Modeling the Aesthetic Values of Landscapes of Tourist Villages Using Artificial Neural Networks Case Study: Savar-Toutakhane Touristic Roads

Majnouni- Toutakhane, Ali; Karimzade, Hosein

doi:10.22054/tms.2020.29638.1853

Document Type : Research Paper

Authors

¹ PH.D Student in Architectural Engineering Department, Univeristy of Bonab, Bonab, Iran

² Assistant Professor Department of Geography and Rural Planning, Faculty of Planning and Environmental Sciences, University of Tabriz,Tabriz, Iran

https://doi.org/10.22054/tms.2020.29638.1853

Abstract

The purpose of this article was to evaluate the aesthetic values of tourism attractions in the Savar-Toutakhane tourist roads in both objective and subjective dimensions; For this purpose, eight components were identified. Artificial neural network were used to determine the objective aesthetics, and the Spearman test and multiple regression were used to determine mental aesthetics. The statistical population of the study was 3324 tourists; using the Cochran formula, 275 people were selected by random sampling. The reliability of the questionnaire was 0.889 using Cronbach's alpha formula. The results of the research using the artificial neural network method showed that the high visibility of the peripheral high peak has the highest value and visibility of the flowing rivers with the least value. The results of multiple regression analysis in the subjective aesthetic field indicated that 8 components could explain 68.9% of variance variations. Also, The results of both methods indicate the high value of tourist attractions on this road.

Keywords

References

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Tourism Management Studies

Modeling the Aesthetic Values of Landscapes of Tourist Villages Using Artificial Neural Networks Case Study: Savar-Toutakhane Touristic Roads

References

References

Volume 15, Issue 51 - Serial Number 15
October 2020
Pages 145-172

Modeling the Aesthetic Values of Landscapes of Tourist Villages Using Artificial Neural Networks Case Study: Savar-Toutakhane Touristic Roads

References

References

Volume 15, Issue 51 - Serial Number 15October 2020Pages 145-172

Volume 15, Issue 51 - Serial Number 15
October 2020
Pages 145-172