جستجوی مقالات مرتبط با کلیدواژه "منطق فازی" در نشریات گروه "علوم انسانی"

Pursuing the goals of a government in the transnational sphere is planned and targeted through foreign policy, the most important of which can be considered as providing security. The current research aims to firstly examine the fragility of Central Asian states as the immediate environment of the Islamic Republic of Iran by using the fuzzy logic method and put the paths that exist in the fragility of Central Asian states as the basis for understanding the situation and by analyzing it, While recognizing the existing security threats in Central Asia, in the second step, he will develop a foreign policy appropriate to the current situation. For this purpose, the main questions of the research are: What is the state of fragility of Central Asian governments? How many paths of fragility are there in Central Asia? Considering the situation in Central Asia, what is the appropriate model of Iran's foreign policy? The result of examining the state of Central Asia in the fragility of governments indicates that all 5 existing governments have warnings of fragility and creating security problems, and two important variables in this situation are elites who oppose the government and vengeful and hostile groups. Referring to the theory of regional security, it seems that the prevention of multilateralism in foreign policy according to the status of each of the identified paths, in addition to providing regional security, will lead to playing a pivotal role for the Islamic Republic of Iran.

Flood is one of the main natural disasters and an important global issue, so that with the increase in the occurrence of floods, the concerns about the increase in death and economic losses due to it increase. Floods occur every year in Iran due to its large size, climatic diversity, land use changes and changes in the temporal and spatial scales of rainfall. The current research is based on the combination of Fuzzy and Hierarchical (AHP) logic models to assess the flood risk of Khuzestan catchment areas. In this research, the parameters of maximum precipitation, distance from waterway, density of waterway, vegetation and slope were used. Digital maps of parameters were prepared using ArcGIS 10.3 software. The probability of flood occurrence for each class of each factor and the importance of each factor compared to other factors in the occurrence of floods were checked by expert opinions and the corresponding weights were calculated in Arc GIS 10.3 software. The obtained weights for each class were applied to the corresponding layers. Finally, flood probability maps of the investigated area were prepared and the vulnerability was evaluated in 5 classes: very high, high, medium, low and very low. The results indicate that the precipitation factor has the greatest impact on the occurrence of floods and the lowest impact is related to the vegetation factor, and of the total area of 6292521 hectares of Khuzestan province, 9.74% is in the very low risk assessment class; 53.47% low risk assessment; 21.10% of moderate risk assessment, 6.97% high risk assessment and 8.69% very high risk assessment.

In addition to natural disasters such as floods, which cause great damage to the environment and human societies, the phenomenon of dust also causes irreparable damage to urban environments, transportation systems, respiratory systems, etc. Identifying Potential Dust Source Areas is considered the first step to control and prevent this phenomenon. Various researches have been conducted to identify dust sources, but most studies have relied on small-scale images. This research aims to use medium-scale satellite images to identify local areas prone to dust production. Google Earth Engine was used to analyze factors influencing dust generation, including slope, Digital Elevation Model (DEM), land use, soil salinity, Normalized Difference Vegetation Index (NDVI), soil moisture, wind speed, precipitation, and Land Surface Temperature (LST). Analytical Hierarchy Process (AHP) was used to assign weights to these elements. The resulting weights were: soil moisture (0.264), NDVI (0.208), wind speed (0.153), precipitation (0.107), land use/soil salinity (0.081), LST (0.064), DEM (0.024), and slope (0.020). The inconsistency index (0.015) indicated a high degree of consistency between the assigned weights, which is below the acceptable threshold (1). Due to the lack of ground-based air quality measurements, the Aerosol Optical Depth product (a satellite-derived measurement of airborne particles) was used to validate the resulting dust source maps. The final map showed that the potential for dust generation decreased closer to the heights of Sahand and increased closer to the lake.

