01486nam a2200265 a 450000100080000000500110000800800410001910000190006024501270007926001720020630000190037850000160039752005860041365000220099965000240102170000170104570000190106270000190108170000200110070000180112070000190113870000210115770000230117870000190120120844732018-02-09       2017    bl uuuu     u00u1 u    #d1 aBULHOES, J. S.  aGap filling in time seriesbA new methodology applying spectral analysis and system identification.h[electronic resource]  aIn: CONFERENCE ON ELECTRICAL, ELECTRONICS ENGINEERING, INFORMATION AND COMMUNICATION TECHNOLOGIES. 2017, Pucon, Chile. [Proceedings...]. Pucon, Chile: IEE Xplorec2017  aNão paginado.  a(CHILECON).  aThe presence of gaps in time series makes the data analysis process difficult. Although there are several methods for filling such gaps, they do not present satisfactory results as the gap widens. The proposal of this paper is to present a new methodology that uses techniques of extraction of characteristics and identification of systems to fill the missing data. The proposed methodology was applied in time series of physical and chemical variables related to the water quality and behavior of the Paraguay River, and the effectiveness of the internal data forecast was proven.  aSpectral Analysis  aMétodo de Análise1 aASSIS, A. O.1 aMARTINS, C. L.1 aFURRIEL, G. P.1 aSILVA, B. C. R.1 aRODRIGUES, L.1 aREIS, M. R. C.1 aCALHEIROS, D. F.1 aOLIVEIRA, M. D. de1 aCALIXTO, W. P.