GUI for System Identification using NARX and NARMAX models

A Python Package For System Identification Using NARMAX Models

An active inference agent based on expected free energy minimization with a nonlinear autoregressive exogenous model.

Code, figures, animations for a NARX-EFE based agent.

Air-quality forecasting in Belgium using Deep Neural Networks, Neuroevolution and distributed Island T​ranspeciation

Level controle in the Facotry IO. Code written in LAD, SCL in TIA Portal

This repository contains code for energy forecasting using multilayer neural networks (MLPs) with autoregressive (AR) and nonlinear autoregressive exogenous (NARX) approaches. The goal is to predict the next-day electricity consumption for a specific case study, utilizing real dataset from a real-life organization.

The project uses a nonlinear autoregressive exogenous (NARX), model to make time-series prediction on data obtained from drive cycling testing on buses

Final project for the Time Series course on two different time series, one on the evolution of the BTC price (series with trend) and the other on the Indian weather (series with trend and seasonality).

Neural Network Lecture Projects.

Explore the double-descent phenomena in the context of system identification. Companion code to the paper (https://arxiv.org/abs/2012.06341):

A python multi-variate time series prediction library working with sklearn

Dual-Stage Attention-Based Recurrent Neural Net for Time Series Prediction

Performed a nonlinear model identification using both the FROE method with polynomial NARX models and feedforward neural networks.

Deep Learning using Neural Network Toolbox + Finance Portfolio Selection with MorningStar

Nonlinear autoregressive exogenous model library. NarxSim ported to U++.