Earthquake should be considered as one of the most prevalent and destructive natural disasters that all the countries of the world, especially Iran, face with. Therefore, it is important to evaluate urban resilience against earthquakes. Urban resilience is a new and under researched concept in urban studies and urban planning. Accordingly, it is necessary to evaluate the resilience of the city of Islamabad Gharb, like any other city, against earthquakes. It seems that considering and resorting to some sources we can understand the vulnerability of Iranian cities. It is necessary to use a suitable model and various types of spatial and non-spatial data. Moreover, the analyses related to the geographic information system and most importantly, the review and analysis of the current global experiences should be considered. Taking these issues into account, we can achieve the risk map of Iranian cities against earthquakes. Additionally, by making the necessary preparations, this phenomenon can be turned into a planned process in crisis management caused by natural hazards. The purpose of this research was to evaluate the resilience of the city of Islamabad Gharb against the risk of earthquakes. For this purpose, the integrated model of Weighted Linear Combination (WLC) and fuzzy Gamma operator (Gamma) were used. Analytical Hierarchy Method (AHP) was applied for weighting the variables. The final goal was to see the status of urban resilience against earthquakes in Islamabad Gharb.

This applied research used a descriptive-analytical method. For this study many resources were used including documentary and library studies, information about and provided by the municipality of Islamabad Gharb city, and other reports including studies that were previously conducted in this field on the city. Moreover, the studies and plans that have been carried out by the deputy of planning of the governorate should be added to the sources. Two integrated models of Weighted Linear Combination (WLC) and fuzzy Gamma operator (Gamma) were used to evaluate the resilience of the city of Islamabad Gharb against earthquakes. Analytical Hierarchy Method (AHP) was also used to weight the variables. For evaluating the resilience of the city against the earthquake, two integrated models of WLC and gamma with values ​​of 0.3, 0.5 and 0.9 were used and the final maps on five classes (very low, low, medium, high, and very high level of resilience) were prepared. Moreover, for evaluating the accurancy and correctness of the final maps produced by the two models, the results of total quality index (QS) were used.

Total quality index (QS) was applied for ensuring the accuracy of WLC models and fuzzy gamma operators of 0.3, 0.5 and 0.9 to prepare earthquake resilience zoning map. Higher QS of zoning model or method indicates that the calculations and predictions for resilience zoning map are highly accurate. By using the QS we can measure the accuracy of the calculations related to the WLC model and fuzzy gamma operators. Moreover, the QS value of each resilience class related to each of the mentioned models can be obtained separately. In addition to these two cases, it is possible to compare the accuracy and correctness of calculations related to each resilience class with the accuracy and correctness of calculations of other resilience classes. The QS values for very low, low, medium, high and very high resilience classes related to the zoning map created by WLC model, respectively, were 0.007, 0.293, 0.001, 0.247 and 0.063. The QS value of "low" resilience class (0.293) is higher than the QS value of other resilience classes. This can be interpreted that the calculations related to the area of ​​the low resilience class have been done with more precision and accuracy than other resilience classes. The following classes are high, very high, very low and medium resilience classes. Moreover, the QS for the WLC model is the algebraic sum of the QS values ​​for very low, low, medium, high and very high resilience classes. Taking into account the QS, the accuracy and correctness of the WLC model for the preparation of resilience zoning map against earthquake risk for the city of Islamabad Gharb was 0.611.

The QS index can be used to calculate the accuracy of the performed calculations related to the WLC model and fuzzy gamma operators. It is also possible to obtain the QS value of each resilience class related to each of these two models separately. Moreover, the precision and accuracy of calculations of each resilience class can be compared with the precision and accuracy of calculations of other resilience classes. QS value for the very low, low, medium, high, and very high resilience classes pertaining to the zoning map created by WLC model were, respectively, 0.007, 0.293, 0.001, 0.247, and 0.063. The QS value of low resilience class (0.293) is higher than the QS value of other resilience classes. We may interpret it that the calculations pertaining to the low resilience class have been done with more precision and accuracy than the calculation of other resilience classes. Other classes are, respectively, high, very high, very low, and medium resilience classes. Moreover, the QS for the WLC model is the algebraic sum of QS values ​​for the very low, low, medium, high, and very high resilience classes. Taking the QS, the precision and accuracy of the WLC model in preparing the zoning map of resilience against earthquake risk for Islamabad Gharb city is 0.611.

Over the past three decades, environmental challenges have become a global concern due to growing worries about the irreversible consequences of environmental degradation. Consequently, addressing environmental issues has increasingly become a priority for policymakers. Today, all countries are striving to achieve a balance between environmental protection and socioeconomic stability through the development of effective policies.

