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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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Particle swarm optimization for neural network learning enhancement
Published 2006“…Two programs have been developed; Particle Swarm Optimization Feedforward Neural Network (PSONN) and Genetic Algorithm Backpropagation Neural Network (GANN). …”
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Differential evolution for neural networks learning enhancement
Published 2008“…These algorithms can be used successfully in many applications requiring the optimization of a certain multi-dimensional function. …”
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A preliminary study of difficulties in learning java programming for secondary school
Published 2020“…The results showed the subtopic of function and procedure was difficult for most of the respondents, regardless kind of programming languages they learned. © 2020, World Academy of Research in Science and Engineering. …”
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Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process
Published 2004“…Artificial Neural Network (ANN) was selected from Machine Learning Algorithms to be the learning algorithm. …”
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Classification of machine learning engines using latent semantic indexing
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A new mobile botnet classification based on permission and API calls
Published 2024Conference Paper -
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Firefly algorithm-based neural network for GCPV system output prediction: article / Nor Syakila Mohd Zainol Abidin
Published 2014“…Additionally, the optimal population size, absorption confession, learning algorithm and type of transfer functions in FA were also investigated in this study. …”
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DESIGN OF IMPROVED GRID FOR TURTLE ROBOT
Published 2013“…This is the followed by developing improved grid design with new algorithm which is then tested continuously to ensure its functionality working flawlessly. …”
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Optimized processing of satellite signal via evolutionary search algorithm
Published 2000“…A robust strategy, called the Pseudo Randomized Search Strategy (PRSS) has been developed to counter the effect of this AS policy. The PRSS algorithm is an adaptive search technique that can learn a high performance knowledge structure in reactive environments that provide information as an objective function. …”
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Performance analysis of support vector machine, Gaussian Process Regression, sequential quadratic programming algorithms in modeling hydrogen-rich syngas production from catalyzed...
Published 2022“…Taking advantage of the data generated from the process, this study explores the performance of twelve machine learning algorithms built on the support vector machine (SVM), the Gaussian process regression (GPR), and the non-linear response quadratic model (NLRQM) using Sequential quadratic programming, and the Levenberg-Marquardt algorithms. …”
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A Stepper Motor Design Optimization Using
Published 2005“…There is a need to fill this void in the area of small-motor design, and develop a program using Genetic Algorithms (GAs) as an approach to achieve optimization. …”
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Monograph -
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A New Mobile Botnet Classification based on Permission and API Calls
Published 2024“…As a result, 16 permissions and 31 API calls that are most related with mobile botnet have been extracted using feature selection and later classified and tested using machine learning algorithms. The experimental result shows that the Random Forest Algorithm has achieved the highest detection accuracy of 99.4% with the lowest false positive rate of 16.1% as compared to other machine learning algorithms. …”
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A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem
Published 2016“…The main keys of the new classifier are based on the new kernel method, new learning metric and a new optimization algorithm in order to optimize the SVM decision function. …”
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An evaluation of Monte Carlo-based hyper-heuristic for interaction testing of industrial embedded software applications.
Published 2020“…The results show the Q-EMCQ is also capable of outperforming the original EMCQ as well as several recent meta/hyper-heuristic including modified choice function, Tabu high-level hyperheuristic, teaching learning-based optimization, sine cosine algorithm, and symbiotic optimization search in clustering quality within comparable execution time.…”
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Current applications of machine learning in dentistry
Published 2022“…Additionally, deep learning (DL), which is a subset of ML, was inspired by the structure and function of the human brain called artificial neural network (ANN). …”
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