caa a22 4500 606159096 CHVBK 20210128100623.0 cr unu---uuuuu 210128e20150801xx s 000 0 eng 10.1007/s00521-014-1801-z doi (NATIONALLICENCE)springer-10.1007/s00521-014-1801-z Integration of artificial neural network and geographical information system for intelligent assessment of land suitability for the cultivation of a selected crop [Elektronische Daten] [Farshid Farnood Ahmadi, Nasir Farsad Layegh] The main objective of this study is to investigate the potential of artificial neural network (ANN) for integration with geographical information system (GIS) to assess the suitability of land to cultivate a selected crop. For this purpose, requirements of a system for intelligent assessment of land suitably were determined and the architecture of the integrated system was designed according to capabilities of ANN and GIS. For evaluation of the integrated system performance, a case study was carried out in the Mazandaran Province, located in the northern part of Iran. In the system implemented for the case study, four effective parameters in crop cultivation were utilized in the multilayer feed-forward back-propagation neural network analysis. The activation function of the hidden layer was set to log-sigmoid function. Designed ANN was trained using the samples extracted from GIS database, and 4-6-1 (4 input parameters as input layer, 6 neurons in hidden layer and 1 target value representing suitability level) structure shows the best result. Evaluation of the system shows that 83.43% of ANN's results are acceptable and consistent with the real world. The Natural Computing Applications Forum, 2014 Artificial neural network nationallicence Crop cultivation nationallicence Geographical information system nationallicence Land suitability assessment nationallicence Farnood Ahmadi Farshid Department of Geomatics Engineering, Faculty of Civil Engineering, University of Tabriz, 29 Bahman Boulevard, Tabriz, Iran aut Farsad Layegh Nasir Department of Geomatics Engineering, Faculty of Civil Engineering, University of Tabriz, 29 Bahman Boulevard, Tabriz, Iran aut Neural Computing and Applications Springer London 26/6(2015-08-01), 1311-1320 0941-0643 26:6<1311 2015 26 521 https://doi.org/10.1007/s00521-014-1801-z text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00521-014-1801-z text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Farnood Ahmadi Farshid Department of Geomatics Engineering, Faculty of Civil Engineering, University of Tabriz, 29 Bahman Boulevard, Tabriz, Iran aut NATIONALLICENCE 700 1- Farsad Layegh Nasir Department of Geomatics Engineering, Faculty of Civil Engineering, University of Tabriz, 29 Bahman Boulevard, Tabriz, Iran aut NATIONALLICENCE 773 0- Neural Computing and Applications Springer London 26/6(2015-08-01), 1311-1320 0941-0643 26:6<1311 2015 26 521