This study aims to examine and evaluate the environmental efficiency of Iran's provinces over different time periods, considering the inherent uncertainty in the data. In the real world, data is not always precise and deterministic, and deviations in data can significantly alter the results of efficiency evaluations. Therefore, it is essential to employ suitable methods to address data uncertainty when assessing efficiency. In this research, a Fuzzy Window Data Envelopment Analysis (FWDEA) model is utilized to evaluate the environmental efficiency of Iran's provinces. This model effectively accounts for data uncertainty and provides more accurate and reliable results.

The approach used in this study incorporates undesirable outputs and can be applied to various structures in fuzzy data envelopment analysis. Based on a literature review, consultations with experts in the fields of the environment and data envelopment analysis, and available data, the input variables of the study were determined to be per capita energy consumption and per capita vehicles, while the output variable was defined as per capita pollutant emissions. Given the uncertainty about whether all units operate at optimal scale, the BCC model was employed. Furthermore, since it is easier to control outputs compared to inputs, an output-oriented data envelopment analysis model with variable returns to scale was assumed. Finally, the proposed fuzzy window data envelopment analysis model was implemented for 29 provinces of Iran over four time periods from 2017 to 2020, and the results were analyzed.

Data analysis using the proposed model revealed that East Azerbaijan province had the best environmental performance with an efficiency score of 0.837407, while Hormozgan province had the worst performance with an efficiency score of 0.332543 during the four years of the study. Examining the annual average efficiency of the provinces indicated that the trend of efficiency improvement or decline varied across provinces over the years and was not stable. Additionally, the results of the fuzzy window data envelopment analysis model showed that the efficiency of provinces varied in each consecutive time window and did not follow a fixed pattern.

In this study, a fuzzy DEA approach was employed to evaluate efficiency considering the ambiguous, unavailable, and imprecise nature of the data. Overall, the use of fuzzy window DEA in assessing the environmental efficiency of Iran's provinces is one of the best methods due to its high accuracy, ability to model fuzzy data, and identification of complex patterns. This approach can assist policymakers in identifying the strengths and weaknesses of provinces in terms of environmental efficiency and formulating appropriate policies to improve environmental performance. To enhance the environmental efficiency of provinces, it is necessary to develop dynamic environmental policies tailored to the specific conditions of each province. Moreover, given that environmental challenges are global, the application of similar approaches to evaluate environmental efficiency in other countries can also contribute to improving global environmental performance.

Identifying and exploiting existing opportunities is the basis for creating and promoting employee creativity and requires appropriate prerequisites. The aim of this study is to investigate the impact of leadership styles on the innovation climate and its impact on employee creativity with the moderating role of creative self-efficacy and the mediating role of trust and personal identity of the General Directorate of Information Technology of the Tax Administration. This is an applied and descriptive-correlational research. The statistical population includes managers and employees of the General Department of Information Technology of the Tax Administration, from which 138 were selected by simple random sampling. The data collection tool is a researcher-made questionnaire. To test the hypotheses, structural equation modeling was performed with the partial least squares approach using Smart PLS software. All hypotheses were confirmed except the hypotheses related to trust and creative self-efficacy. Also, by using transformational and interactive leadership styles as well as identifying employees, innovation can be created in the organization and thus employee creativity indicators will be improved

 Erosion is a critical geomorphological process with significant environmental implications, including land degradation, fertility loss, and negative effects on aquatic ecosystems. It is recognized as an environmental hazard due to the substantial damages it can cause.

 This research uses geomorphometric indicators and a fuzzy approach to zoning the soil erosion potential in the Khiavchai area of Meshginshahr. Various variables were used, including slope, aspect, surface curvature, range length, Melton's roughness coefficient, stream power index, drainage density, topographic wetness index, distance from the river, vegetation, precipitation, and geological formations. The information layers were combined based on their impact on erosion using different fuzzifier functions. The fuzzy gamma operator in a GIS platform was utilized to combine and overlay the indicators. 

