Search Results - (( developing function methods algorithm ) OR ( learner detection using algorithm ))
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Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool
Published 2018“…From the data analysis using WEKA software, the production rules classifier (PART) is found to be the most accurate classification algorithm in classifying the emotion which yields the highest precision percentage of 99.6% compared to J48 (99.5%) and Naïve Bayes (96.2%). …”
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Thesis -
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A conceptual multi-agent framework using ant colony optimization and fuzzy algorithms for learning style detection
Published 2023“…We discuss both agent and multi-agent systems and focus on the implications of the theory of detecting learning styles that constitutes behaviors of learners when using online learning systems, learner's profile, and the structure of multi-agent learning systems. …”
Conference Paper -
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An ensemble deep learning classifier stacked with fuzzy ARTMAP for malware detection
Published 2023“…In this paper, we propose an ensemble DL classifier stacked with the Fuzzy ARTMAP (FAM) model for malware detection. The stacked ensemble method uses several heterogeneous deep neural networks as the base learners. …”
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Android Malware classification using static code analysis and Apriori algorithm improved with particle swarm optimization
Published 2014“…The results of the experiments show that the proposed combined technique has remarkable benefits over the detection using only supervised or unsupervised learners.…”
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Proceeding Paper -
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Development of an automated tool for detecting errors in tenses
Published 2012“…This proves that ATDEiT™ has the potential to be used as an automated tool for detecting errors in tenses for ESL learners.…”
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Static code analysis of permission-based features for android malware classification using apriori algorithm with particle swarm optimization
Published 2015“…In this method, permission-based features were extracted from Android applications byte-code through static code analysis, selected and were used to train supervised classifiers. Using a number of candidate detectors from an improved Apriori Algorithm with Particle Swarm Optimization, the true positive rate of detecting malicious code is maximized, while the false positive rate of wrongful detection is minimized. …”
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Semiparametric inference procedure for the accelarated failure time model with interval-censored data
Published 2019“…The rank-based methods, estimating algorithms, and resampling techniques that are developed do not involve the difficulties of the existing estimating procedures. …”
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A parallel ensemble learning model for fault detection and diagnosis of industrial machinery
Published 2023“…The base learners adopt a hybrid Back-Propagation (BP) and Particle Swarm Optimization (PSO) algorithms to exploit the corresponding local and global optimization capabilities for identifying optimal features and improving FDD performance. …”
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Development and applications of metaheuristic algorithms in engineering design and structural optimization / Ali Sadollah
Published 2013“…In addition, two novel optimization methods are developed and presented which are named the mine blast algorithm (MBA) and the water cycle algorithm (WCA). …”
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Thesis -
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A Novel Discrete Filled Function Algorithm in Solving Discrete Optimization Problems (S/O: 12408)
Published 2016“…We focus our study on a recently developed method known as discrete filled function method. …”
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Monograph -
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A multi-nets ANN model for real-time performance-based automatic fault diagnosis of industrial gas turbine engines
Published 2017“…Two back-propagation training algorithms, namely the Levenberg–Marquardt and Bayesian regularization algorithms, and the k-fold cross-validation technique, were employed to train the optimal networks using a training data set. …”
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Economic dispatch with piecewise linear function and line loss / Amir Ashraf Mohd Johari
Published 2014“…A system of three generation units are tested with developed algorithm. The results obtained show that the proposed method is able to provide the solution of economic dispatch with piecewise linear incremental function and line losses.…”
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A study on regional GDP forecasting analysis based on radial basis function neural network with genetic algorithm (RBFNN-GA) for Shandong economy
Published 2022“…This stochastic learning method is a useful addition to the existing methods for determining the center and smoothing factors of radial basis function neural networks, and it can also help the network more efficiently train. …”
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Sports tournament scheduling using genetic algorithm / Hafeezur Syakir Abdul Motok@Mohd Ridzuan
Published 2020“…The functionality testing is conducted using Blackbox testing technique to test the functionality of the project.…”
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Development of multi-objective optimization methods for integrated scheduling of handling equipment (AGVs, QCs, SP-AS/RS) in automated container terminals
Published 2012“…Therefore, two meta-heuristic algorithms, namely genetic algorithm (GA) and simulated annealing (SA) algorithm, were developed to optimize the integrated scheduling of handling equipment. …”
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Breast cancer disease classification using fuzzy-ID3 algorithm based on association function
Published 2022“…The FID3-AF algorithm is a hybridisation of the fuzzy system, the iterative dichotomizer 3 (ID3) algorithm, and the association function. …”
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Hybrid artificial immune system-genetic algorithm optimization based on mathematical test functions
Published 2023“…This paper demonstrates a hybrid between two optimization methods that are Artificial Immune System (AIS) and Genetic Algorithm (GA). …”
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Feature fusion using a modified genetic algorithm for face and signature recognition system
Published 2015“…A modified fitness function in Wrapper GA was introduced by adding a function to maintain the balanced of the selected features. …”
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Curve Reconstruction By Metaheuristics Algorithms On Cubic Rational Bézier Function
Published 2019“…The optimisation technique consists of exact algorithm, and approximate algorithm. The approximate algorithm is a good technique to be highlighted since it is a feasible way to develop an easier, more convenient curve fitting method, that will save great computation, solve a large scale problem and produce a better quality end result. …”
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