The importance of sustainability development for developing countries and their tourism is a major issue. This study presents a new approach and framework for spatial modelling of tourism products potentials (TPP) in their sustainability evaluation. The approach was developed based on the GIS multi-criteria decision analysis (MCDA) and its performance was evaluated for spatial TPP mapping in Tabriz city, Iran. To achieve this purpose, we recognized the main Components of Tourism Development indicators (CTDI) such as attractions, accommodation, services and infrastructures facilities to improving sustainable tourism, and determined their significance using the Geographic information systems (GIS). Furthermore, the uncertainty analyze was applied to diminish the inherent error in criteria weights. A GIS-based aggregation function was applied to discern the TPP map. Finally, the emphasis in this paper investigates the practical usage of GIS for the benefit of sustainable tourism development. In particular, it inquired the possible opportunities and challenges facing the adoption of GIS to assist sustainable tourism development. The purpose of this article is to map and explore existing and potential attractions, tourism services and facilities in Tabriz and to ensure that potential opportunities are available for all tourists to enjoy enjoyable experiences in order to reveal their diverse economic, social, political and cultural benefits. Build on the positive and negative aspects of their construction and present them with appropriate solutions for tourism development that lead to sustainable tourism development and infrastructure improvement.

Due to the growth of the aging phenomenon, the use of intelligent systems technology to monitor daily activities, which leads to a reduction in the costs for health care of the elderly, has received much attention. Considering that each person's daily activities are related to his/her moods, thus, the relationship can be modeled using intelligent decision-making algorithms such as machine learning. In this study, to model Mood according to the daily activities of the elderly, intelligent decision-making algorithms such as descriptive Bayesian network-based probabilistic model, support vector machine, K nearest neighbor, linear discriminant analysis, decision tree, and ensemble learning methods, such as Bagging and Boosting was used. For the mentioned purpose, an intelligent system, including smart home, wristband, and smartphone, was designed and prepared to collect the dataset, needed to implement, train, and evaluate the proposed intelligent models. With the intelligent system, an elderly woman's daily activities are recorded for five months and her mood status is labeled by a psychologist team. The obtained results prove that the decision-making methods of the support vector machine and the ensemble Bagging tree can accurately detect the person's moods according to her daily activities. However, in a practical aspect, the designed Bayesian network model is more effective to assist psychologists to analyze the causes of detected mood states, by providing a descriptive relationship between variables related to the daily activities and mood states.

Due to the growth of the aging phenomenon, the use of intelligent systems technology to monitor daily activities, which leads to a reduction in the costs for health care of the elderly, has received much attention. Considering that each person's daily activities are related to his/her moods, thus, the relationship can be modeled using intelligent decision-making algorithms such as machine learning. In this study, to model Mood according to the daily activities of the elderly, intelligent decision-making algorithms such as descriptive Bayesian network-based probabilistic model, support vector machine, K nearest neighbor, linear discriminant analysis, decision tree, and ensemble learning methods, such as Bagging and Boosting was used. For the mentioned purpose, an intelligent system, including smart home, wristband, and smartphone, was designed and prepared to collect the dataset, needed to implement, train, and evaluate the proposed intelligent models. With the intelligent system, an elderly woman's daily activities are recorded for five months and her mood status is labeled by a psychologist team. The obtained results prove that the decision-making methods of the support vector machine and the ensemble Bagging tree can accurately detect the person's moods according to her daily activities. However, in a practical aspect, the designed Bayesian network model is more effective to assist psychologists to analyze the causes of detected mood states, by providing a descriptive relationship between variables related to the daily activities and mood states.

The purpose of this study is application of fuzzy-based decision-making system (FMCDM) method and a device for monitoring and controlling water consumption in a smart house used for water supply management (WSM) based on intelligent water management system (IWMS). This paper presents an algorithm applied for water demand consumption (WDC) optimization in regular household and its capability to evaluate the WDC range and decision and controlled WSM in critical circumstances. For this purpose, the heuristic decision-making method are used to monitor and control the WCM as effective IWMS methods based on artificial intelligence technology (AIT) and smart-learning multi-sensor. To program the device software, the MATLAB fuzzy logic programming software has been used. In order to assess the device’ s capability to respond to real conditions, a device is run to study sample-data for 24 hours a day for a month. In this study, four locations (kitchen, restroom, bathroom and garden balcony) are considered as the main WDC locations, then FMCDM algorithm are applied on these targets by main device. The results indicate that the first place (kitchen) has the greatest impact on WDC. However, the fourth place (garden balcony) has the lowest impact on WDC as well water consumption volume (WCV). Moreover, for analysis justification, the expert system (ES) is conducted as a comparison that shows the appropriate agreement with the FMCDM results.

