Prediction Model Adaptation Thanks to Control Chart Monitoring - Application to Pollutants Prediction

Philippe Thomas, William Derigent, Marie-Christine Suhner

2014

Abstract

Indoor air quality is a major determinant of personal exposure to pollutants in today’s world since people spend much of their time in numerous different indoor environments. The Anaximen company develops a smart and connected object named Alima, which can measure every minute several physical parameters: temperature, humidity, concentrations of COV, CO2, formaldehyde and particulate matter (pm). Beyond the measurement aspect, Alima presents some data analysis feature named ‘predictive analytics’, whose primary aim is to predict the evolution of indoor pollutants in time. In this article, the neural network (NN) model,embedded in this object and designed for pollutant prediction, is presented. In addition with this NN model, this article also details an approach where batch learning is performed periodically when a too important drift between the model and the system is detected. This approach is based on control charts.

Paper Citation

in Harvard Style

Thomas P., Derigent W. and Suhner M. (2014). Prediction Model Adaptation Thanks to Control Chart Monitoring - Application to Pollutants Prediction . In Proceedings of the International Conference on Neural Computation Theory and Applications - Volume 1: NCTA, (IJCCI 2014) ISBN 978-989-758-054-3, pages 172-179. DOI: 10.5220/0005075501720179

in Bibtex Style

@conference{ncta14,
author={Philippe Thomas and William Derigent and Marie-Christine Suhner},
title={Prediction Model Adaptation Thanks to Control Chart Monitoring - Application to Pollutants Prediction},
booktitle={Proceedings of the International Conference on Neural Computation Theory and Applications - Volume 1: NCTA, (IJCCI 2014)},
year={2014},
pages={172-179},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005075501720179},
isbn={978-989-758-054-3},
}

in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Neural Computation Theory and Applications - Volume 1: NCTA, (IJCCI 2014)
TI - Prediction Model Adaptation Thanks to Control Chart Monitoring - Application to Pollutants Prediction
SN - 978-989-758-054-3
AU - Thomas P.
AU - Derigent W.
AU - Suhner M.
PY - 2014
SP - 172
EP - 179
DO - 10.5220/0005075501720179