Earticle

초록

영어

Recently years have witnessed the development of cultural enterprises. As one of the most valuable intangible assets, goodwill valuation for cultural enterprises has gained a lot of attention. An efficient method is to use Wavelet Neural Network (WNN) model for learning the predicted value of goodwill given a set of indicators. However, there are some issues of the basic WNN model. On one hand, the randomly determination of the initial state of the neural network leads to the possibility of converging to a local optimal point. To solve this problem, we propose to employ Genetic Algorithm (GA) for optimizing the initial parameters before model training. On the other hand, the training cost of basic WNN is typically big and its convergence speed is relatively slow. To accelerate the convergence speed, we introduce Levenberg-Marquardt (LM) algorithm for training. Besides, we conduct experiment to evaluate the performance of our proposed GA-LM-WNN algorithm.

목차

Abstract
 1. Introduction
 2. Related Work
 3. Modeling
 4. Experiments
 5. Conclusion
 References

키워드

저자

• Han Dong Ping [ School of management, Harbin Institute of Technology, Wei Hai, Shandong, China ]
• Bao Di [ School of management, Harbin Institute of Technology, Harbin, Heilongjiang, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Hybrid Information Technology

• 간기

  격월간

• pISSN

  1738-9968

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605