The summer season of 2003 in Continental Portugal was by far the worst in what respects both to the number of forest fires and the amount of burnt area. In the present work, burnt area monitoring was performed using NOAA/AVHRR imagery by means of a neuro-fuzzy (ANFIS) algorithm that was applied on an operational basis to the surface of the country. Validation of obtained results was performed b...

Gas turbines are currently a popular power generation technology in countries with access to natural gas resources. However they are very complex systems the operation of which at peak performance is challenging. This paper proposes the use of a hybrid approach based on an Adaptive Neuro-Fuzzy Inference System (ANFIS) for the control of the speed and the exhaust temperature of a gas turbine. Th...

Pattern search learning is known for simplicity and faster convergence. However, one of the downfalls of this learning is the premature convergence problem. In this paper, we show how we can avoid the possibility of being trapped in a local pit by the introduction of stochastic value. This improved pattern search is then applied on a recurrent type neuro-fuzzy network (ANFIS) to solve time seri...

In the presented study, by using 0, 10, 20, 30, 40, 50 and 60 gr sodium hexametaphospathe (NaPO3) suspensions were prepared for hydrometer tests. At the end of the tests, particle diameter of the soil were calculated for each hydrometer reading time (0, 1, 2, 5, 10, 15, 30, 60, 120 and 260 min.). By using ANFIS (Adaptive Neuro-Fuzzy Infirence System) a model was developed to predict of the part...

The aims of this research are to study application of high power ultrasound in preparation of stable oil-in-water emulsion. The effect of pH, ionic strength, pectin, Guar gum, lecithin, egg yolk, and xanthan gum as well as the time of sonication, temperature and viscosity of oil-water mixture on the specific surface area and size of droplets, and creaming index of the emulsion samples was inves...

The prediction of elastic modulus is one of the fundamental facts of structural engineering studies. The performance of adaptive neuro-fuzzy inference system (ANFIS) for predicting the elastic modulus of normaland high-strength concrete was investigated. Results indicate that the proposed ANFIS modeling approach outperforms the other given models in terms of prediction capability. According to ...

The aim of this work is to investigate how ANFIS modelling of the chloride permeability of concrete can contribute to the sustainable development. Therefore, to have an opinion about service lives of concrete structures, especially the reinforced ones. Thus, some mixture properties and the rapid chloride permeability test results of different types of concretes obtained from a previous study ar...

In this study, stiffness modulus parameters of asphalt concrete were determined experimentally for different temperature and exposure times. The stiffness modules were calculated according to Nijboer stiffness module. Basic physical properties and the quantity of bitumen of asphalt core samples were designated for determining the stiffness modules. The samples were exposed to 17 C (reference te...

The investigation of the effects of cracks or similar weaknesses on the load carrying capacity of structural elements such as columns, beams and shells is an important problem in civil, mechanical, earthquake and aerospace engineering. In this paper, adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network (ANN)model have been successfully used for the buckling analysis of sl...

One of the most popular data mining areas, which estimate future trends of data, is classification. This research is dedicated to predict Iranian passenger train delay with high accuracy over Iranian railway network. A hybrid method based on neuro-fuzzy inference system and Two-step clustering is used for this purpose. The results indicate that the hybrid method is superior over the other commo...