Measuring and Analyzing Agricultural Development of Iran Using Artificial Neural Network

Subject Areas : Regional Planning

آیت اله کرمی ¹ (هیئت علمی دانشگاه یاسوج)
حمید رستگاری ² (دانشجوی دکتری دانشگاه یاسوج)

Received: 2017-04-29 Accepted : 2018-05-09 Published : 2018-06-22

Keywords: Iran, Agricultural Development, Self-Organization Map, Neural Network Perceptron,

Abstract :

      In general, there is a lack of balanced development in the agricultural sector of many developing countries, including Iran. Therefore, the study of the areas of imbalances and inequalities in the development of this sector is inevitable. By studying the strengths and weaknesses of the provinces, a proper planning can be done. The purpose of this study was to identify the extent of agricultural development in the provinces of Iran. So, the research question was: What is the level of agricultural development in the provinces of Iran? The present study is descriptive-analytic in terms of applied and methodological point of view. The method of collecting information was documentary, library, and standardized tools in the form of formal tables and official results of Agricultural Census results. The statistical population of the study was all provinces of Iran (N=31). Then, 73 sub-indicators in the form of five main agricultural development indicators were extracted from the census and after weighing the indices, the artificial neural network was used to study the agricultural development of the provinces. The calculations were done using Excel and MATLAB software. The results showed that Esfahan, Tehran and Mazandaran ranked first to third respectively and Southern Khorasan, Sistan & Baluchistan and Bushehr ranked last in terms of agricultural development. It is necessary to mention that “exploitation agriculture index” in clusters 2 and 3 and “infrastructure services and other agricultural services index” in cluster 1, most importance were accounted.

References:

1. Ajagekar, B. B. and N. S. Masal, (2011). Regional disparities in the levels of agricultural development inKolhapur District of South Maharashtra. Indian Streams Research Journal, Vol.1, No. 1, pp: 139-144.


2. Alirezaei, M., Gh. Abdoalahzadeh and M. RajabiTnha, (2007). Analysis of regional differences in agricultural productivity with Data envelopment analysis approach. Economics and Agriculture Journal, Vol. 1, No. 2, pp: 1-18. (In Persian).


3. Avazzadehand, S. A. and A. Karami, (2015). Explaining Sustainability of Agricultural Exploitation System: The Case of Operating Family Farming Operating in the Central District of Boyer-Ahmad County. Rural Development Strategies, Vol. 2, No. 1, pp: 27-41. (In Persian).


4. Baghbani Arani A., N. Mozayyeni and R. Maleki, (2011). The comparison and classification of the provinces according to horticulture sub-sector indices. Journal of Agronomy Sciences, Vol. 3, No. 5, pp: 89-102. (In Persian).


5. Baldock, D., J. Dwyer, P. Lowe, J. Petersen and N. Ward, (2001). The nature of rural development: towards a sustainable integrated rural policy in Europe. Institute for European Enviromental Policy.


6. Burja, V. (2011). Regional disparities of Agricultural performance in Romania. Annales. Universitatis Apulensis Series Oeconomica, Vol. 13, No. 1, pp: 115-121.


7. Chelani, A.B., R.C.V. Chalapati, K.M. Phadke and M.Z. Hasan, (2002). Prediction of sulphur dioxide concentration using artificial neural networks. Environmental Modelling & Software, No.17, pp: 161–168.


8. Demuth, H., M. Beale and M. Hagan, (2008). Neural Network Toolbox (MATLAB), version 6, The MathWorks, Inc.


9. Eftekhari, A., M. PurTaheri, M. Farajzade and V. Heidari Sarban, (2010). Role of empowerment on agricultural development (case study: Ardabil Province). Human Geograpy Research. Vol. 42. No. 69, pp: 87-103. (In Persian).


10. Feizabadi, Y. and F. Maleki, (2016). Study and Comparison of Development Degree of Rural Areas in Iran`s Provinces. Growth and Development of Rural & Agricultural Economics, Vol. 1, No. 1, pp: 71-82. (In Persian).


11. Fotros, M.H. and M. Beheshtifar, (2009). Compare of development degree of agricultural sector of Iranian provinces during in two cross sections (1993/1994)-(2003/2004). Agricultural Economics and Development, Vol. 17, No. 75, pp: 17-39. (In Persian).


12. Ghaderi. N., A. Shams, M. AhadnejadReveshty and Z. HooshmandanMoghaddamFard, (2016). Measuring and Analyzing Agricultural Development of Sub – districts in Paveh Township Using Vikor Method. Agricultural Economics and Development, Vol. 24, No. 93, pp: 81-109. (In Persian).


13. Hagan, M. and B. Havard, Dimoth, (2009). Designing neural networks. Translated by S. M. Kia. Kian Rayaneh Publisher, Tehran. First edition. (In Persian).


14. Heydari Sarban, V. (2012). The prioritization of Dehstans of MeshkinShahr County in tems of agricultural development surfaces, Journal of Geography and Planning, Vol. 16, No. 40, pp: 75-96. (In Persian).


15. Jena, D. (2014). Agricultural Development Disparities in Odisha. A Statistical Study. American Review of Mathematics and Statistics, Vol. 2, No. 1, pp: 45-53.


