Neuro-Fuzzy Modeling of an Intelligent Decision Support System for Complex Assessment of Startups’ Success Level

Abstract

The subject of research delves into the utilization of neuro-fuzzy systems, specifically examining their application and efficacy in the context of startup project assessment. The object of research is the comprehensive assessment of startup projects. The purpose of this work is to explore the capabilities of neuro-fuzzy systems in providing a nuanced and accurate assessment of startup projects. To achieve this purpose, an analysis of existing methodologies for predicting startup success was conducted, with a special focus on artificial intelligence methods. This is followed by an in-depth exploration of the neuro-fuzzy approach as a viable alternative to address the complexities inherent in startup valuation. The research then focuses on the thorough selection of technologies, concluding with the software implementation of the system. The scientific novelty of this research resides in its pioneering application of neuro-fuzzy systems for the prediction of startup success, aiming to overcome the limitations of existing AI methodologies and providing a more nuanced and flexible approach for startup assessment. The qualification work has a dual practical value. Stakeholders, including sponsors and businessmen, get a reliable tool for making informed decisions about the feasibility of financing a startup project, while founders get a mechanism for preliminary assessment of their projects, which helps them plan and improve them at an early stage.