The development of grain size during commercial thermomechanical processing of 6000 series aluminium alloy components has been investigated by combining physical experiments and modelling techniques. A range of grain structures was generated by varying both deformation temperature and heat treatment practice. The different deformation conditions were simulated by finite element modelling, which...

This study proposed a model-based robust fault detection (RFD) method using soft computing techniques. Robust detection of the possible realistic incipient faults of an industrial gas turbine engine in steady-state conditions is mainly centered. For residual generation a bank of Multi-Layer perceptron (MLP) models, is used, Moreover, in fault detection phase, a passive approach based on Modelli...

It is known that control signals from a fuzzy logic controller are determined by a response behavior of a controlled object rather than its analytical models. That implies that the fuzzy controller could yield a similar control result for a set of plants with a similar dynamic behavior. This idea leads to modeling of a plant with unknown structure by defining several types of dynamic behavior, ...

In this paper, we derive two techniques for the classification of multifrequency/multitemporal polarimetric SAR images, based respectively on a statistical and on a neural approach. Both techniques are especially designed to exploit the spatial structure of the observed scene, thus allowing more stable classification results. Such techniques are useful when looking at mediumto large-scale featu...

The main aim of this work is the determination aromaticity in biochar from easier accessible parameters (e.g., elemental composition). To end, two machine learning models, including adaptive neurofuzzy inference system (ANFIS) and least-squares support vector (LSSVM), were used to predict constant form 98 dataset gathered earlier reported sources. outputs statistical showed that LSSVM model has...

this paper presents the bio-inspired neurofuzzy based route selection system to avoid traffic congestion. The proposed neuro-fuzzy system selects the best multi-parameters direction between two desired nodes: source and the endpoint. This research practices a mixture of neuro-fuzzy logic and ant colony system (ACS) algorithm for the principal routing to fulfill all the preferred requirements of...

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 ...

Computerised processing of medical images can ease the search of the representative features in the images. The endoscopic images possess rich information expressed by texture. In this paper schemes have been developed to extract new texture features from the texture spectra in the chromatic and achromatic domains for a selected region of interest from each colour component histogram of images ...