基于性别的癫痫患者焦点映射粗糙集分类

IF 1.1 4区计算机科学 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Malaysian Journal of Computer Science Pub Date : 2023-01-31 DOI:10.22452/mjcs.vol36no1.3

Muthukumar B, Murugan S, Bharathi B (Corresponding Author)

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引用次数: 0

摘要

本研究的目的是应用粗糙集的概念对癫痫患者的“喜欢”、“不喜欢”和“中性”思维导图决策进行分类。利用冥想、熟悉度、theta、注意力、欣赏、beta、脑力努力、delta、alpha和gamma等特征，计算了一种有效的基于粗糙集的癫痫患者精神状态分类方法。特征的重要性被认为是条件属性，预期情绪被认为是决策属性。为了分析特征的影响，计算了基数和基于粗糙集的近似。采用灰色关联分析(GRA)算法对患者决策进行喜欢、不喜欢或中立的分类。实验结果表明，基于粗糙集的近似方法对癫痫患者思维导图的分类准确率达到95%。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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CLASSIFICATION OF GENDER BASED FOCUS MAPPING FOR EPILEPSY PATIENTS USING ROUGH SETS

The objective of this work is to classify the mind mapping decisions “like”, “dislike” and “neutral” in Epilepsy patients by applying the concepts of rough sets. An effective rough set-based classification of mental status in epilepsy patients has been computed using the features such as meditation, familiarity, theta, attention, appreciation, beta, mental effort, delta, alpha and gamma. The significance of features is considered as conditional attributes and the expected mood is represented as decision attributes. To analyze the impact of the features, the cardinality and rough set-based approximation are computed. Grey Relational Analysis (GRA) algorithm is applied for classification of patient decision is either like or dislike or neutral. The experimental results on classification of mind mapping of epilepsy patients using rough set-based approximation yields 95% accuracy.

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来源期刊

Malaysian Journal of Computer Science COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, THEORY & METHODS

CiteScore

2.20

自引率

33.30%

发文量

审稿时长

7.5 months

期刊介绍： The Malaysian Journal of Computer Science (ISSN 0127-9084) is published four times a year in January, April, July and October by the Faculty of Computer Science and Information Technology, University of Malaya, since 1985. Over the years, the journal has gained popularity and the number of paper submissions has increased steadily. The rigorous reviews from the referees have helped in ensuring that the high standard of the journal is maintained. The objectives are to promote exchange of information and knowledge in research work, new inventions/developments of Computer Science and on the use of Information Technology towards the structuring of an information-rich society and to assist the academic staff from local and foreign universities, business and industrial sectors, government departments and academic institutions on publishing research results and studies in Computer Science and Information Technology through a scholarly publication. The journal is being indexed and abstracted by Clarivate Analytics'' Web of Science and Elsevier''s Scopus