Search Results - (( evolution optimisation based algorithm ) OR ( problem implementation mining algorithm ))
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Performance evaluation and benchmarking of an extended computational model of ant colony system for DNA sequence design
Published 2014“…Ant colony system (ACS) algorithm is one of the biologically inspired algorithms that have been introduced to effectively solve a variety of combinatorial optimisation problems. …”
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Article -
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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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A competitive co-evolutionary approach for the nurse scheduling problem
Published 2026“…The competitive approach further exhibits smoother convergence behaviour across generations, indicating stronger optimisation dynamics and improved robustness. These findings demonstrate that competitive co-evolution provides an effective and practical alternative to static fitness-based evolutionary methods for nurse scheduling, with broader applicability to healthcare scheduling and constraint optimisation problems.…”
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A Rough-Apriori Technique in Mining Linguistic Association Rules
Published 2008“…It uses the rough membership function to capture the linguistic interval before implementing the Apriori algorithm to mine interesting association rules. …”
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Book Chapter -
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ANALYSIS OF CUSTOMER SERVICE BUSINESS PROCESS USING DATA MINING
Published 2020“…Hence, this paper contribute to justify by the basic concepts of data mining, described the selected types and models of algorithms, and the process of data mining by using R Tools.…”
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Final Year Project -
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Comparative study of apriori-variant algorithms
Published 2016“…One of data mining methods is frequent itemset mining that has been implemented in real world applications, such as identifying buying patterns in grocery and online customers’ behavior.Apriori is a classical algorithm in frequent itemset mining, that able to discover large number or itemset with a certain threshold value. …”
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Conference or Workshop Item -
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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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Conference or Workshop Item -
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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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Analysis of Data Mining Tools for Android Malware Detection
Published 2019“…However, the problem arises in deciding the most appropriate machine learning techniques or algorithm on particular tools to be implemented on particular data. …”
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A novel approach to data mining using simplified swarm optimization
Published 2011“…Therefore, the proposed SSO rule-based classifier with local search strategies has offered a new paradigm shift in solving complex problems in data mining which may not be able to be solved by other benchmark classifiers.…”
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Thesis -
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding
Published 2025“…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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Attribute related methods for improvement of ID3 Algorithm in classification of data: A review
Published 2020“…Decision tree is an important method in data mining to solve the classification problems. There are several learning algorithms to implement the decision tree but the most commonly-used is ID3 algorithm. …”
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An enhanced intelligent database engine by neural network and data mining
Published 2000“…An Intelligent Database Engine (IDE) is developed to solve any classification problem by providing two integrated features: decision-making by a backpropagation (BP) neural network (NN) and decision support by Apriori, a data mining (DM) algorithm. …”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding
Published 2025“…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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Y-type Random 2-satisfiability In Discrete Hopfield Neural Network
Published 2024“…Additionally, the proposed Hybrid Differential Evolution Algorithm was implemented into the training phase to ensure that the cost function of the Discrete Hopfield Neural Network is minimized. …”
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Thesis -
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An Integrated Principal Component Analysis And Weighted Apriori-T Algorithm For Imbalanced Data Root Cause Analysis
Published 2016“…However, frequent pattern mining (FPM) using Apriori-like algorithms and support-confidence framework suffers from the myth of rare item problem in nature. …”
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Thesis -
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Stock market turning points rule-based prediction / Lersak Photong … [et al.]
Published 2021“…Finally, rule-based optimisation techniques such as Particle Swarm Optimization (PSO), Differential Evolution (DE) and Grey Wolf Optimizer (GWO) were used to minimise the amount of time employed in the stock market turning points prediction. …”
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Book Section -
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Case Slicing Technique for Feature Selection
Published 2004“…Finding a good classification algorithm is an important component of many data mining projects. …”
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Thesis
