Prediction of Financing Goal of Crowdfunding Projects
Author(s) -
Haifeng Li,
Xiaohua Chen,
Yuejin Zhang,
Mo Hai
Publication year - 2018
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2018.10.225
Subject(s) - computer science , support vector machine , artificial neural network , set (abstract data type) , logistic regression , range (aeronautics) , renminbi , finance , artificial intelligence , machine learning , business , materials science , composite material , programming language , exchange rate
In this paper, we employ three classification methods, that is, the Logistic Regression(LR), the back propagation(BP) neural network and the support vector machine(SVM) to predict the result of reward crowdfunding projects. The results show that BP neural network has the best performance. In addition, we use the BP neural network to achieve a reasonable range of financing goal of crowdfunding projects. The experiment shows that the current maximum financing goal for reward crowdfunding is about 1 million RMB, which helps the sponsors to set a reasonable amount of financing target under the current reward crowdfunding market.
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