A multi-attribute decision-making fusion model for stock trading with customizable investor personality traits in a picture fuzzy environment

计算机科学 托普西斯 证券交易所 模糊逻辑 人工智能 机器学习 数据挖掘 排名(信息检索) 遗传算法 运筹学 数学 财务 经济
作者
Shio Gai Quek,Ganeshsree Selvachandran,Angie Yih Tsyr Wong,Fiona Wong,Weiping Ding,Ajith Abraham
出处
期刊:Applied Soft Computing [Elsevier BV]
卷期号:147: 110715-110715 被引量:2
标识
DOI:10.1016/j.asoc.2023.110715
摘要

In this paper, a fuzzy logic-based machine learning (ML) algorithm is introduced. This proposed ML algorithm accepts picture fuzzy sets (PFS) as the fuzzified input and incorporates genetic algorithm (GA) during the training process. The proposed ML algorithm is then incorporated into two well-known decision-making methods, namely the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Evaluation Based on Distance from Average Solution (EDAS). These two decision-making methods and the proposed ML algorithm are then applied to solve a multi-attribute decision-making (MADM) problem related to the evaluation and ranking of public listed companies based on their stock performance, in accordance with investors’ personalities. The actual daily closing stock price of five public listed companies from the big market capitalization (Big Cap) category traded in the Kuala Lumpur Stock Exchange (KLSE) for a period of 10 years is used as the datasets for this study. Monte Carlo simulation is used to verify the accuracy of the results. In addition, a comprehensive comparative study of some recent PFS-based decision-making methods in the existing literature and the proposed methods is conducted, and all the typical instances of the investors’ personalities are observed. The results obtained through this comparative study corroborates the results obtained via the proposed methods, and this proves the effectiveness of the proposed methods. The differences in the results obtained via the different methods are analyzed and discussed, and this again proves that the results obtained via the proposed methods are effective and consistent with the judgments of human experts.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
番茄小超人2号完成签到 ,获得积分10
1秒前
qwe发布了新的文献求助10
4秒前
笨笨忘幽完成签到,获得积分10
4秒前
美丽完成签到 ,获得积分10
9秒前
CLTTT完成签到,获得积分10
12秒前
居里姐姐完成签到 ,获得积分10
14秒前
现实的曼安完成签到 ,获得积分10
16秒前
sunzhengkui完成签到,获得积分10
17秒前
MrChew完成签到 ,获得积分10
24秒前
凌露完成签到 ,获得积分0
26秒前
秋秋糖xte完成签到,获得积分10
27秒前
hsrlbc完成签到,获得积分10
28秒前
活力的邴完成签到 ,获得积分10
34秒前
活力的邴关注了科研通微信公众号
39秒前
fanssw完成签到 ,获得积分10
39秒前
忧虑的静柏完成签到 ,获得积分10
44秒前
46秒前
耿教授发布了新的文献求助10
52秒前
小猪完成签到 ,获得积分10
56秒前
1分钟前
SciGPT应助科研通管家采纳,获得10
1分钟前
背后海亦发布了新的文献求助10
1分钟前
慕青应助沈万熙采纳,获得10
1分钟前
BCKT完成签到,获得积分10
1分钟前
badbaby完成签到 ,获得积分10
1分钟前
方圆完成签到 ,获得积分10
1分钟前
1分钟前
无奈的书琴完成签到 ,获得积分10
1分钟前
1分钟前
数乱了梨花完成签到 ,获得积分10
1分钟前
背后海亦发布了新的文献求助10
1分钟前
ACMI完成签到,获得积分10
1分钟前
不秃燃的小老弟完成签到 ,获得积分10
2分钟前
朱婷完成签到 ,获得积分10
2分钟前
小白完成签到 ,获得积分10
2分钟前
谢陈完成签到 ,获得积分10
2分钟前
从容的水壶完成签到 ,获得积分10
2分钟前
xy完成签到 ,获得积分10
2分钟前
千玺的小粉丝儿完成签到,获得积分10
2分钟前
CHENXIN532完成签到,获得积分10
2分钟前
高分求助中
A new approach to the extrapolation of accelerated life test data 1000
Cognitive Neuroscience: The Biology of the Mind 1000
Technical Brochure TB 814: LPIT applications in HV gas insulated switchgear 1000
Immigrant Incorporation in East Asian Democracies 600
Nucleophilic substitution in azasydnone-modified dinitroanisoles 500
不知道标题是什么 500
A Preliminary Study on Correlation Between Independent Components of Facial Thermal Images and Subjective Assessment of Chronic Stress 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 3968559
求助须知:如何正确求助?哪些是违规求助? 3513358
关于积分的说明 11167340
捐赠科研通 3248714
什么是DOI,文献DOI怎么找? 1794453
邀请新用户注册赠送积分活动 875065
科研通“疑难数据库(出版商)”最低求助积分说明 804664