教師資料查詢 | 類別: 會議論文 | 教師: 張應華 Ying-hua Chang (瀏覽個人網頁)

標題:INCORPORATING ARTIFICIAL NEURAL NETWORKS AND EVOLUTION STRATEGIES ON FINANCIAL DISTRESS RULES EXTRACTION
學年101
學期2
發表日期2013/07/07
作品名稱INCORPORATING ARTIFICIAL NEURAL NETWORKS AND EVOLUTION STRATEGIES ON FINANCIAL DISTRESS RULES EXTRACTION
作品名稱(其他語言)
著者Chang, Ying-Hua; Meng, Jui-Hsien
作品所屬單位淡江大學資訊管理學系
出版者
會議名稱2013 International Conference on Business and Information
會議地點Bali, Indonesia
摘要Business environments have been changed for years and more complicated than before. There are more impacts and many difficulties to companies because of financial distress. In order to reduce the impact, it is important to find out the causes of financial distress, and give alert to companies before it get distressed. There were studies that use basic financial analysis,
or single data-mining method exploring causes of financial distress. This study based on dynamic financial states, and finds the characteristics and rules of financial distress. This study combines Back-propagation Artificial Neural Networks (BPN) and Evolution Strategies (ES), extracts rules of financial distress, and incorporates with the results of Markov process analysis, in order to develop an optimized financial-distress alert model.
This study utilizes supervised learning networks to evaluate the risk of financial
distress of the companies, and find out the rules of financial distress by adding the prior evaluated results to evolution strategies.
關鍵字Financial distress;Financial alert;Back-propagation Artificial neural network
語言英文
收錄於
會議性質
校內研討會地點
研討會時間20130707~20130709
通訊作者
國別印尼
公開徵稿
出版型式
出處Proceedings of International Conference on Business and Information
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