Search Results - (( using selection problem algorithm ) OR ( data visualisation using algorithm ))

Menu recommendation for Restoran Jannat Saba using Market Basket analysis / Dinie Sorfina Fathanah Kamarul Ariffin by Kamarul Ariffin, Dinie Sorfina Fathanah

“…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 by Rehman Ullah, Khan, Yin, Bee Oon, Ahmad Sofian, Shminan, Lee, Jun Choi, Chen, Jacqueline How Ting

“…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 by Che Mat, Ruzinoor, Visvalingam, Mahes

“…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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Visualisation System of COVID-19 Data in Malaysia by Rehman Ullah, Khan, NOR SYAZA, SYAMIMI, CLADIA SIMBUT, MAMBANG, IVY, THOMAS, TZI NI, WEE

“…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 by Ruzinoor, Che Mat, Mohamed Shariff, Abdul Rashid, Mahmud, Ahmad Rodzi, Pradhan, Biswajeet

“…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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Visualisation System of COVID-19 Data in Malaysia by Rehman Ullah, Khan, NOR SYAZA, SYAMIMI, CLADIA SIMBUT, MAMBANG, IVY, THOMAS, NI WEE, TZI

“…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 COMPARISON STUDY OF DATA CLUSTERING AND VISUALISATION TECHNIQUES WITH VARIOUS DATA TYPES by Ling, Chien

“…Clustering is used to identify the intrinsic grouping of a set of unlabelled data. …”
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A case study : 2D Vs 3D parallel differential equation toward tumor cell detection on multi-core parallel computing atmosphere by Islam, Md. Rajibul, Alias, Norma

“…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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The efficacy of personal computer (PC) AI image enhancer software on low and high contrast PA chest radiograph: an experimental study by Baharudin, Nurul Atiqah, Ahmad Zaiki, Farah Wahida

“…Methods: An experimental investigation was undertaken using five PC AI image enhancer programs to visualise the thoracic anatomy. …”
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Dynamic modeling by usage data for personalization systems by Aghabozorgi, S.R., Teh, Y.W.

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PREDICTION OF HFMD DISEASE OUTBREAK FROM TWITTER by Tay, Guo Hong

“…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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Formulating new enhanced pattern classification algorithms based on ACO-SVM by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…ACO originally deals with discrete optimization problem.In applying ACO for solving SVM model selection problem which are continuous variables, there is a need to discretize the continuously value into discrete values.This discretization process would result in loss of some information and hence affects the classification accuracy and seeking time.In this algorithm we propose to solve SVM model selection problem using IACOR without the need to discretize continuous value for SVM.The second algorithm aims to simultaneously solve SVM model selection problem and selects a small number of features.SVM model selection and selection of suitable and small number of feature subsets must occur simultaneously because error produced from the feature subset selection phase will affect the values of SVM model selection and result in low classification accuracy.In this second algorithm we propose the use of IACOMV to simultaneously solve SVM model selection problem and features subset selection.Ten benchmark datasets were used to evaluate the proposed algorithms.Results showed that the proposed algorithms can enhance the classification accuracy with small size of features subset.…”
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Secured agriculture sensor data based on end-to-end encryption using raspberry pi by Choo, Jia Huey

“…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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Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection by Tubishat, Mohammad, Idris, Norisma, Shuib, Liyana, Abushariah, Mohammad A.M., Mirjalili, Seyedali

“…An improved version of Salp Swarm Algorithm (ISSA) is proposed in this study to solve feature selection problems and select the optimal subset of features in wrapper-mode. …”
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Image visualisation and classification of MODIS/ASTER Airborne Simulator (MASTER) remotely sensed data for agricultural area by Teoh, Chin Chuang, Dr., Shattri, Mansor, Abdul Rashid, Mohamed Shariff, Noordin, Ahmad

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Dengue classification system using clonal selection algorithm / Karimah Mohd by Mohd, Karimah

“…Some popular intelligent techniques like Genetic Algorithm, Fuzzy Logic and Artificial Neural Network are often used by reasearcher to perform classifcation problems. …”
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Feature selection and model selection algorithm using incremental mixed variable ant colony optimization for support vector machine classifier by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…In order to enhance SVM performance, these problems must be solved simultaneously because error produced from the feature subset selection phase will affect the values of the SVM parameters and resulted in low classification accuracy.Most approaches related with solving SVM model selection problem will discretize the continuous value of SVM parameters which will influence its performance.Incremental Mixed Variable Ant Colony Optimization (IACOMV) has the ability to solve SVM model selection problem without discretising the continuous values and simultaneously solve the two problems.This paper presents an algorithm that integrates IACOMV and SVM.Ten datasets from UCI were used to evaluate the performance of the proposed algorithm.Results showed that the proposed algorithm can enhance the classification accuracy with small number of features.…”
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A Comparative Study on three Component Selection Mechanisms for Hyper-Heuristics in Expensive Optimization by Jia Hui Ong, Jason Teo

“…Numerous studies in optimization problems often lead to tailoring a specific algorithm to adapt to the problem instances, especially in expensive optimization problems. …”
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Diagnosis of eyesight using Improved Clonal Selection Algorithm (ICLONALG) / Nor Khirda Masri by Masri, Nor Khirda

“…This study aims to implement the classification algorithm using the Improved Clonal Selection Algorithm (ICLONALG) to classify the eyesight’s problems. …”
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Static and self-scalable filter range selection algorithms for peer-to-peer networks by Kweh, Yeah Lun

“…The research works were implemented by simulation in which it was used to identify the selection problem, implementation of the proposed algorithms and the measurement of the results. …”
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