A fuzzy decision system for money investment in stock markets based on fuzzy candlesticks pattern recognition

Naranjo, Rodrigo; Santos, Matilde

doi:10.1016/j.eswa.2019.05.012

Cited by 45 publications

(16 citation statements)

References 22 publications

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“…Similarly, the k-nearest neighbour classifier was used by Naranjo and Santos (2019) to design a new fuzzy forecasting system for stock markets. Escobar and Morales-Menendez (2017) present the learning process and pattern recognition strategy for a knowledge-based intelligent supervisory system; the main goal is to detect rare quality events through binary classification.…”

Section: Methods Of Pattern Classification and Feature Selection In The Management And Educationmentioning

confidence: 99%

Further Education, Its Methods and Selected Characteristics of Organisations: An Empirical Study of Their Association With Organisations Profitability

Pudil

Somol

Mikova

et al. 2021

Business, Management and Economics Engineering

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Purpose – The paper presents the results of the study based on a sample of 358 organisations that focuses on further education and training (FET) of their employees. It specifically investigates which specific educational methods and various characteristics of organisations are associated with their financial performance. Research methodology – The Dependency Aware Feature (DAF) selection method from statistical pattern recognition has been used to identify which of the 37 considered variables are most associated with the profitability indicators (ROA, ROCE, ROS). Findings – The profitability indices are significantly associated with some of the specific methods of FET. Organisations should pay attention particularly to instructing, coaching and mentoring. The results also confirm the importance of talent management for organisations to be successful. Research limitations – The examined sample consists solely of organisations operating in the Czech Republic. Shortly, we plan to extend the selection by including organisations from abroad. Practical implications – The study provides recommendations for HR managers for the goals they should focus on. Organisations should evaluate the impacts of FET; otherwise increasing investments in it may not have an effect. Originality/Value – The originality of the current study lies in using a new methodology based on machine learning and respecting complex mutual relations among variables.

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Section: Methods Of Pattern Classification and Feature Selection In The Management And Educationmentioning

confidence: 99%

Further Education, Its Methods and Selected Characteristics of Organisations: An Empirical Study of Their Association With Organisations Profitability

Pudil

Somol

Mikova

et al. 2021

Business, Management and Economics Engineering

View full text Add to dashboard Cite

show abstract

“…e above table shows that in the evaluation of intangible cultural value, the basic value of resources should be first analyzed in the comprehensive evaluation layer, followed by their quality status [23]. is is because the basic value and quality of resources are the basis and guarantee of intangible cultural development, and it is difficult to attract a large number of appreciators without excellent resources.…”

Section: Decision Support Systemmentioning

confidence: 99%

Innovative Development of Intangible Culture of Arts and Crafts in Artificial Intelligence Decision Support System

Liu

2022

Mobile Information Systems

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The Chinese nation has accumulated a lot of precious, rich, and wonderful material and intangible culture in its historical evolution, but these cultures are facing the problem of inheritance difficulties in the long term, and it is becoming more and more difficult to innovate. In order to solve these problems, this paper puts forward the innovative development of the intangible culture of arts and crafts based on artificial intelligence decision support system, with the purpose of studying cultural inheritance, regional brand hematopoiesis promotion, and organizational goal’s support for intangible culture. The method of this paper is to study the basic principles of artificial bee colony algorithms and decision support systems, and then evaluate the value of intangible culture. The purpose of this paper is to analyze the development of local intangible culture and innovation models based on local knowledge systems and confirm the influence of technological innovation on intangible culture so as to promote the sustainable development of intangible culture. This paper describes the present situation of intangible cultural innovation and then explores the innovative ways of intangible culture based on the experiment of cultural development of artificial intelligence. The experimental results show that after using the decision support method mentioned in this paper, the technical progress index of Jingdezhen porcelain culture has increased by 2.4%.

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“…A major challenge that most investors face in stock market is choosing the stock with the best price at the best time possible [7,31]. Fuzzy classification helps investors to make better and faster selection of stocks in the Stock Exchange market considering their capital and the risk of stocks [11,32]. This choice is made using technical or fundamental analysis [1,34,44].…”

Section: Introductionmentioning

confidence: 99%

Analysis and classification of companies on tehran stock exchange with incomplete information

et al. 2021

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Due to uncertainty and large number of companies in financial market, it has become difficult to choose the right stock to investments. Identifying and classifying stocks using fundamental criteria help investors to better understand the risks involved in selecting companies and better manage their own capital, thereby rapidly and accurately choose their preferred stock and make more secure profit. The main concern that capital market investors are facing difficulty to choosing the right stock despite the uncertainties in the market. Uncertainties in the market that lead to incomplete information are presented in this article to complete the reciprocal preference relation method. The purpose of this paper is to present a method for completing information to reduce the uncertainties in the market and finally classify companies in each industry based on fundamental criteria. The classification method used is acceptability / reject ability which is based on distance fuzzy analysis yields more accurate results. Finally, a case study on one of the most critical industries in Tehran Stock Exchange is presented to show the effectiveness of the proposed approach.

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A fuzzy decision system for money investment in stock markets based on fuzzy candlesticks pattern recognition

Cited by 45 publications

References 22 publications

Further Education, Its Methods and Selected Characteristics of Organisations: An Empirical Study of Their Association With Organisations Profitability

Further Education, Its Methods and Selected Characteristics of Organisations: An Empirical Study of Their Association With Organisations Profitability

Innovative Development of Intangible Culture of Arts and Crafts in Artificial Intelligence Decision Support System

Analysis and classification of companies on tehran stock exchange with incomplete information

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