In this paper, we propose novel recurrent architectures for Genetic Programming (GP) and Group Method of Data Handling (GMDH) to predict software reliability. The effectiveness of the models is compared with that of well-known machine learning techniques viz. Multiple Linear Regression (MLR), Multivariate Adaptive Regression Splines (MARS), Backpropagation Neural Network (BPNN), Counter Propaga...

This paper presents an innovative hybrid approach for online recognition of handwritten symbols. The approach is composed of two main techniques. Firstly, fuzzy rules are used to extract a meaningful set of features from a handwritten symbol, and secondly a recurrent neural network uses the feature set as input to recognise the symbol. The extracted feature set is a set of basic shapes capturin...

An adaptive neural fuzzy (NF) controller is developed in this paper for active vibration suppression in flexible structures. A recurrent identification network (RIN) is developed to adaptively identify system dynamics of the plant. A novel recurrent training (RT) technique is suggested to train the RIN so as to optimize nonlinear input-output mapping and to enhance convergence. The effectivenes...

We present a comparative study of electricity consumption predictions using the SARIMAX method (Seasonal Auto Regressive Moving Average eXogenous variables), HyFis2 model (Hybrid Neural Fuzzy Inference System) and LSTNetA (Long Short Time series Network Adapted), hybrid neural network containing GRU (Gated Recurrent Unit), CNN (Convolutional Network) dense layers, specially adapted for this cas...

We give an overview of some of the fundamental issues found in the realm of recurrent neural networks. We use theoretical models of computation to characterize the representational, computational, and learning capabilitities of recurrent network models. We discuss how results derived for deterministic models can be generalized to fuzzy models. We then address how these theoretical models can be...

A novel Nonlinear Consequent Part Recurrent Type-2 Fuzzy System (NCPRT2FS) is presented for the modeling of renewable energy systems. Not only does this paper present a new architecture type-2 fuzzy system (T2FS) identification and behavior prognostication an experimental solar cell set wind turbine, but also, it introduces exquisite technique to acquire optimal number membership functions (MFs...

Human qualitative judgments are often characterized by uncertainty and predictability. Decision-makers tend to be more confident in making linguistic decisions than crisp value judgments. MEREC is capable of achieving relative objective weights several conflicting criteria. This paper contains two parts, first, the extension method fuzzy circumstances based on terms which a parabolic measure ha...