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...

A generalized dynamic fuzzy neural network (GDFNN) was created to estimate heavy metal concentrations in rice by integrating spectral indices and environmental parameters. Hyperspectral data, environmental parameters, and heavy metal content were collected from field experiments with different levels of heavy metal pollution (Cu and Cd). Input variables used in the GDFNN model were derived from...

— In this paper a new approach to model climatic variations in the Plio-Pleistocene is presented. In a recent reference, Rial in [1] introduced the working hypothesis that frequency modulation (FM) of the orbital eccentricity forcing may be an important source of the nonlinearities observed in the δO time series from deep-sea sediment cores. Two models are proposed based on the ANFIS (Adaptive ...

Structural damage can be identified by processing structural vibration response signals and excitation data, and thus the suitability of signal processing methods is essential to structural damage identification. To explore an intelligent signal processing method for structural damage identification, the paper integrated wavelet real-time filtering algorithm, Adaptive Neruo-Fuzzy Inference Syst...

objective: interest in the subject of creativity and its impacts on human life is growing extensively. however, only a few surveys pay attention to the relation between creativity and physiological changes. this paper presents a novel approach to distinguish between creativity states from electrocardiogram signals. nineteen linear and nonlinear features of the cardiac signal were extracted to d...