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...

In this paper, several neural network and statistical learning approaches are proposed that learn to make human like decisions for the job assignment problem of the US Navy. Comparison study of Feedforward Neural Networks (FFNN), Adaptive Neuro-Fuzzy Inference System (ANFIS), Support Vector Machine (SVM) and Adaptive Bayes (AB) classifier with Generalized Estimation Equation (GEE) is provided. ...

In this paper, multi user detection in Code Division Multiple Access (CDMA) was realized with an adaptive neuro-fuzzy inference system (ANFIS) and the bit error rate (BER) performance was compared with the performances of the matched filter and a neural network receiver. Increment of the number of the active users and the receiving various user signals at the receiver input stage in different p...

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...

— 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...