In this paper, evolution strategy is applied in order to improve the time series prediction accuracy of a Sugeno and Takagi type fuzzy inference system FIS. The presented approach...
When designing any type of fuzzy rule based system, considerable effort is placed in identifying the correct number of fuzzy sets and the fine tuning of the corresponding membersh...
Abstract--This study proposes an efficient self-evolving evolutionary learning algorithm (SEELA) for neurofuzzy inference systems (NFISs). The major feature of the proposed SEELA i...
This paper suggests an evolutionary approach to design coordination strategies, a key issue in distributed intelligent systems. We focus on competitive strategies in the form of f...
In this paper, a recurrent neural network based fuzzy inference system (RNFIS) for prediction is proposed. A recurrent network is embedded in the RNFIS by adding feedback connecti...