K. E. Skouby, A. Kivimäki, and L. Haukiputo, Smart Cities and the Ageing Population

K. E. Covinsky, R. M. Palmer, and R. H. Fortinsky, Loss of Independence in Activities of Daily Living in Older Adults Hospitalized with Medical Illnesses: Increased Vulnerability with Age, Journal of the American Geriatrics Society, vol.342, issue.Suppl., pp.451-458, 2003.
DOI : 10.1046/j.1532-5415.2003.51152.x

S. Katz, T. D. Downs, and H. R. Cash, Progress in Development of the Index of ADL, The gerontologist, pp.20-30, 1970.
DOI : 10.1093/geront/10.1_Part_1.20

L. Zaineb, L. Tayeb, R. Philippe, W. Fréderic, and M. Hassani, A Markovianbased Approach for Daily Living Activities Recognition, International Conference on Sensor Networks (SENSORNETS), 2016.

M. Monjezi, M. Hasanipanah, and M. Khandelwal, Evaluation and prediction of blastinduced ground vibration at Shur River Dam, artificial neural network. In: Neural Computing and Applications, pp.7-8, 2013.

M. Esfe, H. Saedodin, S. Bahiraei, and M. , Thermal conductivity modeling of MgO/EG nanofluids using experimental data and artificial neural network, Journal of Thermal Analysis and Calorimetry, vol.74, issue.2, pp.287-294, 2014.
DOI : 10.1007/s10973-014-4002-1

A. Hussein, M. Adda, and M. Atieh, Smart Home Design for Disabled People based on Neural Networks, Procedia Computer Science, pp.117-126, 2014.
DOI : 10.1016/j.procs.2014.08.020

T. Teich, F. Roessler, and D. Kretz, Design of a Prototype Neural Network for Smart Homes and Energy Efficiency, Procedia Engineering, pp.603-608, 2014.
DOI : 10.1016/j.proeng.2014.03.032

H. Fang and L. He, BP Neural Network for Human Activity Recognition in Smart Home, 2012 International Conference on Computer Science and Service System, pp.1034-1037, 2012.
DOI : 10.1109/CSSS.2012.262

S. Oniga and J. Süt?, Human activity recognition using neural networks, Proceedings of the 2014 15th International Carpathian Control Conference (ICCC), pp.403-406, 2014.
DOI : 10.1109/CarpathianCC.2014.6843636

S. Oniga and J. Suto, Activity Recognition in Adaptive Assistive Systems Using Artificial Neural Networks, Elektronika ir Elektrotechnika, pp.68-72, 2016.
DOI : 10.5755/j01.eee.22.1.14112

Z. Liu, Y. Song, and Y. Shang, Posture recognition algorithm for the elderly based on BP neural networks, The 27th Chinese Control and Decision Conference (2015 CCDC), pp.1446-1449, 2015.
DOI : 10.1109/CCDC.2015.7162146

. De-j, A. Kenneth, W. M. Spears, and D. F. Gordon, Using genetic algorithms for concept learning. In: Genetic Algorithms for Machine Learning, pp.5-32, 1993.

C. Jiang and S. Fugen, Forecasting chaotic time series of exchange rate based on nonlinear autoregressive model, 2nd International Conference on, pp.238-241, 2010.

D. Whitley, A genetic algorithm tutorial, Statistics and Computing, vol.4, issue.2, pp.65-85, 1994.
DOI : 10.1007/BF00175354
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.129.179

K. Deb, A. Pratap, and S. Agarwal, A fast and elitist multiobjective genetic algorithm: NSGA-II, IEEE transactions on evolutionary computation, pp.182-197, 2002.
DOI : 10.1109/4235.996017
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.17.7771

S. A. Kazarlis, A. G. Bakirtzis, . Petridis, and . Vassilios, A genetic algorithm solution to the unit commitment problem, IEEE transactions on power systems, pp.83-92, 1996.
DOI : 10.1109/59.485989