Drought forecasting plays an important role in the planning and management of water resources systems. In this paper, a hybrid wavelet and adaptive neuro-fuzzy inference system (WANFIS) is proposed for drought forecasting. The WANFIS model was developed by combining two methods, namely a discrete wavelet transform and adaptive neuro-fuzzy inference system (ANFIS) model. To assess the effectiven...

Handwritten character recognition is an area with many applications. Over the last decade much research has gone into algorithms to develop systems, which accurately convert images of handwriting to text. At the same time, neuro-fuzzy classification models have been researched and proven to solve complex problems. In this paper, two popular models, Adaptive Neuro-Fuzzy Inference System (ANFIS) ...

This paper presents an adaptive neuro-fuzzy inference system (ANFIS) for USD/JPY exchange rates forecasting. Previous work often used time series techniques and neural networks (NN). ANFIS can be used to better explain solutions to users than completely black-box models, such as NN. The proposed neurofuzzy rule based system applies some technical and fundamental indexes as input variables. In o...

In this paper we presented an architecture and basic learning process underlying in fuzzy inference system and adaptive neuro fuzzy inference system which is a hybrid network implemented in framework of adaptive network. In real world computing environment, soft computing techniques including neural network, fuzzy logic algorithms have been widely used to derive an actual decision using given i...

Distributed flexible AC- transmission system (D-FACTS) is a recently advanced FACTS device with high flexibility and smaller size. The DPFC can control power flow in transmission lines, regulate bus voltages and it can also enhance stability margin in power grids. Adaptive-neural network-based fuzzy inference system (ANFIS) combines features of artificial neural network and fuzzy controller. Th...

Purpose Respiratory motion prediction is a chaotic time series prediction problem. In this study, respiratory motion predictability from 12 traces from breast cancer patients is examined by using Adaptive Neuro-Fuzzy Inference System (ANFIS) and Interval Type-2 Non Singleton Fuzzy System (IT2NSFLS). Methods Free breathing data curves were obtained from Real Time Position Management system (RPM ...

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 work is an attempt to illustrate the usage and effectiveness of soft computing techniques in the estimation and control of multi input and multi output systems. This paper focuses on neuro-fuzzy system ANFIS (Adaptive Neuro Fuzzy Inference system). An Adaptive Network based Fuzzy Interference System architecture extended to cope with multivariable systems has been used. The performance of ...

Fuzzy inference systems have been applied in recent years in various medical fields due to their ability to obtain good results featuring white-box models. Adaptive Neuro-Fuzzy Inference System (ANFIS), which combines adaptive neural network capabilities with the fuzzy logic qualitative approach, has been previously used in modelling survival of breast cancer patients based on patient groups de...