16. Khoda-Pabah, K. and H. Beyk-Mohammadi, (2009). Evaluating and categorizing of rural districts of Ardebil on the basis of having development indices. Qurterly Geographic Space, Vol. 9, No. 26, pp: 1-30. (In Persian).


17. Kohonen T., S. Kaski and H. Lappalainen, (1997). Self-organized formation of various invariantfeaturefiters in the adaptive-subspace SOM, Neural Computation 9, pp: 1321-1344.


18. Kohonen, T. (1990). The self-organizing map.Proceedings of the IEEE, Vol. 78, No. 9, pp: 1464-1480.


19. Koopahi, M. (2010). Principle of agricultural economics. 13th edition. University of Tehran press. (In Persian).


20. Koutsouris, A. (2000). A system approaches to agricultural and rural development. Department of Agricultural Economy and Rural Development, University of Athens, Greece.


21. Mangiameli, P., S. K. Chen and D. A. West, (1996). Comparison of SOM neural network and hierarchical clustering. European Journal of Operational Research, Vol. 93, No. 2, pp: 402-417.


22. Ministry of Agriculture (2016). Agricultural statistics, available at: http://agri-jahad.ir/Portal/Home/Default.aspx?CategoryID=95a8e7d0-e5f0-4f2d-a241-792106c74dcc


23. Moeini, H., F. Mohammadtorab and M. Hosseinpour, (2015). Studying the application of self organizing map (SOM) in stream sediment geochemical dataclustering and comparing the results with compositional data dendrogram. Iranian Journal of Mining Engineerng, Vol. 10, No. 27, pp: 95-107. (In Persian).


24. Moradi, Z., A. A. Mirakzade, F. Rostami, F.Karimi, (2015). Measuring of Agricultural Development Levels in Villages of Qaratureh Dehestan Using TOPSIS Technique. Journal of Research and Rural Planning, Vol. 4, No. 2, pp: 78-67. (In Persian).


25. Mousavi, M. and H. Sadig, (2015). Determining the level of agricultural development in Iran, Rural Development Strategy. Vol. 1, No. 5, pp: 55-71. (In Persian).


26. Mowlaei, M., (2008). The study and comparison of agricultura1 development degree among Iran’s provinces in 1994 and 2004. Agricultural Economics and Development, Vol. 16, No. 63, pp: 71-88. (In Persian).


27. Nouri Zaman-abadi, S.H.A. and A. Amini Faskhoudi, (2007). Agricultural development contribution to rural development (case study: Isfahan Province rural areas). Journal of Agriculture, Vol. 38, No. 2, pp: 263-275. (In Persian).


28. Onsel, S., F. Ulengin, G. Ulusoy, E. Aktas, O. Kabak and Y. Topcu, (2008). A new perspective on the competitiveness of nations. Socio-Economic Planning Sciences, No. 42, pp: 221-246.


29. Patil, B.D. (2013). Regional Disparities in Levels of Agricultural Development in Dhule and NandurbarDistricts, India. Research Journal of Agriculture and Forestry Sciences, Vol. 1, No. 5, pp: 9-12.


30. Rashidpur, L., F. Makiabadi and M. Mirdamad, (2015). Assessing the Sustainability Level of Agricultural Farming Systems by Using Indicators in Azarbaijan Province. Journal of Agricultural Extension and Education Research, Vol. 8, No. 4, pp: 61-72. (In Persian).


31. Sadr-Mousavi M.S. and A. Rahimi, (2010). Comparing of the results of multilayer perceptron neural networks and multiple liner regressions for prediction of ozone concentration in Tabriz city. Quarterly Physical Geography Research Quarterly, No. 71, pp: 65-72. (In Persian).


32. Sarvar, R., A. Rashidi and Hesari, A. (2012). Measuring the development of socioeconomic structures of East Azerbaijan province. Geography, Vol. 10, No. 35, pp: 57-82. (In Persian)


33. Sepehrdoust, H. and H. Hamzeali Dastjerdi, (2014). Efficiency measurement of agricultural Sub-Sector's activities; using window analysis method. Journal of Sustainable Agriculture and Priduction Science, Vol. 23, No. 4.1, pp: 131-141. (In Persian).


34. Sharaki, J. and A. Sardar-Shahraki, (2014). Assessing the degree devekioment of Sistan and Baluchestan cities with emphasis on key indicators of the agricultural sector. Journal of Regional Planning. Vol. 4, No. 15, pp: 13-27. (In Persian).


35. Statistical Center of Iran. (2014). Statistical Yearbook of the provinces of Iran. Tehran: Iran's statistics center.


36. Tavakkoli, J. (2014). Assessment Development Level of Agriculture in Iran's Provinces Utilizing Factor Analysis and Numerical Taxonomy. Geography and Sustainability of Environment, No. 12, pp: 1-12. (In Persian).


37. Zangiabadi, A. and Z. Soltanii, (2009). The Measurment of Levels of Agricultural Development in Isfahan Township. Geographical Research, Vol. 23, No. 91, pp: 153-178. (In Persian).