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.
The present work includes the temporal modeling of the oviposition activity of the Aedes aegypti mosquito, a vector of viral diseases such as Dengue, Chicungunya and Zika, based on time series of data extracted from earth observation satellite images. Unlike previous works, Machine Learning techniques that are capable of capturing nonlinear relationships between variables, such as artificial neural...
Local scour around bridge abutment is a time-dependent complex phenomenon encountered world-wide. It is difficult to establish a general empirical model that can be applied to all abutment conditions. In this paper, Radial basis function (RBF) Network has been used to predict the maximum scour depth around bridge abutment. An appropriate model is identified using experimental data from literature...
Stock market forecasting has attracted a lot of research interests in previous literature, and recent studies have shown that artificial neural networks (ANN) method achieved better performance than traditional statistical ones. ANN approaches have, however, suffered from difficulties with generalization, producing models that can overfit the data. This paper employs a relatively new machine learning...
To balance the precision and generality of the prediction model, a new path loss artificial neural network (ANN) prediction model for railway environments is presented firstly in this paper. The utilization of back propagation ANN can overcome some disadvantages of such conventional prediction models as empirical and deterministic models. The training data is based on the electric field strength measurements...
Combining particle swarm optimization algorithm (PSO) with cultural algorithm (CA), a new cultural particle swarm optimization algorithm (CPSO) is proposed by this paper. Then, Both CPSO and PSO are used to resolve the optimization problems of five widely used test functions, and the results show that CPSO has better optimization performance than PSO. Next, CPSO is applied to train artificial neural...
This study tries to examine the impacts of emotional learning based fuzzy inference system (ELFIS) on completion time of projects. For the project management team, on time delivery within budget is a fundamental and important factor that highlights the importance of estimating the completion time of a project during its execution. This study implies four soft computing methods which are artificial...
In the present work an attempt is made to develop a clinical decision support system (CDSS) using the pathological attributes to predict the fetal delivery to be done normal or by surgical procedure. The pathological tests like blood sugar (BR), blood pressure (BP), resistivity index (RI) and systolic-diastolic (S/P) ratio will be recorded at the time of delivery. All attributes lie within a specific...
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.