The methods of ordinary least-squares regression (OLSR), fuzzy regression (FR), and adaptive network fuzzy inference system (ANFIS) are compared in inferring operating rules for a reservoir operations problem. Dynamic programming (DP) is used to provide the input-output data set to be used by OLSR, FR, and ANFIS models. The coefficients of an FR model are found by solving a linear programming (...

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 ...

some applications are critical and must designed fault tolerant system. usually voting algorithm is one of the principle elements of a fault tolerant system. two kinds of voting algorithm are used in most applications, they are majority voting algorithm and weighted average algorithm these algorithms have some problems. majority confronts with the problem of threshold limits and voter of weight...

Weather prediction is an ever challenging area of investigation for scientists. The Adaptive Neuro-Fuzzy Inference System (ANFIS) has been widely used for modeling different kinds of nonlinear systems including rainfall forecasting. Adaptive Neuro-Fuzzy Inference Systems (ANFIS) combines the capabilities of Artificial Neural Networks (ANN) and Fuzzy Inference Systems (FIS) to solve different ki...

Worms spread by scanning for vulnerable hosts across the Internet. In this paper we report a comparative study of three classification schemes for automated portscan detection. These schemes include a simple Fuzzy Inference System (FIS) that uses classical inductive learning, a Neural Network that uses back propagation algorithm and an Adaptive Neuro Fuzzy Inference System (ANFIS) that also emp...

This paper addresses the problem of rate control for Available Bit Rate (ABR) service class in Asynchronous Transfer Mode (ATM) networks. An adaptive neurofuzzy mechanism based on Adaptive Network Fuzzy Inference System (ANFIS) for allocating rates in ABR service has been proposed and compared with the fuzzy technique called as Fuzzy Explicit Rate Marking (FERM). To achieve this, a neurofuzzy A...

Introduction: Epilepsy is a clinical syndrome in which seizures have a tendency to recur. Sodium valproate is the most effective drug in the treatment of all types of generalized seizures. Finding the optimal dosage (the lowest effective dose) of sodium valproate is a real challenge to all neurologists. In this study, a new approach based on Adaptive Neuro-Fuzzy Inference System (ANFIS) was pre...

This paper introduces the application of the hybrid approach Adaptive Neuro-Fuzzy Inference System (ANFIS) for fault classification and diagnosis in industrial actuator. The ANFIS can be viewed either as a fuzzy inference system, a neural network or fuzzy neural network (FNN). This paper integrates the learning capabilities of neural network to the robustness of fuzzy systems in the sense that ...

A supervisory Adaptive Network‐based Fuzzy Inference System (SANFIS) is proposed for the empirical control of a mobile robot. This controller includes an ANFIS controller and a supervisory controller. The ANFIS controller is off‐line tuned by an adaptive fuzzy inference system, the supervisory controller is designed to compensate for the approximation error bet...

Cancer research is one of the major research areas in the medical field. Adaptive Neuro Fuzzy Interference System is used for the classification of Cancer. This algorithm compared with proposed algorithm of Adaptive Neuro Fuzzy Interference system with Runge Kutta learning method for the best classification of cancer. It is one of the better techniques for the classification of the cancer. The ...