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A multidimensional data descriptor tool based on fuzzy min max neural network algorithm

Fatin Nurjannah, Salauddin (2018) A multidimensional data descriptor tool based on fuzzy min max neural network algorithm. Faculty of Computer System & Software Engineering, Universiti Malaysia Pahang.

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Abstract

The purpose of this project is to introduce different techniques and methods that have been used before to analyze the data. The main objective is to build an data analytic tool for a multidimensional dataset. In this project, the technique that will be used is Fuzzy Min Max method. By using this method, the data visualization will displaying the minimum and maximum value in range of zero to one. In this project, it will be compare a few techniques and determine which techniques is the most suitable. The techniques is in the Neural Network which has a few popular techniques such as K-Nearest Neighbour Fuzzy Min Max, general Reflex Fuzzy Min Max to get some idea of methodologies, algorithm, techniques and concept of the whole existing project and research study. Besides that, in this paper, it will also compare three existing system such as Tableau Public, Qlikview and IBM InfoSphere Streams. They have been compare for their advantages and disadvantages. The implementation of Fuzzy Min Max Neural Network technique has been applied using Matlab Programming. Therefore, in this project, it will explain more about why I am using the Fuzzy Min Max method rather than other methods.

Item Type: Undergraduates Project Papers
Additional Information: Project Paper (Bachelors of Computer Science (Graphics And Multimedia Technology)) -- Universiti Malaysia Pahang – 2018, SV: DR. MOHAMMED FALAH MOHAMMED, e-Thesis
Uncontrolled Keywords: Data analytic tool; Fuzzy Min Max Neural Network; Matlab Programming
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty/Division: Faculty of Computer System And Software Engineering
Depositing User: Mrs. Sufarini Mohd Sudin
Date Deposited: 10 Dec 2019 01:56
Last Modified: 10 Dec 2019 01:56
URI: http://umpir.ump.edu.my/id/eprint/26778
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