Search Results - (( data navigation mining algorithm ) OR ( evolution optimisation based algorithm ))
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A web usage mining approach based on LCS algorithm in online predicting recommendation systems
Published 2008“…Web Usage Mining (WUM) systems are specifically designed to carry out this task by analyzing the data representing usage data about a particular Web site. …”
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A new classification model for online predicting users' future movements
Published 2008“…The WUM can model user behavior and, therefore, to forecast their future movements by mining user navigation patterns. To provide online prediction efficiently, we advance architecture for online predicting in web usage mining system by proposing novel model based on Longest Common Subsequence algorithm for classifying user navigation patterns. …”
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A recommender system approach for classifying user navigation patterns using longest common subsequence algorithm.
Published 2009“…In this paper, to provide online predicting effectively, we develop a model for online predicting through web usage mining system and propose a novel approach for classifying user navigation patterns to predict users’ future intentions. …”
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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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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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Organizational Culture Automated Audit System (OCAAS)
Published 2017“…Several state of the art technologies and techniques were used to design and developed OCAAS which include the use of machine learning and sentiment analysis based novel opinion mining algorithms for electronic opinion analysis and computerized statistics based mathematical algorithms for electronic data analysis as well as MySQL database integration for faster data processing and cognitive ergonomics system interface for user friendly interface navigation.…”
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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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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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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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Sequential pattern mining using personalized minimum support threshold with minimum items
Published 2011“…One of the challenges of Sequential Pattern Mining is finding frequent sequential patterns in a huge click stream data (web logs) since the data has the issue of a very low support distribution.By applying a Frequent Pattern Discovery technique, a sequence is considered as frequent if it occurs more than the minimum support (min sup) threshold value.The conventional method of assuming one min sup value is valid for all levels of k-sequence, may have an impact on the overall results or pattern generation. …”
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B-spline curve fitting with different parameterization methods
Published 2020“…After generating control points, distance between the generated and original data points is used to identify the error of the algorithm. Later, genetic algorithm and differential evolution optimization are used to optimise the error of the curve. …”
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Final Year Project / Dissertation / Thesis -
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Reliability assessment of power system generation adequacy with wind power using population-based intelligent search methods
Published 2017“…This study sought to examine the performance of three newly proposed techniques, for reliability assessment of the power systems, namely Disparity Evolution Genetic Algorithm (DEGA), Binary Particle Swarm Optimisation (BPSO), and Differential Evolution Optimization Algorithm (DEOA). …”
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Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level
Published 2024thesis::doctoral thesis -
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iBUST: An intelligent behavioural trust model for securing industrial cyber-physical systems
Published 2024“…In addition, a new optimisation model for finding optimum parameter values in the MEDF and an algorithm for transmuting a 1D quantitative feature into a respective categorical feature are developed to facilitate the model. …”
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Hybrid metaheuristics for QOS-aware service composition / Hadi Naghavipour
Published 2022“…On that basis, the second contribution of this thesis is proposing a fast fuzzy evolutionary algorithm with minimal stochastic behaviour. Furthermore, this thesis contributes to the body of knowledge by introducing a novel method called Fuzzy Rough set Genetic Algorithm (FRGA) that take on efficiency of metaheuristics while reducing search space by leveraging the data mining aspect of rough set theory. …”
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Simultaneous measurement of multiple soil properties through proximal sensor data fusion: a case study
Published 2019“…After choosing the optimal sensor combination for each soil property, the predictive capability was compared using different data mining algorithms, including support vector machines (SVM), random forest (RF), multivariate adaptive regression splines (MARS), and regression trees (CART). …”
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A self‐configured link adaptation for green LTE downlink transmission
Published 2015“…Current and next‐generation cellular networks require such interactive techniques in order to be self‐optimised without complex modifications.…”
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