Search Results - (( java implementation mining algorithm ) OR ( using single machine algorithm ))
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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 -
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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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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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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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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 -
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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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A genetic algorithm on single machine family scheduling problem to minimise total weighted completion time
Published 2009“…In this paper, we address a single machine family scheduling problem where jobs, each characterised by a processing time and an associated positive weight, are partitioned into families and setup time is required between these families. …”
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Optimization of Temperature Rise in Turning Using Single Objective Genetic Algorithm
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Genetic algorithms for single machine family scheduling problems with maximum lateness and completion time
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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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CLASSIFICATION OF BEARING FAULTS USING EXTREME LEARNING MACHINE ALGORITHMS
Published 2017“…Therefore, this project introduces three learning algorithms which are Extreme Learning Machine (ELM), Finite Impulse Response Extreme Learning Machine (FIR-ELM) and Discrete Fourier Transform Extreme Learning Machine (DFT-ELM) to improve the bearing fault diagnosis accuracy and shorten the time used to train and test the neural network.…”
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Final Year Project -
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Development Of Generative Computer-Aided Process Planning System For Lathe Machining
Published 2019“…Furthermore, to minimize unit production cost, machining parameters including cutting speed (CS), feed rate (f) and depth of cut (d) were optimized for regular form surfaces by using firefly algorithm (FA). …”
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Optimised Crossover Genetic Algorithms for Combinatorial Optimisation Problems
Published 2010“…We particularly focus on four problems: single machine family scheduling problem with maximum lateness, single machine family scheduling problem with total weighted completion time, capacitated vehicle routing problem and vehicle routing problem with time windows. …”
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Optimization of turning parameters using ant colony optimization
Published 2008“…This project proposed a new optimization technique based on the ant colony algorithm for solving single-pass turning optimization problems. …”
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Undergraduates Project Papers -
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Development of cell formation algorithm and model for cellular manufacturing system
Published 2011“…The CMS relies on the principle of grouping machines into machine cells and grouping machine parts into part families that is named cell formation. …”
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Single classifer vs. ensemble machine learning approaches for mental health prediction
Published 2023“…The data set contains responses to a survey questionnaire that was conducted by Open Sourcing Mental Illness (OSMI). Machine learning algorithms investigated in this study include Logistic Regression, Gradient Boosting, Neural Networks, K-Nearest Neighbours, and Support Vector Machine, as well as an ensemble approach using these algorithms. …”
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