in this paper, a recurrent fuzzy-neural network (rfnn) controller with neural network identifier in direct control model is designed to control the speed and exhaust temperature of the gas turbine in a combined cycle power plant. since the turbine operation in combined cycle unit is considered, speed and exhaust temperature of the gas turbine should be simultaneously controlled by fuel command ...

In this paper, we propose five data fusion schemes for the Internet of Things (IoT) scenario,which are Relief and Perceptron (Re-P), Relief and Genetic Algorithm Particle Swarm Optimization (Re-GAPSO), Genetic Algorithm and Artificial Neural Network (GA-ANN), Rough and Perceptron (Ro-P)and Rough and GAPSO (Ro-GAPSO). All the schemes consist of four stages, including preprocessingthe data set ba...

the paper deals with data envelopment analysis (dea) and artificial neural network (ann). we believe that solving for the dea efficiency measure, simultaneously with neural network model, provides a promising rich approach to optimal solution. in this paper, a new neural network model is used to estimate the inefficiency of dmus in large datasets.

The paper focuses on problems which arise when two different types of AI methods are combined in one design. The first type is rule based, rough set methodology operating is highly discretized attribute space. The discretization is a consequence of the granular nature of knowledge representation in the theory of rough sets. The second type is neural network working in continuous space. Problems...

This study applies a Back-Propagation Neural Network to the task of floristic land cover classification. The input data consists of the three LANDSAT TM bands 2, 4 and 7 and the GIS based environmental variables Aspect, Elevation, Catchment, Geology and Slope. This dataset covers a 225 square-km sub scene centred near the town of Kioloa, South East, Australia. The study area is complex compnsmg...

It goes without saying that a challenging quest for the construction of intelligent systems is realized through the development of hybrid information technologies and their vigorous and prudent exploitation. In a nutshell, what has emerged under the name of computational intelligence (CI) or soft computing is a well-orchestrated, highly synergistic consortium of technologies of neural networks,...

We present applications of rough set methods for feature selection in pattern recognition. We emphasize the role of the basic constructs of rough set approach in feature selection, namely reducts and their approximations, including dynamic reducts. In the overview of methods for feature selection we discuss feature selection criteria, including the rough set based methods. Our algorithm for fea...

This paper introduced the feature of distribution network and rough set theory. The application in power system was elaborated, such as on load forecasting, fault diagnosis, system-state analysis and data mining. Then given an illustration that using RS attribute reduction algorithm obtain the correlative factors in distribution system load forecasting. These factors were input vector of neural...