Selection of parameters to predict dew point temperature in arid lands: a case study

Mojtaba Qolipour, Ali Mostafaeipour, Mostafa Rezaei, Elham Behnam, Hossein Goudarzi, Ali Razmjou

Abstract

Dew point is the temperature at which water vapor in the air condenses into liquid with the same rate it evaporates. Dew point study is important in arid lands with low rainfall, also in other regions with various hydrological and climatological conditions. In this study, the Grey theory is applied for the first time to propose a framework approach to identify the important parameters affecting the prediction of dew point temperature. The ability of Grey theory to estimate and rank the parameters of a problem with missing data and uncertain conditions means that it has a good potential for mentioned application. For this research, 8 parameters are selected using literature review including: global solar radiation on a horizontal surface (H), water vapor pressure (VP), atmospheric pressure (P), sunshine duration (n), minimum air temperature (Tmin), maximum air temperature (Tmax), average air temperature (Tavg), and Relative Humidity (RH). The study is conducted for the city of Abadeh in Iran by using the data pertaining to a 10 year period between 2005 and 2015. The findings show that RH, Tavg, P, Tmax, Tmin, H, n and Vp with the grey possibility degrees of, respectively, 0.534, 0.551, 0.608, 0.622, 0.635, 0.695, 0.697 and 0.712, are the most important and effective parameters in prediction of dew point temperature. The proposed method also prioritizes the studied parameters in the order of their effectiveness on predicted dew point temperature.

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References

Wang YC, Tang GH. Prediction of sulfuric acid dew point temperature on heat transfer fin surface. Applied Thermal Engineering 2016; 98: 492–501.

Baghban A, Bahadori M, Rozyn J, Lee M, Abbas A, Bahadori A, Rahimali A. Estimation of air dew point temperature using computational intelligence schemes. Applied Thermal Engineering 2016; 93: 1043–1052.

Liu T.ZH, Jiang Y. Development of temperature and humidity independent control (THIC) air-conditioning systems in China—A review. Renewable and Sustainable Energy Reviews 2014; 29: 793–803.

Jani DB, Manish Mishra PK. Solid desiccant air conditioning – A state of the art review. Renewable and Sustainable Energy Reviews 2016; 60: 1451–1469.

Forman C, Kolawole I, Muritala R, Bernd Meyer P. Estimating the global waste heat potential. Renewable and Sustainable Energy Reviews 2016; 57: 1568–1579.

Pandelidis D, Anisimov S. Numerical analysis of the heat and mass transfer processes in selected M-Cycle heat exchangers for the dew point evaporative cooling. Energy Conversion and Management 2015; 90:62–83.

Meng Y, Wen X. Characteristics of dew events in an arid artificial oasis cropland and a sub-humid cropland in China. Journal of Arid Land 2016;8(3):399-408.

Zhuang Y, Zhao W. The ecological role of dew in assisting seed germination of the annual desert plant species in a desert environment, northwestern China. Journal of Arid Land 2016;8(2):264-271.

Wang X, Gao Z, Wang Y, Wang Z, Jin S. Dew measurement and estimation of rain-fed jujube (Zizyphus jujube Mill) in a semi-arid loess hilly region of China. Journal of Arid Land 2017;9(4):547-557.

Pan Y, Wang X. Effects of shrub species and microhabitats on dew formation in a revegetation-stabilized desert ecosystem in Shapotou, northern China. Journal of Arid Land 2041;6(4):389-399.

Amirmojahedi M, Mohammadi K, Shamshirband S, Seyed Danesh A, Mostafaeipour A, Kamsin A. A hybrid computational intelligence method for predicting dew point temperature. Environ Earth Sci 2016; 75:415. DOI 10.1007/s12665-015-5135-7.

Sarkar M. A new theoretical formulation of dew point temperatures applicable for comfort air-cooling systems. Energy and Buildings 2015; 86: 243–256.

Census of the Islamic Republic of Iran, 2006.

www.en.m.wikipedia.org/wiki/Abadeh .

Ming-dong, W., Bin, K., Xiang-yang, L., Xue-ke, W. Grey prediction theory and extension strategy-based excitation control for generator. Electrical Power and Energy Systems 2016; 79: 188-195.

Liu SF, Yang Y, Cao Y, Xie NM. A summary on the research of GRA models. Grey Systems: Theory and Application 2013; 3(1): 7–15.

Zhou Q, Thai VV. Fuzzy and grey theories in failure mode and effect analysis for tanker equipment failure prediction. Safety Science 2016; 83: 74-79.

Li X, Hipel W, Dang Y. An improved grey relational analysis approach for panel data clustering. Expert Systems with Applications. http://dx.doi.org/10.1016/ j.eswa.2015.07. 066.

Li G, Yamaguchi D, Nagai M. A grey based decision making approach to the supplier selection problem. Mathematical and Computer Modeling 2007; 36: 573-581.

Gassmann O, Keupp M. The competitive advantage of early and rapidly internationalizing SMEs in the biotechnology industry: A knowledge-based view", Journal of World Business 2007; 42: 350–366.

www.en.m.wikipedia.org/wiki/Dew_point .

Lin J, Thu K, Bui TD, Wang RZ, Ng KC, Chua KJ. Study on dew point evaporative cooling system with counter-flow configuration. Energy Conversion and Management 2016; 109:153–165.

Taqavifard M, Mehdimalek A. Using of Grey approach for priority key indexes to enhance strategic syllabuses effects. Quant. Of Industrial management researches 2011; 9(22): 135-165.

Dabaghi A, Mahdimalek A. A new method to assessment & priority organizations goals. Journal of Industry management 2010; 2(4): 57-74.

Bhattacharrya, P. A Grey theory based multiple attribute Approach for R&D project portfolio selection. Fuzzy information and engineering 2015; 7: 211-225.

Dong G, Yamaguchi D, Nagai M. A grey-based decision making approach to the supplier selection problem. Mathematical and Computer Modeling 2007; 46: 573-581.

Cheng pen W, Fuguo L, Hongya L, Zhanwei Y, Bo CH. Optimization of structural parameters for elliptical cross-section spiral equal-channel extrusion dies based on grey theory. Chinese Journal of Aeronautics 2007; 26(1): 209–216.

Wei J, Zhou L, Wang F, Wu D. Estimating the Work Safety Situation in Mainland China using Grey Theory. Applied Math. Modelling (2014); doi: http:// dx.doi.org/10.1016/ j.apm.2014.06.017.

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