Employing Grey Model forecasting GM(1,1) to historical medical sensor data towards system preventive in smart home e-health for elderly person

Abstract : Introducing new methods to enhance health services for elderly persons has become the main objective of Smart Home researchers. One of the most important issues that they have dealt with is the application of forecasting models used to predict states of elderly persons. In fact, our approach focuses on some critical health parameters (blood pressure, pulse, etc ) over 40 days. In this paper, we have applied the forecasting Grey Model GM(1,1) on data collected in the smart home MavHome Project. We have also compared the system performances obtained to predict sensor datawhile using the Grey model with those provided while applying the Box-Jenkins ARIMA as a conventional forecasting model. The simulation results show that the Grey Model is more efficient than the Box-Jenkins ARIMA as it has resulted in more accurate forecasting values.
Type de document :
Communication dans un congrès
The 12th International Wireless Communications & Mobile Computing Conference, Sep 2016, Paphos, Cyprus. Proceedings of the 12th International Wireless Communications & Mobile Computing Conference, 2016, Proceedings of the 12th International Wireless Communications & Mobile Computing Conference
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https://hal.inria.fr/hal-01313304
Contributeur : Tayeb Lemlouma <>
Soumis le : lundi 9 mai 2016 - 17:46:15
Dernière modification le : mercredi 29 novembre 2017 - 15:42:22

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  • HAL Id : hal-01313304, version 1

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Rim Jouini, Tayeb Lemlouma, Karima Maalaoui, Leila Azzouz Saidane. Employing Grey Model forecasting GM(1,1) to historical medical sensor data towards system preventive in smart home e-health for elderly person. The 12th International Wireless Communications & Mobile Computing Conference, Sep 2016, Paphos, Cyprus. Proceedings of the 12th International Wireless Communications & Mobile Computing Conference, 2016, Proceedings of the 12th International Wireless Communications & Mobile Computing Conference. 〈hal-01313304〉

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