Search Results - (( java implementation mining algorithm ) OR ( knowledge network process 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
Sentiment mining using immune network algorithm /Raja Muhammad Hafiz Raja Kamarudin
Published 2012“…This research tries to utilize biological-inspired computing algorithm, Immune Network algorithm, in this sentiment analysis field. …”
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8
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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9
An Improvement on Extended Kalman Filter for Neural Network Training
Published 2005“…The inference accuracy, inference duration and training performance of this extended Kalman filter neural network were compared with the standard back-propagation algorithm and an improved version of the back-propagation neural network learning algorithm. …”
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10
Eye Diagram Modeling Of High-Speed Channels Using Artificial Neural Networks With An Improved Adaptive Sampling Algorithm
Published 2019“…Besides that, the use of the prior knowledge input neural network (PKI-ANN) and the prior knowledge input difference neural network (PKID-ANN) for the modeling of high dimensional SI problem is proposed. …”
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11
Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process
Published 2004“…Building knowledge within the network was measured by calculating the total percentage of error between target machining data and the outputs from the network during the training process. …”
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12
A Continuous Overlay Path Probing Algorithm For Overlay Networks
Published 2013“…Bandwidth is a key factor in network technologies and it has been of major importance throughout the history of packet networks. …”
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13
Static image of hand gesture for numerical sign language recognition system using backfrofagation neural network / Erman Ibrahim
Published 2007“…This project is about recognizing hand gesture for sign language using backpropagation (BP) algorithm that is one of the training algorithms used in the Artificial Neural Network (ANN). …”
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14
Static and self-scalable filter range selection algorithms for peer-to-peer networks
Published 2011“…For peer-to-peer networks, Loo (2005) selection algorithm has been selected as the benchmark as it is an established algorithm that claimed to be the best proposed for this network. …”
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15
Hybrid Neural Networks and Genetic Algorithm for Fault Detection and Diagnosis of a Plant
Published 2008“…Keywords: Fault Detection, Thermal Power Plant, Neural Networks (ANNs), Genetic Algorithms (GAs). Intelligent Networking. …”
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16
What, how and when to use knowledge in neural network application
Published 2004“…; How to use this knowledge?; and When to use this knowledge? Knowledge is simply the weights that connect each neuron in neural networks. …”
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17
E4ML: Educational Tool for Machine Learning
Published 2003“…There are various types of machine learning algorithms with certain processes taken by the algorithm.In teaching of the machine learning algorithms, such processes need to be explained especially to the beginner in introductory level.This paper discusses the development the tool that addresses the process by certain algorithm to produce a hypothesis or output based on given data.This tool can also be used in teaching and learning purposes.The explanation of processes by the algorithms is demonstrated through simple simulation.The source of the algorithms was adapted from Mitchell book [1] that cover popular algorithms in machine learning for teaching and learning such as Concept Learning, Decision Tree, Bayesian Learning, Neural Networks, and Instance based Learning.The tool also used several classes of Weka (Waikato Environment for Knowledge Analysis) as a basis for the design and implementation of the new tool that focuses on explaining the processes taken by certain algorithm.…”
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18
Coalition of genetic algorithms and artificial neural network for isolated spoken Malay speech recognition / Noraini Seman
Published 2012“…However, due to the stochastic nature of this algorithm, the learning process can reach an optimal solution with much higher probability than many standard neural network techniques.…”
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Book Section -
19
Multi-Backpropagation network
Published 2002“…The learning mechanism for Neural Network is its learning algorithm. Backpropagation (or backprop) algorithm is one of the well-known algorithms in neural networks. …”
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20
Twisted pair cable fault diagnosis via random forest machine learning
Published 2022“…Secondly, the feature transformation, a knowledge-based method, is utilized to pre-process the fault data. …”
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