مدلسازی حجم تجاری درختان توده‌های آمیختۀ راش جنگل‌های هیرکانی با استفاده از شبکۀ عصبی مصنوعی

[1]. Namiranian, M. (2010). measurement of tree and forest biometry. University of Tehran Press, Tehran.

[2]. Bayati, H., and Najafi, A. (2013). Performance Comparison Artificial Neural Networks with Regression Analysis in Trees Trunk Volume Estimation. Journal of Forest and Wood Products, 66 (2): 177-191.

[3]. Ozçelik, R., Diamantopoulou, M.J., Brooks, JR., and Wiant Jr, HV. (2010). Estimating tree bole volume using artificial neural network models for four species in Turkey. Journal of Environmental Management, 91(3): 742-753.

[4]. Atkinson, P.M., and Tatnall, A.R.L. (1997). Introduction neural networks in remote sensing. International Journal of Remote Sensing, 18(4): 699-709.

[5]. Coulson, R.N., Folse, L.J., and Loh, D.K. (1987). Artificial intelligence and natural resource management. Science, (237): 262-267.

[6]. Lek, S., Delacoste, M., Baran, P., Dimopoulos, I., Lauques, J., and Aulagnier, S. (1996). Application of neural networks to modelling nonlinear relationships in ecology. Ecological Modelling, 90(1): 39-52.

[7]. Hagan, M.T., Demuth, H.B., and Beale, M.H. (1996). Neural Network design. PWS publishing co, United States of America.

[8]. Tiryaki, S., and Aydin, A. (2014). An artificial neural network model for predicting compression strength of heat treated woods and comparison with a multiple linear regression model. Construction and Building Materials, 62: 102-108.

[9]. Hamzacebi, C., Akay, D., and Kutay, F. (2009). Comparison of direct and iterative artificial neural network forecast approaches in multi-periodic time series forecasting. Expert Systems with Application, 36(2): 3839-3844.

[10]. Anonymous. (2008). Glandrood Forest management project, district3, Noor, Mazandarn (second renewal view). General Office of Natural Resources and Watershed Management of Mazandaran province, Nowshahr, 174 p.

[11]. Naghdi, R., and Ghajar, I. (2012). Application of Artificial Neural Network in the Modeling of Skidding Time Prediction. Advanced Materials Research, 403-408: 3538-3543.

[12]. Woods, K., and Bowyer, K.W. (1997). Generating ROC Curves for Artificial Neural Networks. IEEE Transactions on Medical Imaging, 16(3): 329-337.

[13]. Foody, G.M., Boyd, D.S., and Cutler, M.E.J. (2003). Predictive relations of tropical forest biomass from Landsat TM data and their transferability between regions. Remote Sensing of Environment, 85(4): 463-474.

[14]. Azizi Ghalaty, S., Rangzan, K., Taghizadeh, A., and Ahmady, Sh. (2015). Application of artificial neural network and ordinary least squares regression in modeling land use changes. Journal of forest and wood products, (68)1: 1-16.

[15]. Bayati, H., Najafi, A., and Abdolmaleki, P. (2016). Assessment of artificial neural networks ability in winching time study of Timber Jack 450C. Journal of Forest and Wood Products, (68)4: 757- 769.

[16]. Feiznia, S., Mohammad Asgari, H., and Moazzami, M. (2008). Investigating the applicability of Neural Network method for estimating daily suspended sediment yield (Case study: Zard Drainage Basin, Khozestan Province). Journal of the Iranian Natural Resources, 60(4): 1199-1210.