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.
Unintended lane departure accidents are due to driver's inattention, incapacitation, and drowsiness. Lane departure warning systems have been developed to enhance traffic safety by predicting/detecting driving situation and alerting drivers to avoid or mitigate traffic accidents. This paper explores effectiveness of a three-layer perceptron neural network in predicting an unintentional lane departure,...
For many years, neural networks have gained gigantic interest and their popularity is likely to continue because of the success stories of deep learning. Nonetheless, their applications are mostly limited to static and not temporal patterns. In this paper, we apply time warping invariant Echo State Networks (ESNs) to time-series classification tasks using datasets from various studies in the UCR archive...
Most of the real systems including a large number of physical, physiological and biochemical signals exhibit non-stationarity or time-varying behavior. Electroencephalogram is brain signal that allows gaining the understanding of the complex inner mechanisms of the brain and abnormal brain waves and plays a vital role in diagnosis of different brain disorders. We have carried out a study for nonlinear...
A new soft computing method called the parameter-free simplified swarm optimization (SSO)-based artificial neural network (ANN), or improved SSO for short, is proposed to adjust the weights in ANNs. The method is a modification of the SSO, and seeks to overcome some of the drawbacks of SSO. In the experiments, the iSSO is compared with five other famous soft computing methods, including the backpropagation...
The prediction of rare events is a pressing scientific problem. Events such as extreme meteorological conditions, may aggravate human morbidity and mortality. Yet, their prediction is inherently difficult as, by definition, these events are characterised by low occurrence, high sampling variation, and uncertainty. For example, earthquakes have a high magnitude variation and are irregular. In the past,...
In this paper we develop two methods that are able to analyze and recognize patterns in time series. The first model is based on analytic programming (AP), which belongs to soft computing. AP is based as well as genetic programming on the set of functions, operators and so-called terminals, which are usually constants or independent variables. The second one uses an artificial neural network that...
Stock price fluctuation in stock markets is a very important issue in financial researches. However, the information in stock markets of China is too much to analysis. Fractal theory is an important modern branch of nonlinear science. Neural network has a strong nonlinear approximation ability and self-organizing, adaptive features. Based on fractal theory, the Shanghai integrated index are chosen...
The goal of this project is thus to experiment with ANNs and to evaluate performance of ANN models in studying stock price patterns in time by attempting to predict future results of a time-series by simply studying patterns in the time-series of stock prices. In this project we have instantiated the proposed Neural Network using the stock prices of Iran Tractor Manufacturing Company during two years...
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.