Search Results - (( data (replication OR implication) mining algorithm ) OR ( parallel extraction based algorithm ))
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Binary vote assignment on grid quorum replication technique with association rule
Published 2018“…The main feature of BV AGQ-AR is that the technique integrates replication and data mining technique allowing meaningful extraction of knowledge from large data sets. …”
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Exploration of machine learning forecasting methods in M4 competition / Muhammad Halim Hamdan and Shuzlina Abdul-Rahman
Published 2021“…There are so many forecasting algorithms and techniques available. The abilities of Data Mining to obtain and gather data from multiple sources is very useful to researcher, practitioner, business and more. …”
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Image classification using two dimensional wavelet coefficients with parallel computing
Published 2020“…This research algorithm demonstrated a very promising result with Support Vector Machines, this algorithm produces a 90% of accuracies whereas the decision tree algorithm gets 100% accuracies. …”
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Final Year Project / Dissertation / Thesis -
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Voting algorithms for large scale fault-tolerant systems
Published 2011“…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
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Intelligent mining of large-scale bio-data: bioinformatics applications
Published 2017“…It also highlights some future perspectives of data mining in bioinformatics that can inspire further developments of data mining instruments. …”
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Evaluation and optimization of frequent, closed and maximal association rule based classification
Published 2014“…Real world applications of association rule mining have well-known problems of discovering a large number of rules, many of which are not interesting or useful for the application at hand.The algorithms for closed and maximal item sets mining significantly reduce the volume of rules discovered and complexity associated with the task, but the implications of their use and important differences with respect to the generalization power, precision and recall when used in the classification problem have not been examined.In this paper, we present a systematic evaluation of the association rules discovered from frequent, closed and maximal item set mining algorithms, combining common data mining and statistical interestingness measures, and outline an appropriate sequence of usage.The experiments are performed using a number of real-world datasets that represent diverse characteristics of data/items, and detailed evaluation of rule sets is provided as a whole and w.r.t individual classes. …”
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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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Datasets Size: Effect on Clustering Results
Published 2013“…This gives a wider acceptance to data mining, being an interdisciplinary field that implements algorithm on stored data with a view to discovering hidden knowledge. …”
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Conference or Workshop Item -
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Online harmonic extraction and synchronization algorithm based control for unified power quality conditioner for microgrid systems
Published 2022“…Due to parallel computing feature and simple algorithm, ADALINE is utilized widely in parameter estimation. …”
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Using predictive analytics to solve a newsvendor problem / S. Sarifah Radiah Shariff and Hady Hud
Published 2023“…The best algorithm will not be the same for all the data sets. …”
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Book Section -
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An efficient indexing and retrieval of iris biometrics data using hybrid transform and firefly based K-means algorithm title
Published 2019“…The enhanced method combines three transformation methods for analyzing the iris image and extracting its local features. It uses a weighted K-means clustering algorithm based on the improved FA to optimize the initial clustering centers of K-means algorithm, known as Weighted K-means clustering-Improved Firefly Algorithm (WKIFA). …”
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Robust partitioning and indexing for iris biometric database based on local features
Published 2018“…The proposed method combines three transformation methods DCT, DWT and SVD to analyse iris images and extract their local features. Further, the scalable K-means++ algorithm is used for partitioning and classification processes, and an efficient parallel technique that divides the features groups causing the formation of two b-trees based on index keys is applied for search and retrieval. …”
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Parallelizing web scraping to improve performance and scalability
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Final Year Project / Dissertation / Thesis -
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Smart agriculture economics and engineering: Unveiling the innovation behind ai-enhanced rice farming
Published 2025“…This article introduced innovative Artificial Intelligence-based (AI-based) predictive algorithms for short-term rice production, utilizing the Cross Industry Standard Process for Data Mining (CRISP-DM) data science framework. …”
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