Proceedings of the 2nd International Conference on Advances in Computer Science and Engineering (CSE 2013)

A Venture Capital Assessment Model based on the Genetic Neural Network

Authors
Tieying Liu, Yuting Fan, Xinzhu Xu
Corresponding Author
Tieying Liu
Available Online July 2013.
DOI
https://doi.org/10.2991/cse.2013.27How to use a DOI?
Keywords
venture capital; venture evaluation; benefit valuation,;index system
Abstract
With the rapid development of economy, there are greater challenges in Venture Capital. In the face of the venture project selecting, scientific evaluation of investment venture has been an important issue in venture investment, and it directly influences the success or failure of investment. In this paper, we analyzed the venture evaluation index system, and apply the improved genetic algorithm (GA) to processes of the neural network construction and training, and then we set up an evaluation model of genetic algorithm and artificial neural network. In order to solve problems of venture -benefit assessment in the venture investment, we presented a method which is under the dynamic factors influence. And use of it, investors can make scientific decision according to the preference of venture and benefit. The experimental results show that the model we presented can effectively improve evaluation efficiency, and increase the rationality and correctness of venture evaluation system.
Open Access
This is an open access article distributed under the CC BY-NC license.

Download article (PDF)

Proceedings
2nd International Conference on Advances in Computer Science and Engineering (CSE 2013)
Part of series
Advances in Intelligent Systems Research
Publication Date
July 2013
ISBN
978-90786-77-70-3
DOI
https://doi.org/10.2991/cse.2013.27How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Tieying Liu
AU  - Yuting Fan
AU  - Xinzhu Xu
PY  - 2013/07
DA  - 2013/07
TI  - A Venture Capital Assessment Model based on the Genetic Neural Network
BT  - 2nd International Conference on Advances in Computer Science and Engineering (CSE 2013)
PB  - Atlantis Press
UR  - https://doi.org/10.2991/cse.2013.27
DO  - https://doi.org/10.2991/cse.2013.27
ID  - Liu2013/07
ER  -