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An accurate estimate of wind speed and direction is important for many application domains including weather prediction, smart grids, and e.g. traffic management. These two environmental variables depend on a number of factors and are linked together. Evolutionary fuzzy rules, based on fuzzy information retrieval and genetic programming, have been used to solve a variety of real–world regression and...
Industrial plants use many different sensors for processes monitoring and controlling. These sensors generate huge amount of data. These data should be used for improving of the quality of semi and final products in each factory. In this paper, we describe processing of two different datasets acquired from a steel-mill factory using three different methods SVM, Fuzzy Rules and Bayesian classification...
Methods based on fuzzy sets and fuzzy logic have proved to be efficient data classifiers and value estimators. This study presents an application of evolutionary evolved fuzzy rules based on the concept of extended Boolean queries to a multi-class data mining problem. Fuzzy rules are used as symbolic classifiers machine-learned from the data and used to label data samples and predict the value of...
Traffic accidents represent a major problem threatening peoples lives, health, and property. Traffic behavior and driving in particular is a social and cultural phenomenon that exhibits significant differences across countries and regions. Therefore, traffic models developed in one country might not be suitable for other countries. Similarly, attributes of importance, dependencies, and patterns found...
Renewable energy sources are becoming a significant part of todays energy mix. The unstable production of many renewable energy sources including photovoltaic and wind power plants puts increased demands on power transmission systems and on the power grid as a whole. Soft computing methods can contribute to the prediction of electric energy production of renewable resources and therefore to the reliability...
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