Title of article :
Modelling Crowdfunding Ensemble Learning Prediction
Author/Authors :
Saeidi Aghdam, Mehran Department of Eentrepreneurship - Qazvin Branch - Islamic Azad University - Qazvin, Iran , Alamtabriz, Akbar Department of Industrial management - Shahid beheshti University - Tehran, Iran , Bahiraie, Alireza Department of Mathematics - Semnan University - Semnan, Iran , Sadeghi, Ahmad Department of Geography - Faculty of Earth Sciences - Shahid Beheshti University - Tehran, Iran
Abstract :
Crowdfunding is a new technology-enabled innovative process that is changing
the capital market space. Internet-based applications, particularly those related to
Web 2.0, have had a significant impact on sectors of society such as education,
business, and medicine. The goal of this research is to fill a gap in the literature
on mathematical modelling and prediction of ensemble learning in order to evaluate
crowdfunding projects. The Mathematical model determines the cost of
funding for the entrepreneur and the return investors will receive per period. A
correct financial model is essential in order to keep all three stakeholders involved
in the long term. The results show the designed model improved performance in
predicting the evaluation of success or failure of Crowdfunding projects.
Keywords :
Prediction , Mathematical , Crowdfunding , Entrepreneurship
Journal title :
Advances in Mathematical Finance and Applications
