Search Results - (( exploring _ learning algorithm ) OR ( java implication based algorithm ))
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Computational Thinking (Algorithms) Through Unplugged Programming Activities: Exploring Upper Primary Students’ Learning Experiences
Published 2021“…Studies have shown the effectiveness of UPA in developing CT skills and is comparable to the technology driven learning method. The aim of this study is to explore the experience of primary school students on their learning of algorithms, which is one of the CT skills, through the UPA method. …”
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Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems
Published 2022“…To overcome these drawbacks and to achieve an appropriate percentage of exploitation and exploration, this study presents a new modified teaching learning-based optimization algorithm called the fuzzy adaptive teaching learning-based optimization algorithm. …”
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Modified Opposition Based Learning to Improve Harmony Search Variants Exploration
Published 2020“…Opposition-based learning variants enhanced the explorations and help optimization algorithms to avoid local optima falling. …”
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Enhanced Adaptive Confidence-Based Q Routing Algorithms For Network Traffic
Published 2004“…The CQ Routing Algorithm is intended to improve the quality of actions made in exploration phase while dual reinforcement learning emphasises on increasing the number of actions occurred in exploration phase. …”
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Improving the exploration strategy of an automated android GUI testing tool based on the Q-Learning algorithm by selecting potential actions
Published 2022“…Furthermore, the proposed techniques based on the Q-Learning algorithm do not consider context-based actions. …”
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Enhancing simulated kalman filter algorithm using current optimum opposition-based learning
Published 2019“…From literature, current optimum opposition-based learning (COOBL) has been employed to increase the diversity (exploration) of search algorithm by allowing current population to be compared with an opposite population. …”
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Comparison between Lamarckian Evolution and Baldwin Evolution of neural network
Published 2006“…Hybrid genetic algorithms are the combination of learning algorithms(Back propagation), usually working as evaluation functions, and genetic algorithms. …”
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An energy-efficient spectrum-aware reinforcement learning-based clustering algorithm for cognitive radio sensor networks
Published 2015“…While the topic of energy efficiency has been well investigated in conventional wireless sensor networks, the latter has not been extensively explored. In this paper, we propose a reinforcement learning-based spectrum-aware clustering algorithm that allows a member node to learn the energy and cooperative sensing costs for neighboring clusters to achieve an optimal solution. …”
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Automated bilateral negotiation with incomplete information in the e-marketplace.
Published 2011“…The MGT algorithm is useful to explore the properties of the Pareto-optimal offers. …”
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Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model
Published 2018“…In this article, we present the exploration on the combination of the clustering based algorithm with an ensemble classification learning. …”
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Autism Spectrum Disorder Classification Using Deep Learning
Published 2021“…Recently, deep learning methods have significantly sharpened the cutting edge of learning algorithms in a wide range of artificial intelligence tasks. …”
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Enhanced Q-Learning algorithm for potential actions selection in automated graphical user interface testing
Published 2023“…To overcome this limitation, the Q-Learning algorithm was proposed by several researchers to minimise randomness. …”
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Q-learning whale optimization algorithm for test suite generation with constraints support
Published 2023“…This paper introduces a new variant of a metaheuristic algorithm based on the whale optimization algorithm (WOA), the Q-learning algorithm and the Exponential Monte Carlo Acceptance Probability called (QWOA-EMC). …”
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Improved intrusion detection algorithm based on TLBO and GA algorithms
Published 2021“…The proposed method combined the New Teaching-Learning-Based Optimization Algorithm (NTLBO), Support Vector Machine (SVM), Extreme Learning Machine (ELM), and Logistic Regression (LR) (feature selection and weighting) NTLBO algorithm with supervised machine learning techniques for Feature Subset Selection (FSS). …”
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Industry 5.0 and Education 5.0: Transforming Vocational Education through Intelligent Technology
Published 2024“…By analyzing the research gaps in personalized learning paths, emotion-driven learning, crossdisciplinary integration, and long-term learning behavior analysis, the paper proposes four improved algorithms: the adaptive learning path generation algorithm, the emotion-driven personalized learning algorithm, the cross-disciplinary knowledge graph algorithm, and the long-term learning behavior prediction algorithm. …”
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Opposition- based simulated kalman filters and their application in system identification
Published 2017“…From literature, Opposition-based Learning (OBL) has been employed to increase the diversity (exploration) of search algorithm by allowing current population to be compared with an opposite population. …”
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Application of deep learning algorithms in lung sound classification: A systematic review since 2015
Published 2025“…The article’s thorough analysis revealed that deep learning algorithms have outperformed traditional machine learning techniques in lung sound classification.…”
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