Filling missing meteorological data in heating and cooling seasons separately-Reference-Cited by-同舟云学术

Filling missing meteorological data in heating and cooling seasons separately

Published:2018-09-04 Issue:2 Volume:39 Page:701-710
ISSN:0899-8418
Container-title:International Journal of Climatology
language:en
Short-container-title:Int J Climatol

Author:

Anjomshoaa Ali¹^ORCID,Salmanzadeh Mazyar¹^ORCID

Affiliation:

1. Department of Mechanical Engineering; Shahid Bahonar University of Kerman; Kerman Iran

Publisher

Wiley

Subject

Atmospheric Science

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1002/joc.5836/fullpdf

Reference18 articles.

1. Estimation of the changeover times and degree-days balance point temperatures of a city using energy signatures;Anjomshoaa;Sustainable Cities and Society,2017

2. Finding a criterion for the pressure loss of energy recovery exchangers in HVAC systems from thermodynamic and economic points of view;Anjomshoaa;Energy and Buildings,2018

3. Restoration of Short Periods of Missing Energy Use and Weather Data Using Cubic Spline and Fourier Series Approaches: Qualitative Analysis., In;Baltazar-Cervantes;Proceedings of the 13th Symposium on Improving Building Systems in Hot and Humid Climates.,2002

4. Study of cubic splines and Fourier series as interpolation techniques for filling in short periods of missing building energy use and weather data;Baltazar;Journal of Solar Energy Engineering,2006

5. 2013

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