Search Results - between ((teaching algorithm) OR (learning algorithm))
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Greedy-assisted teaching-learning-based optimization algorithm for cost-based hybrid flow shop scheduling
Published 2025“…However, limited attention has been given to CHFS when considering holistic cost models using efficient algorithms. This paper presents a novel Greedy-Assisted Teaching-Learning-Based Optimization (GTLBO) algorithm for CHFS. …”
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Enhancing wind power forecasting accuracy with hybrid deep learning and teaching-learning-based optimization
Published 2024“…This paper presents an innovative approach that combines deep learning (DL) with Teaching-Learning-Based Optimization (TLBO) to predict wind power output accurately. …”
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An improved teaching-learning-based optimization for extreme learning machine in floating photovoltaic power forecasting
Published 2025“…This study presents an improved teaching-learning-based optimization algorithm with extreme learning machine for floating photovoltaic power forecasting. …”
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The application of suitable sports games for junior high school students based on deep learning and artificial intelligence
Published 2025“…They are obviously lower than those of other algorithms. ST-GCN action detection algorithm based on deep learning and artificial intelligence technology can significantly improve the accuracy of action recognition in junior middle school students’ sports activities, and provide an immediate and accurate feedback mechanism for physical education teaching. …”
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A fuzzy adaptive teaching learning-based optimization strategy for generating mixed strength t-way test suites
Published 2019“…Owing to its proven performance in many other optimization problems, the adoption of the parameter-free Teaching Learning-based Optimization (TLBO) algorithm as a new t-way strategy is deemed useful. …”
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Visualization Tool for Pathfinding Algorithms
Published 2023“…By incorporating interactive features and step-by-step animations of popular pathfinding algorithms, the tool empowers students to actively engage in the learning process and experiment with different algorithmic approaches. …”
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Final Year Project Report / IMRAD -
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Modeling a problem solving approach through computational thinking for teaching programming / Zebel Al Tareq
Published 2021“…Even though there was no significant difference between the scores of the active learning methods, a comparison between both the approaches from a teaching perspective suggested that game-based learning was more suitable due to its interactivity. …”
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Enhancing understanding of programming concepts through physical games
Published 2017“…The activities were conducted involving first and fourth year undergraduate students and Master students in Programming 1 (31 students), Data Structure (6 students), Analysis of Algorithm (12 students) and Advanced Algorithm (22 students) courses respectively. …”
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Conference or Workshop Item -
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Learning style analysis based on Felder-Silverman Index Model using Rule Base algorithm
Published 2024“…The method will contain 44 questions based on four different domains of learning styles. Overall, the Learning Style Analysis System implementation is expected to positively contribute to the quality of teaching and learning at the university by aligning teaching approaches to individual learning styles. …”
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Enhancing generality of meta-heuristic algorithms through adaptive selection and hybridization
Published 2018“…Many meta-heuristic algorithms have been developed to date (e.g. Simulated Annealing (SA), Particle Swarm Optimization (PSO), Teaching Learning based Optimization (TLBO), Grey Wolf Optimizer(GWO) to name a few). …”
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Computerised Heuristic Algorithm for Multi-location Lecture Timetabling
Published 2020“…The proposed two-stage heuristic algorithm consists of Lecturer Grouping Stage which allocates the lecturers into different team-teaching groups. …”
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Chiller energy prediction in commercial building : A metaheuristic-enhanced deep learning approach
Published 2024“…This paper introduces an innovative methodology that integrates deep learning (DL), specifically Fixed Forward Neural Networks (FFNN), with Teaching-Learning-Based Optimization (TLBO) to enhance the accuracy of chiller energy consumption forecasts. …”
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Optimal power flow using a hybridization algorithm of arithmetic optimization and aquila optimizer
Published 2024“…The proposed AO-AOA algorithm follows two strategies to find a better optimal solution. …”
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Usability prioritization using performance metrics and hierarchical agglomerative clustering in MAR-learning application
Published 2023Conference Paper -
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Research on the construction of English intelligent classroom based on Artificial Intelligence
Published 2018“…For English learning, merely language teaching is not enough, nor is merely language learning, and successful English should cultivate students' intercultural communication ability and integrate the social culture factors of a language into the language teaching for students. …”
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Wind power forecasting with metaheuristic-based feature selection and neural networks
Published 2024“…Specifically, five distinct algorithms - Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Teaching-Learning-Based Optimization (TLBO), and Evolutionary Mating Algorithm (EMA) - are integrated with NN model to identify optimal feature subsets from a comprehensive dataset of 18 diverse features. …”
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Model rangkaian neural bagi penentuan gaya pembelajaran pelajar berasaskan model Felder-Silverman
Published 2022“…Artificial intelligence models are built based on neural network algorithms and the supervised machine learning technique. …”
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Comparative evaluation of tabu search hyper-heuristic against its low-level meta-heuristic constituents
Published 2019“…The results based on its application to t-way test suite generation problem indicate that HHH outperforms all its individual LLH constituents consisting of particle swarm optimization (PSO), global neighbourhood algorithm (GNA), cuckoo search (CS) algorithm and teaching learning-based opthnization algorithm (TLBO). …”
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Conference or Workshop Item -
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Current applications of machine learning in dentistry
Published 2022“…The process is similar to a human expert that can learn by repeated training (Hung et al., 2019). The quality of the output depends on the quality of data used to train and validate the algorithm (Rowe, 2019). …”
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