MODELING AND ESTIMATION OF WOOD EQUILIBRIUM MOISTURE CONTENT (EMC) WITH SPATIAL VARIABLES IN IRAN

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HELALI J.; EDALAT H.; RASOULI D.

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Journal: Journal of Wood and Forest Science and Technology Year:2016 | Volume:23 | Issue:1 Page(s): 63-75

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Title

MODELING AND ESTIMATION OF WOOD EQUILIBRIUM MOISTURE CONTENT (EMC) WITH SPATIAL VARIABLES IN IRAN

Author(s)

HELALI J. | EDALAT H. | RASOULI D. | Issue Writer Certificate

Keywords

WOODQ2

EQUILIBRIUM MOISTURE CONTENTQ1

SPATIAL VARIABLEQ1

MATHEMATICAL MODELINGQ1

STATISTICAL EQUATIONSQ1

Abstract

Background and objectives: EQUILIBRIUM MOISTURE CONTENT (EMC) is one of the major indicators in WOOD sciences that its determination and investigation in the different locations prevents the losses of WOOD products quality by meteorological parameters. This study was conducted to present a mathematical model according to a correlation between EMC and SPATIAL VARIABLEs (latitude, longitude and altitude).Materials and methods: In this study, 93 synoptic and climatology stations during a 26-year period were selected and then the regression equations of uni- and multi-variable between EMC and the SPATIAL VARIABLEs were fitted to the experimental data. The distribution of stations was suitably selected to cover all the geographical and climatic zones in the country. The constructed equations were evaluated using determination of coefficient (R2), root mean square error (RMSE), and mean bias error (MBE). In initial and second steps, the equations were considered with the highest R2 values and the lowest RMSE values, respectively. Under-estimation and over-estimation of the equations were determined by negative and positive MBE values, respectively.Results: Results showed that the offshore and cold climate had more EMC than the central and arid climates of Iran. The highest EMC was belonged to winter months, initial months of spring and final months of autumn. Analysis by SPATIAL VARIABLEs revealed that use of two-variable equation of latitude-altitude represents better than the uni-variable equations. However, three-variable analysis showed more exact results compared to uni- and two-variable equations. A good finding was found in the warm months using three-variable analysis.Conclusion: It seems that the suitable solution to investigate EMC with SPATIAL VARIABLEs was studying the regional scale, considering the climatic conditions, near and further to water resources and finally presenting a reasonable model for specific climate of the each area.

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APA: Copy

HELALI, J., EDALAT, H., & RASOULI, D.. (2016). MODELING AND ESTIMATION OF WOOD EQUILIBRIUM MOISTURE CONTENT (EMC) WITH SPATIAL VARIABLES IN IRAN. JOURNAL OF WOOD AND FOREST SCIENCE AND TECHNOLOGY, 23(1), 63-75. SID. https://sid.ir/paper/156661/en

Vancouver: Copy

HELALI J., EDALAT H., RASOULI D.. MODELING AND ESTIMATION OF WOOD EQUILIBRIUM MOISTURE CONTENT (EMC) WITH SPATIAL VARIABLES IN IRAN. JOURNAL OF WOOD AND FOREST SCIENCE AND TECHNOLOGY[Internet]. 2016;23(1):63-75. Available from: https://sid.ir/paper/156661/en

IEEE: Copy

J. HELALI, H. EDALAT, and D. RASOULI, “MODELING AND ESTIMATION OF WOOD EQUILIBRIUM MOISTURE CONTENT (EMC) WITH SPATIAL VARIABLES IN IRAN,” JOURNAL OF WOOD AND FOREST SCIENCE AND TECHNOLOGY, vol. 23, no. 1, pp. 63–75, 2016, [Online]. Available: https://sid.ir/paper/156661/en

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