Search Results - (( data selection method algorithm ) OR ( data visualisation using algorithm ))
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A COMPARISON STUDY OF DATA CLUSTERING AND VISUALISATION TECHNIQUES WITH VARIOUS DATA TYPES
Published 2020“…In this project, experiments on visualisation and performance analysis of selected clustering methods are conducted. …”
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Final Year Project Report / IMRAD -
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Predicting 30-day mortality after an acute coronary syndrome (ACS) using machine learning methods for feature selection, classification and visualization
Published 2021“…Hybrid combinations of feature selection, classification and visualisation using machine learning (ML) methods have the potential for enhanced understanding and 30-day mortality prediction of patients with cardiovascular disease using population-specific data. …”
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Menu recommendation for Restoran Jannat Saba using Market Basket analysis / Dinie Sorfina Fathanah Kamarul Ariffin
Published 2025“…The FP-Growth algorithm has been employed for its effectiveness in identifying frequent itemsets and association rules in transactional data. …”
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Multi-dimensional Data Visualisation using Mobile Augmented Reality
Published 2020“…Therefore, this algorithm uses AR to provide a multi-display solution for improved data visualisation after processing, summarising and classifying data. …”
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Effectiveness of silhouette rendering algorithms in terrain visualisation
Published 2002“…Silhouette Rendering Algorithms have been successfully used in various applications such as communicating shape and cartoon rendering.This paper explores how effective silhouette rendering algorithms could be used in terrain visualisation. …”
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Explainable artificial intelligence-based intuitionistic fuzzy network TOPSIS preference relation models for sukuk investment decisions
Published 2025“…Three explainable models were developed, namely, intuitionistic fuzzy network TOPSIS, intuitionistic fuzzypreference relation, and intuitionistic fuzzy network preference relation with a weighting algorithm. The properties of transparency were achieved through model design, while post-hoc explainability was addressed using visualisation, and the models were applied to sukuk data in selecting suitable investment alternatives. …”
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Visualisation System of COVID-19 Data in Malaysia
Published 2021“…This study aims to provide a system, using COVID-19 data as a sample to visualise and analyse cases, deaths, discharged ICU cases updates in Malaysia as a whole state wise of COVID-19 daily statistics. …”
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3D terrain visualisation for GIS: A comparison of different techniques
Published 2011“…The results of this paper will be of help to the users in identifying the best technique of terrain visualisation suitable for GIS data.…”
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Book Section -
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Visualisation System of COVID-19 Data in Malaysia
Published 2021“…This study aims to provide a system, using COVID-19 data as a sample to visualise and analyse cases, deaths, discharged ICU cases updates in Malaysia as a whole state wise of COVID-19 daily statistics. …”
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A case study : 2D Vs 3D parallel differential equation toward tumor cell detection on multi-core parallel computing atmosphere
Published 2010“…In order to detect tumour cells, 2D and 3D Partial Differential Equations (PDE) are considered and compared by using Multi-Core parallel computing atmosphere with visualisation, communication and data analysis. …”
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Dynamic modeling by usage data for personalization systems
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PREDICTION OF HFMD DISEASE OUTBREAK FROM TWITTER
Published 2019“…This is because both Naive Bayes and SVM are baseline algorithm used in text classification. In the end, a visualisation of HFMD Disease Map is presented to visualize the city that suffer HFMD outbreak using geo-located tweet that related with HFMD. …”
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Final Year Project Report / IMRAD -
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Multiple equations model selection algorithm with iterative estimation method
Published 2016“…Meanwhile, real data analysis using water quality index displays excellent accomplishments when compared to other selection procedures.Consequently, iterative feasible generalized least squares method is regarded as a more suitable estimation method in this automated selection.It can also be seen that simultaneous selections outperform the individual selections.This strategy by executing simultaneous selection with iterative estimation method is therefore proven to outclass in this analysis.…”
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Application of the bees algorithm to the selection features for manufacturing data
Published 2007“…Some of the features may contain irrelevant information caused by data redundancy or by noise. A “wrapper” feature selection method using the Bees Algorithm and Multilayer Perception (MLP) networks is described in this paper. …”
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Case Slicing Technique for Feature Selection
Published 2004“…CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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Secured agriculture sensor data based on end-to-end encryption using raspberry pi
Published 2025“…This project addresses these security concerns by developing a secure data collection and visualisation system using Raspberry Pi and Node-RED. …”
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Final Year Project / Dissertation / Thesis -
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Attribute related methods for improvement of ID3 Algorithm in classification of data: A review
Published 2020“…Results of the reviewed techniques show that attribute selection methods capable to resolve the limitations in ID3 algorithm and increase the performance of the method. …”
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Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi
Published 2019“…Experiments demonstrate and prove that the proposed EBPSO method produces better accuracy mining data and selecting subset of relevant features comparing other algorithms. …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…Experiments demonstrate that ensemble classifier learning method produces better accuracy mining data streams and selecting subset of relevant features comparing other single classifiers. …”
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