 The results revealed that approximately 8.4% of the study area exhibited high erosion potential. In comparison, around 18.7% had a high erosion potential, primarily located in the middle parts of the watershed. The high erodibility in these areas can be attributed to erodible geological formations, steep slopes, and high drainage density. Other contributing factors include predominantly southern and western slope aspects, longer slopes, and poor vegetation. 

 The indicators used in assessing erosion-prone areas provide insights into the geomorphological and hydrological conditions of the study watershed. The prepared erosion map can serve as a foundation for prioritizing soil conservation management measures and reducing the impact of erosion. 

Innovation:

 This research employs a combination of geomorphometric indicators and a fuzzy approach to assess soil erosion potential accurately. The practical application lies in utilizing the study's findings to prioritize areas for effectively implementing erosion mitigation and soil conservation measures in land management.

In this article, for the first time, a new method is introduced to control the process of preparing materials and equipment in the factory using genetic-fuzzy combined algorithms, and in this method, the effect of external random factors in the form of demand and guidance of time uncertainty is specially considered. has been In the proposed model, parameters of time-varying member functions are used dynamically to describe the values ​​of mixed sets of modeled outputs. The method presented in this article is based on four confirmed criteria, which are used based on real information extracted from the industrial town of Saujblag area, and each of the criteria is examined and analyzed in the following.

Soil erosion is one of the most important geomorphological processes on the earth's surface, which has accelerated due to human intervention. This process causes many damages such as loss of fertile soils, destruction of infrastructure and filling of dams. In the assessment of soil erosion, several factors should be used in a combined and integrated manner. In this regard, in basins without data or with limited data, a set of geomorphological indicators can be used in combination with other indicators and the erosion potential can be evaluated. In the current research, the erosion potential of Firouzabadchay catchment area located in Ardabil province has been evaluated. In this regard, 13 indicators, mainly geomorphological, were used. In order to combine and overlapped the layers, fuzzy logic was used in the context of the geographic information system (GIS). The results show the high potential of soil erosion in the surface of the Firozabad catchment area. Several factors are effective in the erodibility of the basin's soils, which in this context can be the wide outcrop of Quaternary alluvial formations, gypsum marls, lahar and volcanic ash, weak vegetation, predominance of steep slopes, high drainage density, existence of numerous streams, high values of roughness number and long slopes. In zones of the study basin where several factors affecting erosion have favorable conditions, the rate of erosion has intensified. In this regard, we can mention the central sub-basins of the study basin, which are among the critical areas of the basin due to the presence of alluvial and marl formations, weak vegetation, high slope, high drainage density and several other factors.

The 63.20 kV substations serve as the energy injection points from the transmission network to the distribution network. Determining the substation's location is important from both technical and economic perspectives for regional electricity companies and electricity distribution companies. This research aims to identify the optimal location for constructing a 63.20 kV substation, distinguishing its methodology from similar studies by considering criteria specific to electricity distribution companies and the internal interactions and influences of these criteria.

This study employs the network analysis process (ANP) and fuzzy logic within Geographic Information System (GIS). Based on expert evaluations, 13 criteria were identified as primary factors for substation location. ArcGIS software was utilized to create criteria layers. To standardize the criteria layers, data were normalized between 0 and 1 using fuzzy membership functions. The ANP method was then used to determine the final weightings of the criteria, which were applied to their corresponding fuzzy maps. For the final analysis, the gamma operator with the gamma values of 0.7, 0.8, and 0.9 was employed. Optimal gamma value selection was implemented using the gamma correlation coefficient test in SPSS software, leading to the calculation of the correlation coefficient and standard deviation.

The standard deviation calculations indicated that a gamma value of 0.7 has higher accuracy compared to other values. In the final map, areas around the city of Kahak were identified as the optimal location for constructing the 63.20 kV substation in Qom province

The most important factor in investing is choosing the asset that will bring us the highest expected return. Each investment forms its portfolio by predicting the investment risk and estimating the expected return. Various methods have been used to estimate the expected return on investment in recent decades, the most important of which is the Markowitz mean-variance model. But this model has been faced with flaws, so financial researchers have tried in the following decades to obtain more reliable findings for portfolio optimization by adding higher moments such as skewness and kurtosis and entropy. The statistical population of this research is based on trading data (adjusted price) of the top 35 symbols of the the Iranian capital market during the last ten years from 2013 to 2023 from the software bourseview, tsetmc, and the variables including variance, mean, skewness, kurtosis and entropy after processing. Data were implemented using Matlab version 6.7 software and portfolio optimization was done based on mv, mvs, mvsk models and finally MVSKE model. The findings of this research indicate that informational entropy is a reliable variable in portfolio optimization.

