Pattern search learning is known for simplicity and faster convergence. However, one of the downfalls of this learning is the premature convergence problem. In this paper, we show how we can avoid the possibility of being trapped in a local pit by the introduction of stochastic value. This improved pattern search is then applied on a recurrent type neuro-fuzzy network (ANFIS) to solve time seri...

Point Estimation Using the Kullback-Leibler Loss Function and MML p. 87 Single Factor Analysis in MML Mixture Modelling p. 96 Discovering Associations in Spatial Data An Efficient Medoid Based Approach p. 110 Data Mining Using Dynamically Constructed Recurrent Fuzzy Neural Networks p. 122 CCAIIA: Clustering Categorical Attributes into Interesting Association Rules p. 132 Selective Materializati...

A dynamic fuzzy neural network for short-term load forecasting of the Greek power system is proposed, and an hourly based prediction whole year performed. DBD-FELF (Dynamic Block-Diagonal Fuzzy Electric Load Forecaster) consists rules with consequent parts that are networks internal recurrence. These have a hidden layer, which pairs neurons feedback connections between them. The overall model p...

Abstract In this paper, a novel hybrid technique is proposed for transient stability analysis on grid connected Wind-Diesel-PV system. The methodology combination of the dwarf mongoose optimization algorithm (DMO) and recalling enhanced recurrent neural network (RERNN) named DMO-RERNN. main purpose work to consider various elements system according different conditions. voltage profile using un...

The fuzzy systems and control are regarded as the most widely used application of fuzzy logic systems in recent years (Jang, 1993; John & Coupland, 2007; Lin & Lee, 1006; Mendel, 2001; Wang, 1994). The structure of traditional fuzzy system models that is characterized by using type 1 fuzzy sets, which are defined on a universe of discourse, map an element of the universe of discourse onto a pre...

The walking beam furnace (WBF) plays a critical role in a steel production factory, and has complex nonlinear dynamic behaviour. Thus, using the conventional physical principles to build a model of the process leads to a time-consuming modeling procedure and when the number of operating set-points in walking beam furnace increases the conventional modeling problem difficultly will be solved, in...

This paper proposes a high-precision intelligent adaptive backstepping control system (HPIABCS) for the position control of permanent-magnet synchronous motor (PMSM) servo drive. The HPIABCS incorporates an ideal backstepping controller, a dynamic recurrent-fuzzy-wavelet-neural-network (DRFWNN) uncertainty observer and a robust H∞ controller. First, a backstepping position controller is designe...