Applications of artificial neural networks and hybrid models for predicting CO 2 flux from soil to atmosphere
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ORIGINAL PAPER
Applications of artificial neural networks and hybrid models for predicting CO2 flux from soil to atmosphere S. Altikat1 · A. Gulbe2 · H. K. Kucukerdem1 · A. Altikat3 Received: 28 January 2020 / Revised: 22 May 2020 / Accepted: 2 June 2020 © Islamic Azad University (IAU) 2020
Abstract The goal of this research is to model the level of carbon dioxide flowing from soil to sky using various methods. The methods of multiple linear regression (MLR) and artificial neural networks (ANN) beside two different hybrid models were exploited to achieve this objective. These hybrid models were arranged as the prior two methods with principal component analysis (PCA). For the ANN, 36 different structures were used with different transfer (logsig–logsig, tansig–tansig, pureline–pureline, logsig–tansig, logsig–pureline and tansig–pureline)—learning functions (Levenberg–Marquardt and Gradient Descent with Momentum) and neuron numbers (10, 20 and 30). The manure norm, soil type, soil temperature, soil moisture content, soil depth, and photosynthetically active radiation values were taken into account as input parameters while CO2 flux was output parameter. According to the research conducted, the best results were obtained from the ANN method. This method was followed by PCA + ANN, MLR and PCA + MLR methods. The R2 value of the network established in the ANN method was determined as 0.98. In this ANN model, Levenberg–Marquardt and tansig–pureline with 30 neurons were used as transfer and learning functions, respectively. Besides, when principal components were used as input parameters, the lower R2 values were obtained with both the MLR and ANN methods. Keywords Artificial neural networks · Principal components · Linear regression · Saline soil · Soil moisture · Soil temperature
Introduction There are a few main factors affecting soil CO2 flux such as soil organic matter content, soil type, soil tillage and management systems, root respiration, etc. The decomposition of soil organic matter causes CO2 flux (Kuzyakov 2002; Fender et al. 2013). Fertilization, especially N fertilization, accelerates CO2 flux due to the effect of root development (Shao et al. 2013) and microbial activity (Yan et al. 2010; Fangueiro et al. 2008). Soil temperature and soil moisture Editorial responsibility: Parveen Fatemeh Rupani. * S. Altikat [email protected] 1
Department of the Biosystems Engineering, Agriculture Faculty, Iğdır University, Iğdır, Turkey
2
Department of the Computer Science, Vocational School of Technical Sciences, Iğdır University, Iğdır, Turkey
3
Department of the Environmental Engineering, Engineering Faculty, Iğdır University, Iğdır, Turkey
affect soil CO2 flux because of their direct impact on microbial activity (Risk et al. 2002; Rustad et al. 2001). Soil respiration amount increases with the increase in soil temperature (Kirschbaum 1995; William et al. 1994, Lou et al. 2003, Lu et al. 2008). Various methods have been used while modeling of the CO2 flux from soil to atmosphere.
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