The precise and fair implementation of laws in the judicial policy of legal systems is inevitable. In two-value or Aristotelian logic, the foundations and principles of science are subject to a fixed rule that thing is either right or wrong. Fuzzy thinking in the interpretation and explanation of laws, both quantitatively and qualitatively, represents a special framework in the purposeful examination of ambiguities and uncertainties. Fuzzy thinking represents a special framework for the purposeful study of ambiguities and uncertainties in the application of laws, both quantitatively and qualitatively, therefore, the design of fuzzy thinking in measuring and explaining criminal and legal matters can be very effective in advancing towards criminal justice. Because the logic used in our laws, which has its roots and precepts in Islamic law, is multiple logic, and propositions and legal materials are often graded and used continuously with variables as examples. This study aims to try a new approach to explaining and interpreting laws based on fuzzy thinking in times of ambiguity and complexity and to help build a logical and equitable framework that leads to the development of rules based on legal variables and components. The result is that with the theory of explanation and interpretation of the existing laws based on fuzzy thinking, as well as the design and implementation of the fuzzy judicial system with the help of experts, it is possible to progress towards a more accurate and fair judicial system. Because the thinking and subjective criteria of the judges in interpreting the laws can be fuzzy and the judges also issue more fair verdicts. For example, to prevent crimes leading to imprisonment, which will reduce the number of prisoners. Therefore, the fuzzy thinking plan in evaluating and explaining legal issues can be very efficient in moving towards criminal and legal justice.

Analyzing user sentiments in marketing and enhancing customer experiences are essential for developing effective marketing strategies. This analysis is crucial for assessing the performance of social media platforms as communication tools. This research was practical in nature and cross-sectional in time, while utilizing both quantitative and qualitative variables within a descriptive research design. The study categorized user tweets without relying on prior knowledge or labeled data, employing fuzzy systems and an unsupervised approach. This advancement in sentiment analysis enabled researchers and practitioners to extract valuable insights from user opinions and emotions within their respective domains and platforms, thereby facilitating informed business decisions aimed at maximizing profitability. As a case study, this empirical research examined user experiences with Samsung and Apple mobile phones from 2022 to the present, classifying sentiments into positive, negative, and neutral categories. Three sentiment analysis tools—SentiWordNet, AFINN, and VADER—were employed to determine the polarity of the tweets. The classification results revealed a higher level of user satisfaction with Samsung mobile phones compared to Apple.

One of the structural factors in any organization is human resource management. Human power is the greatest asset of any organization in terms of having the power of thought, creativity and innovation. Performance evaluation is a method through which the process of identifying, observing, measuring and improving human performance in organizations is carried out. Some of the most important factors affecting the evaluation of employees' performance are: type of job, employee behavior, management method and determination of minimum salary. The basic purpose of using performance appraisal is to maximize productivity by identifying and capitalizing on employee strengths.A good performance evaluation system should have five features, which include simplicity and comprehensibility, especially from the perspective of the organization's employees, fairness, objectivity, openness, and usefulness. The purpose of the article is to determine indicators and models to evaluate employee performance and to determine the effect of a fuzzy decision support system on employee performance evaluation. Statistical Society; He is a social security employee of Mashhad city. Using data mining technology, we extracted human resource information from multiple databases about the status of the organization's personnel, then using the fuzzy evaluator model and the data extracted from the database, we were able to identify the types of forces and employees in the organization. Based on the features, it discovers and also determines what kind of features an employee belongs to​

