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From a new view of financial distress concept drift, this paper attempts to put forward a new method for dynamic financial distress prediction modeling based on slip time window and multiple support vector machines (SVMs). A new algorithm is designed to dynamically select the proper time window to handle concept drift, and then a dynamic classifier selection method is used to build a combined model...
Auditing practices nowadays have to cope with an increasing number of fraudulent financial statements. Data mining techniques can facilitate auditors in accomplishing the task of detection of fraudulent financial statements (FFS). Considering the character of FFS, this paper designs a FFS detection model based on Naïve Bayes classifier. To perform the experiment, we choose 44 FFS according to the...
This paper focuses on the development of knowledge model for a prediction of air cargo offload. A knowledge model is a model containing a set of knowledge via rules that has been obtained from mining certain amount of data. These rules might help the management in major decision making such as setting up new strategy. In this study, an intelligent technique for data mining called a rough set theory...
This paper establishes a speaker-independent pronunciation recognition and assessment system with 673 words for mandarin Chinese under the background of a Chinese learning system framework. The recognition part is based on HTK using HMM (Hidden Markov Models) and improved in the aspect of acoustic model. Making use of the recognition results and the log-likelihood obtained from the Viterbi coding,...
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