Abstrad A Fuzzijed TSK-type Recurrent Neiiral Fuzzy Network (FTRNFN) for handling furry temporal information is proposed in this paper. The inputs and oulputs of FTRNFN are fuzzy pattems represented by Gaussian or isosceles triangular membership functions. In structure, FTRNFN is a recurrent fizzy nefwork constructed from a series of recurrent fuzzy +then rules with TSK-t)pe Consequent parts. T...

Recurrent fuzzy neural networks (FNNs) have been widely applied to dynamic system processing problems. However, most recurrent FNNs focus on the use of type-1 fuzzy sets. This paper proposes a Mamdani-type recurrent interval type-2 FNN (M-RIT2FNN) that uses interval type-2 fuzzy sets in both rule antecedent and consequent parts. The reason for using interval type-2 fuzzy sets is to increase net...

A method for response integration in modular neural networks with type-2 fuzzy logic for biometric systems p. 5 Evolving type-2 fuzzy logic controllers for autonomous mobile robots p. 16 Adaptive type-2 fuzzy logic for intelligent home environment p. 26 Interval type-1 non-singleton type-2 TSK fuzzy logic systems using the hybrid training method RLS-BP p. 36 An efficient computational method to...

this paper aims to evaluate the impact of several indices of market structure including entry to barrier, economies of scale and concentration degree on 140 active industries using the digit. accordingly, we apply three methods including cost disadvantages ratio ( ), herfindahl–hirschman concentration index ( ) and comanor and willson criterion in order to assess the economies of scale and usin...

Mạng nơ-ron mờ hồi quy (recurrent fuzzy neural networks - RFNNs) đã được nhiều nghiên cứu kiểm chứng thành công trên mô phỏng. Tuy nhiên, các thực nghiệm điều khiển thiết bị vẫn còn hạn chế. Thậm chí có quan điểm cho rằng với tốc độ huấn luyện trực tuyến chậm, RFNNs khó đảm bảo yêu cầu truyền thông tín hiệu. Nghiên này tiến hành kỹ thuật giám sát dùng hệ ổn định lưu lượng chất lỏng RT020 của hã...

A new definition of Adaptive Neuro Fuzzy Systems is presented in this paper for the identification of unknown nonlinear dynamical systems. The proposed scheme uses the concept of Adaptive Fuzzy Systems (AFS) operating in conjunction with High Order Neural Network Functions (F-HONNFs). Since the plant is considered unknown, we first propose its approximation by a special form of an adaptive fuzz...

We assess a neural-based method for fuzzy astronomical seeing prediction, based on known meteorological variables at the same time-point. This multiple regression, termed nowcasting 10, 11], will allow the modern telescopes to be preset, a few hours in advance, in the most suited instrumental mode. The data used are extensive meteorological and seeing measurements partly made at Cerro Paranal i...

the paper analyses issues leading to errors in graphic object classifiers. thedistance measures suggested in literature and used as a basis in traditional, fuzzy, andneuro-fuzzy classifiers are found to be not suitable for classification of non-stylized orfuzzy objects in which the features of classes are much more difficult to recognize becauseof significant uncertainties in their location and...