This research aims to perform strategic planning of tourism development in Kandovan village using SOAR model. This model is a combination of SWOT strategy and Appreciative Inquiry (AI) introduced by Jacqueline M. Stavros. AI, instead of focusing on problems such as weaknesses and threats, identifies strengths and creates promising opportunities. Methods: In this study, library and semi-structured interview methods have been used. The present study is a qualitative research in terms of nature and method of data collection. The statistical population of this research includes villagers of Kandovan, government officials, and NGO's related to Kandovan village, in Osku County, near Tabriz metropolis, and tourists visiting the Kandovan village in the summer of 2016. In this research, the qualitative content analysis technique was used in the framework of inductive approach in accordance with the SOAR strategic planning model. Then, four SOAR strategic model indicators, i.e. strengths, opportunities, aspirations and results were extracted. Results: The results of the research indicate that for implementation of UNESCO's architectural standards to world village registration, it is necessary to construct a new Kandovan next to the old village. In addition, holding festivals, exhibitions and weekly markets for the development of regional tourism is recommended. Establishment of tourism amenities such as construction of parking lots, recreational complex, designing websites and construction of a hotel are some other recommendations. Holding training courses related to tourism in the village, is a major step towards development of tourism considering the potential among the youth of the village. Conclusion: Villagers require to learn a series of educational courses. The youth of the village continue to do their business in the village and commute between the village and the city they live during the tourist season. Considering the young generation's loyalty to their hometown and their desire to work in their village, many of them are ready to participate in the development of tourism of village and, as a result, holding educational courses from the Cultural Heritage and Tourism Organization of the region such as foreign language courses, tourism guides, hospitality culture, marketing and advertising are welcomed by young people.

This paper shows a few novel calculations for wind speed estimation, which is focused around soft computing. The inputs of to the estimators are picked as the wind turbine power coefficient, rotational rate and blade pitch angle. Polynomial and radial basis function (RBF) are applied as the kernel function of Support Vector Regression (SVR) technique to estimate the wind speed in this study. Instead of minimizing the observed training error, SVR_poly and SVR_rbf attempt to minimize the generalization error bound so as to achieve generalized performance. The results are compared with the adaptive neuro-fuzzy (ANFIS) results.