JOURNAL ARTICLE
Arithmetic Optimization Algorithm with Adaptive Neuro-Fuzzy Interference System for Predicting Financial Crisis.
Published In: International Journal of Neutrosophic Science (IJNS), 2024, v. 23, n. 4. P. 426 1 of 3
Database: Applied Science & Technology Source Ultimate 2 of 3
Authored By: Kouki, Fadoua 3 of 3
Abstract
Financial technology (Fintech) is paramount in driving advanced technologies, economies, society, and several other sectors. Smart Fintech is the new-generation Fintech, primarily stimulated and endowed by compuational technology. Smart Fintech syndicates DSAI and renovates economies and finance for dynamic, smart, customized, automated services and systems, economies and financial companies, and the industry. The strength and development of the country's economies are assessed by the correct forecasting. Financial crisis prediction (FCP) has the substantial consequence on the economies. Previous studies mainly emphasise statistical, DL, and ML methodologies for predicting the financial well-being of the business. Therefore, this article develops a new Arithmetic Optimization Algorithm with Adaptive Neuro-Fuzzy Interference System (AOA-ANFIS) technique for Predicting Financial Crisis. The presented AOA-ANFIS technique aims to predict the presence of financial crises or not. The model incorporates three major elements: Arithmetic Optimization Algorithm (AOA) for feature selection, Adaptive Neuro-Fuzzy Inference System (ANFIS) as the classification algorithm, and Bat Optimization Algorithm (BOA) for parameter tuning. The AOA feature selection model effectively detects the important attributes from a large proportion of financial indicators, augmenting the model's prediction capability while decreasing computational difficulty. Subsequently, the ANFIS classifier exploits the features selected for capturing the intricate non-linear relations intrinsic in financial data, permitting accurate crisis calculation. Additionally, the BOA parameter tuning model augments the ANFIS model's parameters, ensuring robustness and optimum performance. Experimental outcomes on varied financial databases validate the higher efficiency of the AOAANFIS technique over underlying processes, demonstrating its effectiveness in forecasting financial crises with great reliability and precision. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:International Journal of Neutrosophic Science (IJNS). 2024/04, Vol. 23, Issue 4, p426
- Document Type:Article
- Subject Area:Business and Management
- Publication Date:2024
- ISSN:26926148
- DOI:10.54216/IJNS.230435
- Accession Number:180872184
- Copyright Statement:Copyright of International Journal of Neutrosophic Science (IJNS) is the property of American Scientific Publishing Group and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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