Fuzzy logic programs are a useful framework for handling uncertainty in logic programming; nevertheless, there is the need for modelling adaptation of fuzzy logic programs. In this paper, we first overview weighted fuzzy programs, which bring fuzzy logic programs and connectionist models closer together by associating significance weights with the atoms of a logic rule: by exploiting the existe...

This study presents the effects of project uncertainties on nonlinear time-cost tradeoff (TCT) profile of real life engineering projects by the fusion of fuzzy logic and artificial neural network (ANN) models with hybrid meta-heuristic (HMH) technique, abridged as Fuzzy-ANN-HMH. Nonlinear time-cost relationship of project activities is dealt with ANN models. ANN models are then integrated with ...

Artificial intelligent tools such as expert systems, artificial neural network and fuzzy logic support decision-making are being used in intelligent manufacturing systems. Success of intelligent manufacturing systems depends on effective and efficient utilization of intelligent tools. Weld residual stress depends on different process parameters and its prediction and control is a challenge to t...

It has been well established that neural networks provide a reasonable and powerful alternative to conventional classifiers. During the past few years there has been a large and energetic upswing in research efforts aimed at synthesizing fuzzy logic with neural networks. This combination of fuzzy logic and neural networks seems natural because two approaches generally attack the design of “inte...

A novel fuzzy-neural tree (FNT) is presented, where each tree node uses a Gaussian as a fuzzy membership or possibility distribution in place of sigmoidal function in conventional neural networks. Although neural networks with Gaussian activation functions as well as different types of cooperative neuro-fuzzy systems have been extensively described in the literature, the FNT presented in this p...

modeling of stream flow–suspended sediment relationship is one of the most studied topics in hydrology due to itsessential application to water resources management. recently, artificial intelligence has gained much popularity owing toits application in calibrating the nonlinear relationships inherent in the stream flow–suspended sediment relationship. thisstudy made us of adaptive neuro-fuzzy ...

ABSTRACT: In this study, adaptive neuro-fuzzy inference system, and feed forward neural network as two artificial intelligence-based models along with conventional multiple linear regression model were used to predict the multi-station modelling of dissolve oxygen concentration at the downstream of Mathura City in India. The data used are dissolved oxygen, pH, biological oxygen demand and water...

in common classical methods of cavity depth estimation through microgravity data, usually when a pre-geometrical model is considered for the cavity shape, the simple geometrical models of sphere, vertical cylinder and horizontal cylinder are commonly used. it is obviously an important fact that in real conditions the shapes of the cavities are not exactly sphere, horizontal cylinder or vertical...

In this paper, the fuzzy neural network is selected as the algorithm for data mining (DM), introducing the artificial neural network into the fuzzy logic by treating it as a computing tool, it is a networklized description form by using the artificial neural network as the membership function in a fuzzy system, fuzzy rules and extension principle. The fuzzy neural network (FNN) is selected as t...