Fuzzy Inspired Intelligent Interaction Model for Business Sector using Statistical Analysis

Elmitwally, Nouh (2024) Fuzzy Inspired Intelligent Interaction Model for Business Sector using Statistical Analysis. In: The 10th International Conference on Next Generation Computing (ICNGC 2024), November 20-23, 2024, Holy Angel University, Angeles City, Philippines. (In Press)

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Abstract

Technological breakthroughs in Artificial Intelligence (AI) have led to the growth of human-like computers that can work independently and replicate a cognitive activity. The progression and interest among managers, researchers, and the general public have aroused interest in many industries, and significant corporate sectors are spending massively to profit gain through technology with the development of business interaction models. As information technology (IT) platforms become more advanced, and business activities become more autonomous, there is an increasing demand for business managers to better impact company operations and how they correspond with organizational goals. Machine learning and fuzzy logic design have lately been highlighted as recent innovations. Machine learning is an artificial intelligence approach that may enable smarter and more intelligent decision-making outcomes. In comparison, Fuzzy Logic Design (FLD) is a procedure that provides inferences or solutions from an ambiguous situation. In this research article, a fuzzy-inspired intelligent interaction model for the business sector is proposed, which utilizes a fuzzy logic design approach while enabling users to understand functions from a business standpoint and organize them related to the business targets, identify key indicators and carry out the necessary intelligent analysis on them to recognize causal factors of unforeseen metric values and enhance efficiency to improve business leadership.

Item Type:	Conference or Workshop Item (Paper)
Dates:	Date Event 20 November 2024 Accepted
Subjects:	CAH11 - computing > CAH11-01 - computing > CAH11-01-01 - computer science
Divisions:	Faculty of Computing, Engineering and the Built Environment > College of Computing
Depositing User:	Nouh Elmitwally
Date Deposited:	11 Feb 2025 11:11
Last Modified:	11 Feb 2025 11:11
URI:	https://www.open-access.bcu.ac.uk/id/eprint/16139