An adaptive fuzzy inference neural network (AFINN) is proposed in this paper. It has self-construction ability, parameter estimation ability and rule extraction ability. The structure of AFINN is formed by the
For simplicity, let us take a type-0 fuzzy system. The complete neural network representing the fuzzy inference system is shown in Fig. 12.26. Let us very quickly re-visit the step-by-step working of the fuzzy inference system and re-formulate the problem in terms of a neural network. ...
The architecture of the neural network consists of the input vector, one hidden layer and output layer. Bayesian regularization is employed to obtain the effective number of neurons in the hidden layer. The input variables and target of the adaptive neuro-fuzzy inference system are the same as ...
The main objective of this study is the development of the adaptive neuro-fuzzy inference system (ANFIS) and an artificial neural network (ANN) for predicting the adsorption capacity in different operating conditions for different materials. Both models take into account the adsorbent type, adsorbent...
adaptive network fuzzy inference systemDeveloping a precise and accurate model of gold price is critical to assets management because of its unique features. In this paper, adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network (ANN) model have been used for modeling the gold ...
Asian Network for Scientific InformationJournal of Environmental Science & TechnologyMpallas L, Tzimopoulos C, Evangelides C (2011) Comparison between Neural Networks and Adaptive Neuro-fuzzy Inference System in Modeling Lake Kerkini Water Level Fluctuation Lake Manegement using Artificial Intelligence. J...
ANFIS uses the neural network training parameters to tune the parameters of the fuzzy inference system. The features that make ANFIS a commendable technique for achieving goals is: i. It defines the behaviour of a complex problem/system by refining the IF-ELSE rule. ii. It is easy to ...
In this paper the Neuro-Fuzzy system ANFIS (Adaptive Network Fuzzy Inference System)and its integration in the Stuttgart Neural Network Simulator (SNNS) is described. The rule-based knowledge base...doi:10.1007/978-3-322-86825-1_9Kais Brahim...
It contains two main elements: the adaptive neural network and fuzzy inference system. There are five logical blocks in a floating inference method. A fuzzifier transforms individual input numbers into fuzzy sets. In essence, this dynamic unit translates crisp inputs into linguistic meaning ...
Adaptive Neuro-Fuzzy Inference System(ANFIS) is a neural network system with one input and several outputs, which is got through achieving one step sugeno fuzzy system by the format of network. 自适应神经网络模糊推理系统(AdaptiveNeuro FuzzyInferenceSystem, ANFIS)是将Sugeno一阶模糊系统以网络的形式...