 Today, urban furniture has been considered by city managers and planners due to its significant role in improving the quality of urban life. Therefore, a small change in the quality of each of its components has a direct impact on the quantity and quality of its components and other variables. The aim of this study is to evaluate the quality of urban furniture in regions 1 and 2 of Tabriz using fuzzy logic inference system in Matlab software environment. The present research is descriptive in terms of methodology and applied in terms of purpose. In order to collect data and information used in the research, the library and field survey method has been used. The components used in this study include two components of beauty and fit of urban furniture and urban furniture standard, each of which was examined in the form of three main indicators based on fuzzy logic inferences. The results showed that region 1 and 2 of Tabriz is not in a good position in terms of the quality of urban furniture with a score of 0.39 and 0.35, respectively, and has not been able to satisfy the people. Therefore, there is a need to review the approved urban furniture programs as well as to develop new programs based on the strengths and weaknesses of the areas under study.Finally, it should be noted that the use of comparative methods to assess the quality of furniture in different urban areas can provide a comprehensive view of recognizing the differences between areas in terms of urban facilities, the necessary planning to establish spatial justice between deprived areas and provided areas.

Systems for assessing groundwater vulnerability are designed to protect groundwater resources from pollution. The DRASTIC method is a well-known approach for determining groundwater susceptibility. One drawback of the DRASTIC method is that it relies on expert judgment to rank parameters, which introduces uncertainty. This study used a new generation of Fuzzy Logic (FL), called the Z-number theory, to estimate the specific vulnerability of aquifers and address this uncertainty. The specific vulnerability of the Ardabil and Qorveh-Dehgolan aquifers was estimated using two scenarios: the DRASTIC parameters as inputs and nitrate concentration values as output. The vulnerability of the aquifer was also evaluated by comparing the results of the proposed models with those of the DRASTIC model, which served as a benchmark. The analysis showed that the Z-number Based Modeling (ZBM), which considered data reliability and weighted the rules appropriately, produced higher-quality results than the classic FL. In the Ardabil plain, the ZBM yielded results that were 53% better (using seven inputs) and 184% better (using four inputs) compared to the classic FL. In the Qorveh-Dehgolan Plain (QDP), the ZBM produced results that were 127% better (using seven inputs) and 311% better (using four inputs) than the classic FL. The irregularity and non-linearity of the data, such as the high coefficient of variation (CV) in the Ardabil plain compared to the QDP, may contribute to the high CV value in the plains. Therefore, in plains with high CV, the quality of the extracted Z-number-based rules may be lower.

The concept of the fragility of the state is one of the key words in the political sciences that were considered in the post-World War II period, and especially after the end of the Cold War. The Central Asia has also been one of the geographic regions that has sparked many views and analyzes on the states in the region and their fragility. But it should be noted that the paths that lead to the fragility of governments are not the same, and it is possible to draw different patterns from the ways leading to the fragility of the state. According to this the main research question are, what is the state of fragility in the Central Asia? What are the characteristics of paths that lead to the fragility of the Central Asiaern states? Considering the exploratory nature of the main research question, no hypotheses have been presented and interpreted for the results. To answer the questions, with the benefit of fuzzy logic, the top paths that are created by the combination of several factors are examined. The survey also shows that 10 governments in the Central Asia are fragile states and can identify four causal paths among them. Also, among the factors involved in these causal paths, the government's lack of legitimacy and the existence of conflicting groups can be identified as an unnecessary imperative for the fragile states of the Central Asia.

Performance-based budgeting (PBB) aims to allocate public budget resources to organizations based on their performance. Consequently, the necessity of evaluating entities' performance in implementing and executing a performance-based budgeting system has spurred some researchers to expound PBB maturity models, while others have concentrated on designing models to gauge its maturity level. In this investigation, mindful of the developed model of performance-based budgeting in Iran, endeavors have been made to fashion a data envelopment analysis (DEA) model in harmony with the conceptual framework of PBB maturity. Considerations such as the network structure of the PBB maturity model, quantitative-qualitative data, and the hierarchical structure of indicators and sub-indicators within the PBB maturity model should be factored into the design of the mathematical model. Consequently, the primary aim of this article is to devise a two-stage-multilayer fuzzy network data envelopment analysis model that encompasses all three of these considerations and delineates the level of budgetary maturity based on performance for various entities. The outcomes indicate that taking into account the uncertainty present in the data and adjusting levels in optimistic, pessimistic, and moderate, while bolstering the discriminative power of the model, will furnish decision-makers with more precise information.