Type-2 Fuzzy Expert System Approach for Decision-Making of Financial Assets and Investing under Different Uncertainty

Janková, Zuzana; Dostál, Petr

doi:10.1155/2021/3839071

Cited by 12 publications

(7 citation statements)

References 46 publications

(46 reference statements)

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“…An interceptor can be responsible for executing one or more ORB services [14]. Logically speaking, in one customer and one item, an interceptor can be inserted into the call path between standard objects.…”

Section: Hardware Designmentioning

confidence: 99%

Design of University Financial Information System Based on Data Mining Technology and IoT

Guo¹

2022

Wireless Communications and Mobile Computing

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As China’s information construction level keeps getting better and higher education keeps getting better, new rules and regulations are being made and put into place. These new rules and regulations require colleges and universities to have comprehensive budget management, dynamic fund management, scientific forecast analysis and performance assessment, and the integration of campus cards and digital campuses. At present, the financial management concept and financial management software used by colleges and universities have been relatively lagging behind, which cannot adapt to the needs of current information and career development. Therefore, the financial information system of colleges and universities based on data mining technology is designed. The hardware part is designed with CORBA interceptor, B/S structure, and SQL converter. The software part first figures out what kind of financial information platform is needed. Then, using data mining technology, it builds a financial information model. Finally, it designs the functional module of financial information technology and builds the financial index system for colleges and universities. The results of the system tests show that the designed financial information system works well and has some use value.

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Section: Hardware Designmentioning

confidence: 99%

Design of University Financial Information System Based on Data Mining Technology and IoT

Guo¹

2022

Wireless Communications and Mobile Computing

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“…For a long time, the construction of a financial decision support system has been the concern of scholars. The financial decision support system realizes scientific and effective financial decision-making by comprehensively managing the upstream and downstream financial information of the enterprise, integrating the actual financial situation of the enterprise in the whole process, and integrating internal and external information [ 1 – 3 ]. In recent years, with the vigorous development of computer technology, the concepts of digitization and intelligence have emerged in the management information system [ 4 ], [ 5 ].…”

Section: Introductionmentioning

confidence: 99%

Design of Digital and Intelligent Financial Decision Support System Based on Artificial Intelligence

Jia

Wang

Tian

et al. 2022

Computational Intelligence and Neuroscience

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The quality of financial decision-making is very important to the future development of an enterprise, but it is often affected by the completeness of useful information for decision-making and the subjective factors of decision makers, and is often unstable. With the development of computer technology, the financial decision support system came into being, which improved the quality of financial decision to some extent. However, although the existing financial decision support system has achieved dataization to a certain extent, it still faces problems such as artificial leadership, insufficient intelligence, and poor decision-making efficiency, and cannot fully meet the needs of decision-makers. The explosion of artificial intelligence technology in recent years has provided potential improvements to financial decision support systems. In this article, we conduct a detailed analysis of the deficiencies in the current financial decision support system, build the mechanism and implementation path of the financial decision support system under artificial intelligence, and design a digital and intelligent financial decision support system. At the same time, we apply the proposed financial decision support system to the financial practice of X enterprise. Through the questionnaire survey, it is found that through the comprehensive application of artificial intelligence technology, the new system has a higher degree of intelligence than the existing system, and its construction can effectively improve the timeliness and accuracy of financial decision-making, while reducing the cost of financial decision-making. It is conducive to promoting the integration of management accounting and financial accounting.

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“…Comparing Sugeno´s and Mamdani´s defuzzification process, the Mamdani´s is more computationally efficient, as it uses a weighted average or weighted sum of a few data points rather than compute a centroid of a two-dimensional area (Chaudhari, 2014). Janková & Dostál (2021) justifies the usage of the fuzzy inference system of the Mamdani type for the model construction to support investment decisions in Exchange-Traded Funds as it operates better with unstructured or poorly structured input data than the Sugeno type. Amaral et al (2019) propose the use of Computational Intelligence algorithms to predict cryptocurrencies values based on historical values.…”

Section: Entrepreneurship and Sustainability Issuesmentioning

confidence: 99%

A fuzzy evaluation model of manufacturing machinery in terms of sustainable business

Hašková¹,

Vochоzka²,

Kučera³

2023

JESI

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The inclusion of sustainability criteria in the investment decision processes requires application of tools that consider the vague nature of sustainable characteristics. Fuzzy approach can process the vagueness of sustainability measures. The aim of the paper is to develop a suitable model of the fuzzy assessment of investment alternatives measured by Sustainability Utility Index. Its scheme is described methodologically as a three-stage system of multi-criteria ex-ante evaluation. An algorithmic conception of the system is performed at its third stage by a "fuzzy processor". The fuzzy model is applied to the task of the optimal type of building machinery selection in view of the cost and sustainable criteria. The results enable the manager to optimize his/her decision, who aims to minimize the investment and operation costs of the building machinery. Compared to the fuzzy approach based on Mandani´s system, our model avoids several complications associated with the semantics of fuzzy implications in various fuzzy logics, it is more user friendly and easily algorithmized. This model is thus suitable to apply not only in corporate sphere but also in areas of ecology, sociology, economics. The limits of the fuzzy system are twofold -on the general level the fuzzy systems lack the ability to learn and memorize; determining or tuning a suitable membership function and fuzzy rules is not always clear. The challenge is first to test the model in the corporate sphere and second to acquaint potential users with this computationally undemanding fuzzy procedure.

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Type-2 Fuzzy Expert System Approach for Decision-Making of Financial Assets and Investing under Different Uncertainty

Cited by 12 publications

References 46 publications

Design of University Financial Information System Based on Data Mining Technology and IoT

Design of University Financial Information System Based on Data Mining Technology and IoT

Design of Digital and Intelligent Financial Decision Support System Based on Artificial Intelligence

A fuzzy evaluation model of manufacturing machinery in terms of sustainable business

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