Credit-risk evaluation decisions are important for the ®nancial institutions involved due to the high level of risk associated with wrong decisions. The process of making credit-risk evaluation decision is complex and unstructured. Neural networks are known to perform reasonably well compared to alternate methods for this problem. However, a drawback of using neural networks for credit-risk eva...

0198-9715/$ see front matter 2008 Elsevier Ltd. A doi:10.1016/j.compenvurbsys.2008.12.001 * Corresponding author. Tel.: +357 2289 2270; fax: E-mail addresses: [email protected] (S. Christod (A. Deligianni), [email protected] (P. Aslani), ceepaa4@ The efficient and organized management of public utility networks is of paramount importance to a network’s viability and reliable functioning. One of...

This paper focuses on the development of intelligent controllers for use in a process of enzyme recovery from pineapple rind. The proteolytic enzyme bromelain (EC 3.4.22.4) is precipitated with alcohol at low temperature in a fed-batch jacketed tank. Temperature control is crucial to avoid irreversible protein denaturation. Fuzzy or neural controllers offer a way of implementing solutions that ...

In this paper the model of hybrid power system is developed. It comprises two thermal power generation system with Photovoltaic generation system (PV), wind turbine, fuel cell, aqua electrolyzer and battery storage system. To maintain the preferred frequency and power exchange with the neighboring system in the hybrid power system is the objective of Automatic Generation Control (AGC). The devi...

A neurofuzzy methodology is presented for motion planning in semi-autonomous mobile robots. The robotic automata considered are devices whose main feature is incremental learning from a human instructor. Fuzzy descriptions are used for the robot to acquire a repertoire of behaviors from an instructor which it may subsequently refine and recall using neural adaptive techniques. The robot is endo...

During the last years, the fuzzy set theory was one of the most innovative,active and fruitful areas of research for applications, especially in the field of industrial processes. The aim of this brief introduction is to give some ideas about the foundations of the fuzzy system: defintions, semantics and applications. We will deal also with the relation with Artificial Neural Network (ANN) and ...

A neuro-fuzzy system has been developed to model the behaviour of a fast ferry. The sources of the available knowledge are the physical laws of the vertical dynamics of the craft, and some experimental and simulated data of the ship performance in regular waves. The non-linear model has been obtained by applying adaptive neurofuzzy inference. It is focus on the vertical motion of the craft, bot...

A new approximation to the dynamics of neocortex, preserving essential functions but not the microstructure, is presented. Local feature spaces are used to replace neurodynamics of neural cell assemblies in categorization, approximation and generalization processes. A global workspace (mind space), resulting from cooperation among local feature spaces, facilitates memory-based reasoning. Implem...

â  abstract: in this paper, artificial neural network (ann) was used for modeling the nonlinear structure of a debutanizer column in a refinery gas process plant. the actual input-output data of the system were measured in order to be used for system identification based on root mean square error (rmse) minimization approach. it was shown that the designed recurrent neural network is able to pr...

in this paper, we describe our implementation of an interior point algorithm for large scale systems. first we identify system with small and medium methods convex optimization, then we use interior point method for identification. finally we offer an interior point method that uses nonlinear cost function and see that we achieve a good trade-off between error and cpu time. actually, in this pa...