文章基本信息

标题：A Modified Wavelet Neutral Network Model for Measuring Goodwill
本地全文：下载
作者：Han Dong Ping ; Bao Di
期刊名称：International Journal of Hybrid Information Technology
印刷版ISSN：1738-9968
出版年度：2014
卷号：7
期号：4
页码：201-212
DOI：10.14257/ijhit.2014.7.4.17
出版社：SERSC
摘要：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.
关键词：Goodwill; Wavelet Neural Network