The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In this study, a classification model for predicting human judgment accuracy in Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) was developed using the decision tree model. The training data for decision tree learning was obtained from the questionnaire responses of 22 participants in various fields. Experimental results showed the proposed decision tree model is able to explore...
Since Song and Chissom proposed the fuzzy time series in 1993, many previous studies have proposed variant fuzzy time series models to deal with uncertain and vague data. A drawback of these models is that they do not consider appropriately the weights of fuzzy relations. This paper proposes an adoptive fuzzy time series model to solve above problems. It develops weighted fuzzy rules by calculating...
For more than three decades, Box and Jenkins' Auto-Regressive Integrated Moving Average (ARIMA) technique has been one of the most widely used linear models in time series forecasting. However, it is well documented that many software failure observations are nonlinear and ARIMA is a general univariate model developed based on the assumption that the time series data being predicted are linear. Therefore,...
Based on grey GM(1, 1) of the forecast for engine wear trend, the Markov chains is presented, so the grey GM(1, 1) and Markov chain model for predicting the engine wear trend is built in this paper. The model is felled together two kind of inherent quality of time list data organically since evolvement rules is mined from time list data and random response is attained through state transfer probability...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.