Nature-inspired metaheuristics for optimization have proven successful, due to their fine balance between exploration and exploitation of a search space. This balance can be further refined by hybridization. In this paper, we conduct experiments with some of the most promising nature-inspired metaheuristics, for assessing their performance when using them to replace backpropagation as a learnin...

Adaptation of network weights using LevenbergMarquardt (LM) training algorithm was proposed as a mechanism to improve the performance of Artificial Neural Networks (ANN) in modeling the Tennessee Eastman (TE) chemical process reactor. A Neural Network of the AutoRegressive, eXternal (NNARX) input model was developed. Four sub-models for the TE reactor were built. They are: the reactor level, th...

u(t−1) u(t−2) y(t−1) y(t−2) y(t) This note contains important information on how the present toolbox is to be installed and the conditions under which it may be used. Please read it carefully before use. The note should be sufficient for being able to make the essential portion of the toolbox functions work properly. However, to enhance performance a number of functions have been rewritten in C...

The idea of using Feed-Forward Neural Networks (FFNNs) as regression functions for Nonlinear AutoRegressive eXogenous (NARX) models, leading to models herein named NARXs (NNARXs), has been quite popular in the early days machine learning applied nonlinear system identification, owing their simple structure and ease application control design. Nonetheless, few theoretical results are available c...

Gait event detection is important for diagnosis and evaluation. This is a challenging endeavor due to subjectivity, high amount of data, among other problems. ANFIS (Artificial Neural Fuzzy Inference Systems), ARX (Autoregressive Models with Exogenous Variables), OE (Output Error models), NARX (Nonlinear Autoregressive Models with Exogenous Variables) and models based on NN (neural networks) we...

This paper aims to discuss and analyze the potentialities of Recurrent Neural Networks (RNN) in control design applications. The main families RNN are considered, namely Nonlinear AutoRegressive eXogenous, (NNARX), Echo State (ESN), Long Short Term Memory (LSTM), Gated Units (GRU). goal is twofold. Firstly, survey recent results concerning training that enjoy Input-to-State Stability (ISS) Incr...

This paper presents a block oriented nonlinear dynamic model suitable for online identification.The model has the well known Hammerstein architecture where as a novelty the nonlinear static part is represented by a B-spline neural network (BSNN), and the linear static one is formalized by an auto regressive exogenous model (ARX). The model is suitable as a feed-forward control module in combina...

Naturally ventilated tropical greenhouse is classified as a complex system because it involves with nonlinear process and multivariable system. The purpose of this study is to determine the mathematical model of NVTG climates to in order to describe and predict the dynamic behavior of temperature and humidity inside NVTG for development of its control system. The modeling of the system is divid...