درخت حوزه‌های تخصصی

Today, choosing the suitable model for determining the portfolio of investment in financial assets is one of the critical issues of the attention of analysts and capital market activists, and investing in a portfolio consisting of mutual investment funds is the same. With this statement, the purpose of the article is to evaluate and compare the net assets value (return) of the Federation of Asian and European Stock Exchanges (FEAS) member countries by using support machine models in comparison with statistical models. The statistical and sample population included the data of 39 selected traded funds and FEAS members from 12 selected countries (including Iran) between 2014 and 2021. The data related to the mentioned funds were classified and analyzed using spss-modeler, rapid miner, and Weka software. They were tested with 24 support machine methods and 11 statistical methods, and the results showed that the prediction accuracy of statistical models is lower than that of support machine models. The Mann-Whitney test was used to determine the significance of this difference. Also, the results show that at the 95% confidence level, it can be claimed that the prediction accuracy of machine learning models is higher than statistical models. The average rating of machine learning models was (20.86) much higher than statistical models (10.85).

Land heritage and necessity of planning in order to safeguard this heritage is one of the greatest challenges facing the researchers of untouched spaces and international natural heritage. One of the most important instruments in this approach is considering tourism capabilities in the form of geological attractions and geomorphology of the land heritages and its bond with economical, cultural and social features of tourism. Geotourism plays an unparalleled role in the development of economic, cultural and environmental effects on land management and planning for the conservation and sustainable development of the geological heritage. The Alamut area of ​​Qazvin, along with the legacy of land, is a significant destination in the country from the cultural and social point of view. In order to reach the goals of the sustainable development, it is important to identify the crucial geosites of the region and analyze them based on their different geo-tourism values. In the meantime, East Alamut is one of the areas that can attract many tourists with a variety of natural phenomena. In this study, using satellite images, geological maps, and field studies, 10 East Alamut lands with higher geo-touristic attraction were selected. In the final review of geo-tourism assessment based on the GAM method, the geosite of the Kalayeh Moalem was identified as one of the top geosits due to its scientific value in national level, having aesthetic, cultural and social values, and the existence of a set of functional, economic, and tourist services values.​​ Evan Lake is also in the second priority due to high geological diversity, its ecological and cultural values, easy access, tourism services, appropriate infrastructure and also aesthetic and protective values. Alamut historical area, next to the Garmarud Valley is on next priority.