Nowadays, there are sad statistics that about 90% of all startups have failed. That is why the development of methods and models for predicting the success of startup projects is significant.There is no research on using neuro-fuzzy systems for astartup success integrated assessment. This statement only em-phasizes the need to develop and implement such a system due to its undeniable relevance.Fuzzy systems are widespread in modern startup success forecasting models, but they have disadvantages like finding membership functions, the need for an expert to determine the rules and total adherence to the existing system rules. That iswhy the search for the possibilities to combine neural networks and fuzzy logic has become quite popular.Most of theexisting analysis and projects evaluation models use accurate data-based training, but it is not always possible to provide accurate startup data. The purpose of this research is to support decision-making in the creation of startup projects through the development of an automated information system for a comprehensive assessment of the startup success.A neuro-fuzzy information technology model for startup success level integrated assessment has been developed, consist-ing of 3 main subsystems. The data processing subsystem,subsystem of neuro-fuzzy assessment for projects, subsystem for searching for successful startup projects and selecting strategies for further startup development. The complex information system will allow you to get a success assessment, an individually formed strategy for project development, and use the experience of similar startups in the development.
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