Predicting areas with ecotourism capability using artificial neural networks and linear discriminant analysis (case stud
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Predicting areas with ecotourism capability using artificial neural networks and linear discriminant analysis (case study: Arasbaran Protected Area, Iran) Manijeh Talebi1 · Baris Majnounian1 · Majid Makhdoum1 · Ehsan Abdi1 · Mahmoud Omid2 Received: 18 December 2019 / Accepted: 26 August 2020 © Springer Nature B.V. 2020
Abstract In this study, the common systematic approach in Iran as well as a multilayer perceptron neural network were used to evaluate the ecological capability of the area for ecotourism. The performance of the artificial neural network (ANN) and linear discriminant analysis (LDA) method in the prediction and ranking of areas with ecotourism capability were also compared. Based on the results obtained, the ANN with an overall accuracy of 97% outperformed LDA (overall accuracy of 86%) in terms of the prediction and classification of recreational areas. Therefore, for each class, the ANN with an accuracy, precision, and sensitivity of 98%, 94.33%, and 86.67%, respectively, outperformed the LDA with the corresponding values of 90.67%, 55.33%, and 40.33%, respectively. Based on the ANN-modeled map, 0.17%, 10.09%, and 89.74% of the area were shown to belong to intensive recreation class 2, extensive recreation class 2, and the not suitable for recreation class, respectively. Therefore, the ANN functions well with higher accuracy for modeling and classification of areas with ecotourism capability compared to LDA. Keywords Artificial neural network · Ecological capability evaluation · Ecotourism · Linear discriminant analysis
1 Introduction Currently, efforts are being made to meet the physical, mental, social, cultural, economic, and physiological needs of people via leisure facilities and recreation areas, and people are turning to natural areas to regain balance and health (Cetin and Sevik 2016a). Tourism, in its various forms, has long been considered as a way to satisfy these types of human needs. Given the mechanical life of modern people, ecotourism is one of the growing branches of * Ehsan Abdi [email protected] 1
Department of Forestry and Forest Economics, Faculty of Natural Resources, University of Tehran, Karaj, Iran
2
Department of Mechanical Engineering Agricultural Machinery, Faculty of Agricultural Engineering and Technology, University of Tehran, Karaj, Iran
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this industry (Salman Mahini et al. 2009). According to the International Nature Conservation Union (IUCN), the definition of ecotourism includes having fun while supporting the protection of natural and cultural resources. Tourism management businesses provide opportunities for local residents in favor of tourism development (Cetin and Sevik 2016b). Therefore, ecotourism aiming to minimize environmental impacts and apply ecological protection principles contributes to the economic development of local communities, landscape protection, and sustainable development plans (Dhami and Deng 2012; Dhami et al. 2014; Sahani 2019; Zhang et al. 2015), and the associated training, employment c
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