Physical-Spatial Analysis of Hamadan Urban Areas Based on Integration of Smart Growth Indicators. Urban growth management improves the economic and social paths using smart growth principles which surveys expanding new urban development through stabilizing and revitalizing existing neighborhoods. In fact, smart growth is a planning theory that emphasizes stopping the spreading of the city. This study aims to analyze and evaluate four regions of Hamadan city’s acquiring of different smart growth indicators. This study is applied research in terms of objective and descriptive in terms of method and the TOPSIS multi-criteria decision-making model is used for spatial analysis of urban smart growth indicators. This study is applied research in terms of objective and descriptive in terms of method and the TOPSIS multi-criteria decision-making model is used for spatial analysis of urban smart growth indicators. The results indicate that area one with TOPSIS combined score of 0. 7569 ranked first (acquired), area two with TOPSIS score of 0. 5143 ranked second (semi-acquired) area three with TOPSIS score of 0. 4669 ranked third (deprived) and area four with TOPSIS score of 0. 3136 ranked fourth (deprived). Therefore, the distribution of smart growth indicators in Hamadan city has not been fairly distributed, and there is a great difference among the Hamadan city districts so that there are all types of acquired, semi-acquired and deprived zoning in the four districts of Hamadan. In addition, population distribution indicates that the population density has been very high in the areas close to the city center of Hamadan (Imam Khomeini Square) and the first and second rings, and the population density has gradually decreased in the outskirts. Keyword: urban sprawl, smart growth, density, topsis model, hamedan

The inclination toward cities and urbanization is a universal phenomenon. It is predicted that most of the increase in population and urbanization will occur in cities in developing countries. Due to the increasing urban population, the development of urban spaces in the future is inevitable, so understanding this process is essential for effective management of urban environmental protection. Therefore, the purpose of this study is to investigate smart growth indices in the spatial area of Gorgan city using multi-criteria decision making models. The method used in this study is descriptiveanalytical and it is an applied research. The required data were extracted from secondary data and 16 criteria were used to evaluate Gorgan's urban areas in terms of smart growth indices. Data analysis was performed using Shannon entropy (TOPSIS) and SAW (Excel) and Excel spreadsheet software (SPSS) and Arc GIS software was used to map. The results of the mean technique show that Area 2 with (0. 634) average score ranks first in terms of smart growth indices and Area 1, city of Gorgan is ranked second (0. 591). Overall, these two areas in the Gorgan Zone are smart according to growth indicators. Area 4 with 0. 528 is third ranking, Area 3 with 0. 447 is fourth ranking and Area 6 with 0. 371 is fifth ranking all of which are in semi-favorable areas in Gorgan. Finally, Areas 8, 5 and 7 are ranked sixth, seventh and eighth with scores of 0. 321, 0. 210 and 0. 171, respectively, and in terms of having smart growth indicators at a low level and they are less-favorable areas.

Introduction: The existence of intelligent decision-making in educational managers increases their recognition skills and they find the ability to identify the decision process, check possibilities, make correct judgments, and plan carefully. Therefore, the present study was conducted with the aim of studying the mediating role of intellectual ethics in the relationship between digital leadership and smart decision-making among elementary school principals in Kermanshah province. Material and Methods: The research is a correlational research based on structural equation modeling of the correlation-covariance matrix. The statistical population includes all the elementary principals of Kermanshah province in the academic year 2021-2022 (N=1902). The sample size was estimated based on proportional stratified random sampling and Cochran's formula (n=320). The tools included intelligent leadership, intellectual ethics and smart decision-making questionnaires, whose content validity was confirmed by experts and professors, and their construct validity was confirmed by factor analysis. The reliability of the questionnaires was calculated through Cronbach's alpha as 0. 85, 0. 93 and 0. 95 respectively. Pearson's correlation test and structural equation modeling were used for data analysis, and SPSS and LISREL software were used. Results: The relationship between digital leadership and intellectual ethics, digital leadership and intelligent decision-making, and the relationship between intellectual ethics and smart decision-making were significant. Finally, it was found that intellectual ethics can play a mediating role in the relationship between digital leadership and smart decision making. Conclusion: The results of this study show that educational managers can make smart decisions through the digital leadership style and, of course, considering intellectual ethics, and in this way, take steps in the direction of advancing educational goals and missions.