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.
Stock market prediction has attracted much attention from academia as well as business. However, it is a challenging research topic, in which many advanced computational methods have been proposed, but not yet attained a desirable and reliable performance. This study proposes a new method for stock market prediction, which adopts the Long Short-Term Memory (LSTM) neural network and incorporates investor...
Vegetation index derived from remote sensing measurement servers as the significant reference for crop growing monitor and agricultural disaster forecasting. Vegetation index forecasting at long lead time and appropriate spatial scale is critical for decision making to mitigate the impacts from agricultural disaster. In previous studies, vegetation index forecasting has been studied and implemented...
Financial forecasting is the basis for budgeting activities and estimating future financing needs. Applying machine learning and data mining models to financial forecasting is both effective and efficient. Among different kinds of machine learning models, kernel methods are well accepted since they are more robust and accurate than traditional models, such as neural networks. However, learning from...
This paper presents a novel method to predict bankruptcy, using a Genetic Programming (GP) based approach called Evolving Decision Rules (EDR). In order to obtain the optimum parameters of the classifying mechanism, we use a data set, obtained from the US Federal Deposit Insurance Corporation (FDIC). The set consists of limited financial institutions' data, presented as variables widely used to detect...
In this paper, we investigate the statistical properties of fluctuations of Chinese stock index. According to the theory of artificial neural network, a stochastic time effective function is introduced in the forecasting model of the index in the present paper, which gives an improved neural network - the stochastic time effective neural network model. In this model, a promising data mining technique...
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.