of predicting high potential archers by means of physical fitness indicators
Published 2019“…k-nearest neighbour (k-NN) has been shown to be an effective learning algorithm for classification and prediction. …”
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OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT
Published 2023“…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. …”
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A machine learning approach of predicting high potential archers by means of physical fitness indicators
Published 2019“…k-nearest neighbour (k-NN) has been shown to be an effective learning algorithm for classification and prediction. …”
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Evaluation of postgraduate academic performance using artificial intelligence models
Published 2022“…The main purpose of this study was to predict the academic performance of students, their cumulative grade point average (CGPA) in particular, at postgraduate levels (e.g., master's degree), using and comparing different machine learning (ML) algorithms. …”
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Evaluation of postgraduate academic performance using artificial intelligence models
Published 2022“…The main purpose of this study was to predict the academic performance of students, their cumulative grade point average (CGPA) in particular, at postgraduate levels (e.g., master's degree), using and comparing different machine learning (ML) algorithms. …”
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Evaluation of postgraduate academic performance using artificial intelligence models
Published 2022“…The main purpose of this study was to predict the academic performance of students, their cumulative grade point average (CGPA) in particular, at postgraduate levels (e.g., master's degree), using and comparing different machine learning (ML) algorithms. …”
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Modeling time series data using Genetic Algorithm based on Backpropagation Neural network
Published 2018“…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. …”
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