Search Results - (( java implementation mining algorithm ) OR ( using action learning algorithm ))
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1
Direct approach for mining association rules from structured XML data
Published 2012“…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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Thesis -
2
Study and Implementation of Data Mining in Urban Gardening
Published 2019“…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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3
Scalable approach for mining association rules from structured XML data
Published 2009“…Many techniques have been proposed to tackle the problem of mining XML data we study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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4
Mining association rules from structured XML data
Published 2009“…Many techniques have been proposed to tackle the problem of mining XML data. We study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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5
A web-based implementation of k-means algorithms
Published 2022“…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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Final Year Project / Dissertation / Thesis -
6
Image clustering comparison of two color segmentation techniques
Published 2010“…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
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7
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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8
Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof
Published 2019“…From the reviews, it is evident that autonomous system is set to handle finite number of encountered states using finite sequences of actions. In order to learn the optimized states-action policy the self-learning algorithm is developed using hybrid AI algorithm by combining unsupervised weightless neural network, which employs AUTOWiSARD and reinforcement learning algorithm, which employs Q-learning. …”
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9
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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10
Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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11
Machine Learning Approach Regarding The Classification And Prediction Of Dog Sounds: A Case Study Of South Indian Breeds
Published 2024journal::journal article -
12
Revolutionizing video analytics: a review of action recognition using 3D
Published 2024“…This paper provides an overview of recent research in 3D video action recognition, concentrating on different deep learning architectures, self-supervised learning, graph-based methods, fewshot and zero-shot learning, cross-modal action understanding, and model interpretability. …”
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13
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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14
Application of reinforcement learning to wireless sensor networks: models and algorithms
Published 2015“…This covers many components and features of RL, such as state, action and reward. This article presents how most schemes in WSNs have been approached using the traditional and enhanced RL models and algorithms. …”
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15
Particle swarm optimization with deep learning for human action recognition
Published 2021“…This paper proposes a deep learning framework for human action recognition to overcome the drawbacks of the current state-of-the-art methods. …”
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16
Comparison Method Q-Learning and SARSA for Simulation of Drone Controller using Reinforcement Learning
Published 2023“…Through this study, Q-Learning and State-Action-Reward-StateAction (SARSA) are used in this study and the comparison of results involving both the performance and effectiveness of the system based on the simulation of both methods can be seen through the analysis. …”
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17
Comparison Method Q-Learning and SARSA for Simulation of Drone Controller using Reinforcement Learning
Published 2023“…Through this study, Q-Learning and State-Action-Reward-StateAction (SARSA) are used in this study and the comparison of results involving both the performance and effectiveness of the system based on the simulation of both methods can be seen through the analysis. …”
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18
Comparison Method Q-Learning and SARSA for Simulation of Drone Controller using Reinforcement Learning
Published 2023“…Through this study, Q-Learning and State-Action-Reward-StateAction (SARSA) are used in this study and the comparison of results involving both the performance and effectiveness of the system based on the simulation of both methods can be seen through the analysis. …”
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19
Comparison Method Q-Learning and SARSA for Simulation of Drone Controller using Reinforcement Learning
Published 2023“…Through this study, Q-Learning and State-Action-Reward-StateAction (SARSA) are used in this study and the comparison of results involving both the performance and effectiveness of the system based on the simulation of both methods can be seen through the analysis. …”
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20
Comparison Method Q-Learning and SARSA for Simulation of Drone Controller using Reinforcement Learning
Published 2023“…Through this study, Q-Learning and State-Action-Reward-StateAction (SARSA) are used in this study and the comparison of results involving both the performance and effectiveness of the system based on the simulation of both methods can be seen through the analysis. …”
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