This paper presents an improved technique for accelerating the process of doing logic programming in discrete Hopfield neural network by integrating fuzzy logic and modifying activation function. Generally Hopfield networks are suitable for solving combinatorial optimization problems and pattern recognition problems. However Hopfield neural networks also face some limitations; one of the major ...

ii using them to find global minimum point of seven well-known benchmark functions commonly used in development of optimisation techniques development. The results show that all ABFAs achieve better accuracy and speed compared to those of SBFA. The ABFAs are then used in modelling and control of a single-link flexible manipulator system. This includes modelling (based on linear model structures...

Two new computing models, namely a fuzzy expert system and a hybrid neural network-fuzzy expert system for time series forecasting of electric load, are presented in this paper. The fuzzy-logic-based expert system utilizes the historical relationship between load and dry-bulb temperature, and predicts electric loads fairly accurately, 1-24 h ahead. In the case of the hybrid neural network-fuzzy...

Water level forecasting through fuzzy logic and artificial neural network approaches S. Alvisi, G. Mascellani, M. Franchini, and A. Bárdossy Dipartimento di Ingegneria, Università degli Studi di Ferrara, Italia Institut für Wasserbau, Universität Stuttgart, Deutschland Received: 29 May 2005 – Accepted: 13 June 2005 – Published: 22 June 2005 Correspondence to: S. Alvisi ([email protected]) © ...

-This paper presents a new and simple fuzzy neural network based on structured fuzzy logic processors. The modifications of the referential fuzzy logic processors provide the equality index. The major advantage of the proposed network is that the learning process is faster and it has the capability of self -determining the relative cardinality. The fast learning is due to incorporating the rece...

A new strategy in wind speed prediction based on fuzzy logic and artificial neural networks was proposed. The new strategy for fuzzy logic not only provides significantly less rule base but also has increased estimated wind speed accuracy when compared to traditional one. Meanwhile, applying the proposed approach to artificial neural network leads to less neuron numbers and less learning time p...

A general adaptation through 'exploration' approach for controlling discrete event systems is presented. In this approach optimal controllers for a few operating conditions are determined (exploration) and an on-line adaptation module is trained on this data for generalization. A machinerepair example is formulated to illustrate the general control method. The on-line adaptation mechanism is ap...

A neural network can approximate a function, but it is impossible to interpret the result in terms of natural language. The consolidation of neural networks and fuzzy logic in neurofuzzy models provides learning as well as readability. This paper aims at modeling the input-output relationship with fuzzy IF-THEN rules by using fuzzy clustering technique. The main difference between fuzzy cluster...

A neural network can approximate a function, but it is impossible to interpret the result in terms of natural language. The consolidation of neural networks and fuzzy logic in neurofuzzy models provides learning as well as readability. This paper aims at modeling the input-output relationship with fuzzy IF-THEN rules by using fuzzy clustering technique. The main difference between fuzzy cluster...