Search Results - (( (learner OR learned) generated using algorithm ) OR ( java application optimisation algorithm ))
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1
Study and Implementation of Data Mining in Urban Gardening
Published 2019“…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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2
Ensemble model of Artificial Neural Networks with randomized number of hidden neurons
Published 2013“…Ten base learners of the ANN model were created with each using a randomly generated number of hidden neurons. …”
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Proceeding -
3
Static code analysis of permission-based features for android malware classification using apriori algorithm with particle swarm optimization
Published 2015“…This paper presents a classification approach on android malware using candidate detectors generated from an unsupervised association rule of Apriori Algorithm. …”
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4
Android Malware classification using static code analysis and Apriori algorithm improved with particle swarm optimization
Published 2014“…This paper presents a classification of android malware using candidate detectors generated from an unsupervised association rule of Apriori algorithm improved with particle swarm optimization to train three different supervised classifiers. …”
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Proceeding Paper -
5
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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6
Bridging Mayer’s cognitive theory of multimedia learning and computational thinking in tackling the cognitive load issues among young digital natives : a conceptual framework
Published 2022“…The purpose of this paper is to study the relationship between CT and Mayer’s Cognitive Theory of Multimedia Learning (CTML) on the cognitive load of the learners. …”
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7
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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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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9
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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10
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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11
Pairwise Test Suite Generation Using Adaptive Teaching Learning-Based Optimization Algorithm with Remedial Operator
Published 2019“…Being a NP-complete problem, pairwise test suite generation problem has been addressed using several meta-heuristic algorithms including the Fuzzy Adaptive Teaching Learning-based Optimization (ATLBO) algorithm in the literature. …”
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12
Prediction of hydropower generation via machine learning algorithms at three Gorges Dam, China
Published 2024“…Three different scenarios are examined, such as scenario1 (SC1): used to predict daily power generation, scenario 2 (SC2): used to predict power generation for monthly prediction and scenario 3 (SC3): used to predict hydropower generation (HPG) seasonally. …”
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13
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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Thesis -
14
New Learning Models for Generating Classification Rules Based on Rough Set Approach
Published 2000“…Recently, different models were used to generate knowledge from vague and uncertain data sets such as induction decision tree, neural network, fuzzy logic, genetic algorithm, rough set theory, and others. …”
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15
Web-based expert system for material selection of natural fiber- reinforced polymer composites
Published 2015“…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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16
An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM)
Published 2024“…The scope of this study is tri folded, First, an exhaustive and parametric comparative study on a wide variety of machine learning algorithms is presented to evaluate the performance of machine learning algorithms in energy load prediction. …”
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17
A review on security and privacy issues in E-learning and the MapReduce aproach
Published 2019“…Then, we proposed e-Learning using MapReduce algorithm in protecting the security and privacy of eLearning. …”
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18
Unsupervised learning of image data using generative adversarial network
Published 2020“…Based on the results obtained, the GAN algorithm can learn the internal representation of data without labels and can act as good features extractor. …”
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Proceedings -
19
Next generation insect taxonomic classification by comparing different deep learning algorithms
Published 2022“…The results show that different taxonomic ranks require different deep learning (DL) algorithms to generate high-performance models, which indicates that the design of an automated systematic classification pipeline requires the integration of different algorithms. …”
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20
Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS
Published 2017“…Since extreme learning machine is a non-iterative estimation procedure, it is faster than gradient-based algorithms which are iterative. …”
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