Search Results - (( develop (learner OR learned) generated algorithm ) OR ( java implication force algorithm ))
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Meta-Heuristic Algorithms for Learning Path Recommender at MOOC
Published 2021“…We have developed Metaheuristic algorithms includes the Genetic Algorithm (GA) and Ant Colony Optimization Algorithm (ACO), to solve the proposed model. …”
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Reimagining English language learning: a systematic review of AI integration in classroom practice (2019–2024)
Published 2025“…Based on 48 peer-reviewed empirical studies published between 2019 and 2024, the review explores how AI tools, particularly Natural Language Processing (NLP), Intelligent Tutoring Systems (ITS), and generative AI, support personalized learning, increase engagement, and strengthen skill development among English language learners. …”
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Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool
Published 2018“…In future, this research can be an initial work in automating tutorial decisions in an intelligent tutoring system which are able to adapt to the behaviour of the learners based on the detected mental states. Therefore, more relevant information about the students can be provided to the schools and teachers in order to increase the learning impacts.…”
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An automated learner for extracting new ontology relations
Published 2013“…Also we present a novel approach of learning based on the best lexical patterns extracted, besides two new algorithms the CIA and PS that provide the final set of rules for mining causation to enrich ontologies.…”
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Exploring the unseen: Unleashing the potential of Synthesia AI in pedagogical approaches / Ts. Jacqueline Joseph
Published 2023“…Synthesis AI is an advanced innovation that utilizes AI and deep learning algorithms to create educational videos with a humanlike voice actor. …”
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Clustering ensemble learning method based on incremental genetic algorithms
Published 2012“…Moreover, experiments demonstrate that final clustering solution generated by the proposed incremental genetic-based clustering ensemble algorithm using the pattern ensemble learning method possess comparative or better clustering accuracy than clustering solutions generated by the incremental genetic-based clustering ensemble algorithms using other recombination operators. …”
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Prediction of hydropower generation via machine learning algorithms at three Gorges Dam, China
Published 2024“…Therefore, this study investigates the capability of various machine learning algorithms in predicting the power production of a reservoir located in China using data from 1979 to 2016. …”
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Automated bilateral negotiation with incomplete information in the e-marketplace.
Published 2011“…The reason is that, SRT algorithm is sensitive to the accuracy of the learned preferences while MGT algorithm can generate Pareto-optimal offers even with an approximation of the learned preferences.…”
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Development of a Bioinspired optimization algorithm for the automatic generation of multiple distinct behaviors in simulated mobile robots
Published 2006“…Results showed that robot controllers could be successfully developed using the POE-MOEA algorithm. The generated robot controllers allowed the robots to move towards to the light source even the simulation and testing environments are noticeably different.…”
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New Learning Models for Generating Classification Rules Based on Rough Set Approach
Published 2000“…All of these models take long time to learn for a huge and dynamic data set. Thus, the challenge is how to develop an efficient model that can decrease the learning time without affecting the quality of the generated classification rules. …”
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Automatic Mind Maps Generation for The Holy Quran
Published 2022“…Therefore, the aim of this paper is to develop an algorithm that automatically generate the topics based on the mind map of a set of verses in the Holy Quran. …”
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Evaluating different machine learning models for predicting municipal solid waste generation: a case study of Malaysia
Published 2025“…Therefore, one of the aims of this research was to investigate the use of machine learning algorithms and its benefits. The machine learning algorithms investigated are specifically Gaussian process regression (GPR), ensemble of trees and neural networks. …”
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Unified neural network controller of series active power filter for power quality problems mitigation
Published 2013“…First, Widrow-Hoff algorithm is examined and its constant learning rate is modified by adding an adaptive learning rule to change the learning rate value. …”
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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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Operating a reservoir system based on the shark machine learning algorithm
Published 2018“…In the current study, the shark machine learning algorithm (SMLA) is proposed to develop an optimal rule for operating the reservoir. …”
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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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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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Ensemble learning for multidimensional poverty classification
Published 2020“…The goal of this study was to determine whether ensemble learning method (random forest) can classify poverty and hence produce multidimensional poverty indicator compared to based learner method using eKasih dataset. …”
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Prediction models of heritage building based on machine learning / Nur Shahirah Ja'afar
Published 2021“…These algorithms were developed by using prewar shophouses dataset from 2004 until 2018 based on factors of heritage properties. …”
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