Search Results - (( developing function learning algorithm ) OR ( java evaluation case algorithm ))
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A new hybrid fuzzy ARTMAP and radial basis function neural network with online pruning strategy
Published 2023Conference Paper -
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A Reference Based Surface Defect Segmentation Algorithm For Automatic Optical Inspection System
Published 2020“…This study aims to develop an algorithm for the AOI system to segment and detect surface defects, requiring low processing power and a small number of learning dataset with labelling error resistance. …”
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Comparison of performances of Jaya Algorithm and Cuckoo Search algorithm using benchmark functions
Published 2022“…To help engineers select the best metaheuristic algorithms for their problems, there is a need to evaluate the performance of different metaheuristic algorithms against each other using common case studies. …”
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Binary Coati Optimization Algorithm- Multi- Kernel Least Square Support Vector Machine-Extreme Learning Machine Model (BCOA-MKLSSVM-ELM): A New Hybrid Machine Learning Model for Pr...
Published 2024“…In this study, we used extreme learning machine (ELM)-multi-kernel least square support vector machine (ELM-MKLSSVM), extreme learning machine (ELM)-LSSVM-polynomial kernel function (PKF) (ELM-LSSVM-PKF), ELM-LSSVM-radial basis kernel function (RBF) (ELM-LSSVM-RBF), ELM-LSSVM-Linear Kernel function (LKF), ELM, and MKLSSVM models to predict water level. …”
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An enhancement of multi-factor weighted approach technique in prioritizing test cases by comparing similarity distance
Published 2025“…Software testing is one of the most critical phases in the software development life cycle model (SDLC), where the quality of a software product is evaluated. Test case prioritization (TCP) is used to prioritize and schedule test case execution to conduct higher-priority test cases to optimize the software testing process. …”
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Hybrid Harmony Search Algorithm with Grey Wolf Optimizer and Modified Opposition-based Learning
Published 2019“…Many variants have been developed to cope with this problem and improve algorithm performance. …”
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A framework of test case prioritisation in regression testing using particle swarm-artificial bee colony algorithm
Published 2024“…This research employed a modified version of the Design Science Research Methodology (DSRM), streamlined into five stages: problem identification, theoretical study, framework development, evaluation, and reporting. The developed framework, grounded in fault-based testing theory, comprises three key components: inputs, prioritization factors, and a prioritization 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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Support directional shifting vector: A direction based machine learning classifier
Published 2021“…The positional error of the linear function has been modelled as a loss function which is iteratively optimized using the gradient descent algorithm. …”
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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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E-history Malaysian secondary school textbook using TF-IDF algorithm and text visualization / Nur Hafizah Mohd Ridzuan
Published 2020“…The objective of the project is to design and develop an E-History Malaysian secondary school textbook system using Term Frequency-Inverse Document Frequency (TF-IDF) algorithm with text visualization and also to test the functionality and usability of the system through a web-based system. …”
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Evaluation of optimal MLP structure for heart disease diagnosis / Salbiah Ab Hamid
Published 2010“…A transfer function simulation model is developed by using the MATLAB software. …”
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Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy
Published 2019“…An efficient iterative algorithm is developed to optimize the objective function of the proposed algorithm since it is non-smooth and difficult to solve. …”
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Acceleration Strategies For The Backpropagation Neural Network Learning Algorithm
Published 2001“…In this thesis, factors that govern the learning speed of the backpropagation algorithm are investigated and mathematically analyzed in order to develop strategies to improve the performance of this neural network learning algorithm. …”
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Quantum-Behaved Lightning Search Algorithm to Improve Indirect Field-Oriented Fuzzy-PI Control for im Drive
Published 2023Conference Paper -
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Clustering ensemble learning method based on incremental genetic algorithms
Published 2012“…In order to address the above mentioned challenges, this study is devoted towards the development of a clusterer and a clustering ensemble learning method based on incremental genetic algorithms addressing group unlabeled samples. …”
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RECURSIVE LEARNING ALGORITHMS ON RBF NETWORKS FOR NONLINEAR SYSTEM IDENTIFICATION
Published 2010“…Science and technology development has the tendency of learning from nature where human also try to develop artificial intelligent by imitating biological neuron network which is popularly termed Artificial Neural Network (ANN). …”
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Graph-Based Algorithm With Self-Weighted And Adaptive Neighbours Learning For Multi-View Clustering
Published 2024“…To address this issue, this study incorporated joint graph learning from the gmc algorithm into swmcan, creating a new algorithm called swmcan-jg. …”
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