Search Results - (( based context learning algorithm ) OR ( java implication based algorithm ))
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Enhanced Q-Learning algorithm for potential actions selection in automated graphical user interface testing
Published 2023“…We utilized the enhanced Q-Learning algorithm to compare actions, including context-based actions, to effectively achieve higher code coverage. …”
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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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Machine learning algorithms in context of intrusion detection
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Conference or Workshop Item -
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Clustering ensemble learning method based on incremental genetic algorithms
Published 2012“…In the first and second phases, a threshold fuzzy c-means clustering algorithm as a clusterer and a pattern ensemble learning method based on the incremental genetic-based algorithms are proposed respectively. …”
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5
Context-Aware Recommender System based on machine learning in tourist mobile application / Nor Liza Saad … [et al.]
Published 2022“…Furthermore, data were collected simulated based on the mobile application prototype to be used for finding the suitable machine learning algorithms in the recommendation system module. …”
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Transfer learning for sentiment analysis using bert based supervised fine-tuning
Published 2022“…In addition, we also introduced the ability of transfer learning to classical machine learning algorithms for the performance comparison of CNN-BiLSTM. …”
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Acquisition of context-based word recognition by reinforcement learning using a recurrent neural network
Published 2012“…The developed learning system has a 4-layered RNN and it was trained by BPTT method based on teaching signal that was generated by Q-Learning algorithm. …”
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Acquisition of context-based word recognition by reinforcement learning using a recurrent neural network
Published 2012“…The developed learning system has a 4-layered RNN and it was trained by BPTT method based on teaching signal that was generated by Q-Learning algorithm. …”
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9
Acquisition of context-based word recognition by reinforcement learning using a recurrent neural network
Published 2012“…The developed learning system has a 4-layered RNN and it was trained by BPTT method based on teaching signal that was generated by Q-Learning algorithm. …”
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Undergraduates Project Papers -
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Machine Learning Approach Regarding The Classification And Prediction Of Dog Sounds: A Case Study Of South Indian Breeds
Published 2024journal::journal article -
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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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Dynamic Bayesian Networks and Variable Length Genetic Algorithm for Dialogue Act Recognition
Published 2007“…The current dialogue act recognition models, namely cue-based models, are based on machine learning techniques, particularly statistical ones. …”
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Context enrichment framework for sentiment analysis in handling word ambiguity resolution
Published 2024“…A rule-based method is introduced to select context words based on their similarity. …”
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Design and optimization of Levenberg-Marquardt based Neural Network Classifier for EMG signals to identify hand motions
Published 2013“…Between the Levenberg-Marquardt and scaled conjugate gradient learning algorithms, the aforesaid algorithm shows better classification performance. …”
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Behavioural Feature Extraction For Context-Aware Traffic Classification Of Mobile Applications
Published 2018“…This thesis identified domain-specific features that are effective for accurate, large-scale and scalable mobile applications classification using machine learning techniques. This thesis designed a context-aware traffic classification framework that includes a set of sequential algorithms from cleaning datasets, to identifying new features and detecting optimal classifier(s) based on problem contexts to improve classification accuracy in multi-variate traffic classification.…”
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Machine learning based-model to predict catalytic performance on removal of hazardous nitrophenols and azo dyes pollutants from wastewater
Published 2025“…In this particular research study, the application of machine learning techniques was employed in order to make an estimation of the performance of reduction catalysis in the context of ecologically detrimental nitrophenols and azo dyes contaminants. …”
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Multitasking deep neural network models for Arabic dialect sentiment analysis
Published 2022“…The existing approaches are based on traditional machine learning algorithms, such as support vector machine (SVM). …”
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