期刊名称：International Journal of Signal Processing, Image Processing and Pattern Recognition
印刷版ISSN：2005-4254
出版年度：2014
卷号：7
期号：5
页码：375-388
DOI：10.14257/ijsip.2014.7.5.32
出版社：SERSC
摘要：As one part of cultural enterprises, recently years have witnessed the development of Animation Enterprises. Even though the development of Animation Enterprises has become mature nowadays, there is still lack of quantitative understanding of Animation Enterprises. As one of the most valuable assets, goodwill quantifies the value of the survival and development of Animation Enterprises. An established 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. For example, the randomly determination of the initial state of the neural network leads to the possibility of converging to a local optimal point. Besides, the Animation enterprises cost of basic WNN is typically big and its convergence speed is relatively slow. To solve above challenge, we propose to improve WNN using Particle Swarm Optimization (PSO) algorithm. At the end, we conduct a case study on Heilongjiang Animation Enterprises to evaluate the performance of our proposed algorithm for goodwill measurement.
