Paper Key : IRJ************252
Author: Tambe Sakshi Rajendra
Date Published: 04 Apr 2024
Abstract
Investment strategies are successful in helping struggling businesses meet their desired financial goals. However, implementing these strategies poses challenges for startups and other early-stage organizations. This predicament could lead to various issues in achieving investment objectives, which could be highly detrimental. Furthermore, this situation could worsen if potential investors overlook excellent investment opportunities in innovative companies. Businesses heavily rely on initial funding, during which investors make significant investments crucial for future expansion. There's a notable lack of valuable research guiding investors on making precise investment recommendations. To address this gap, an interactive application has been developed, utilizing K Nearest Neighbor, Linear Regression, Artificial Neural Network, and Fuzzy Classification algorithms for investment-related suggestions. These suggestions have proven effective for both investors and registered startups, demonstrating satisfactory performance in facilitating informed decision-making.Keywords: K Nearest Neighbors, Linear Regression, Artificial Neural Networks, and Fuzzy Classification.