fuzzy logic

Today, knowledge-based businesses are important in the two dimensions of science production and knowledge-based economy development. The special conditions of these businesses, such as being new, focused on creativity, communication with other organizations, and the use of various capacities, have caused the challenges related to this category to be given more attention. The purpose of this article is to provide an interpretative structural model for the challenges of marine knowledge-based businesses that are not in the formation stage but in the structural and communication maturity stage. In this research, library studies and literature review were used to calculate the criteria related to maritime knowledge-based trans-bureaucratic organization, and in order to identify the obstacles and challenges that are the main variables of the research, the questionnaire tool and the content analysis approach were used. . The statistical population of the research is 11 specialists and experts in the field of marine technologies, whose opinions have been collected using the Delphi technique and analyzed by combining the research approach in soft operations and fuzzy logic. Fuzzy logic pays attention to the degree and intensity of the relationship between elements according to the opinions of experts and makes the final model more valid. Based on the results of the research, the challenges of "management based on open relationships and high trust" and "success-seeking spirit, idealism and excellence-seeking human capital" have been placed at the level of a model and are always influential and influential. are high "Financial, technical, business and commercial risks",

Various  political interventions have cast a shadow on the Iran’s foreign trade, and not considering them for analyzing the target markets, will make the results unrealistic and biased. The purpose of this research is to evaluate the efficiency of exports through the modification of the gravity model by considering policy variables. Two methods of modified stochastic boundary gravity model with fuzzy logic (A) and normal gravity model (B) have been used. The research data was collected from 33 major importing countries of Iran's pistachio and saffron during the period of years 2001 to 2020. The results showed that in the medium term (2016-2020), the export efficiency were about 39% and 29% for saffron and pistachio respectively. The greatest potential in pattern A is related to the UAE, Spain, Hong Kong, China and Afghanistan. While by removing political variables in most countries such as China, the potential is lower and in some countries such as Japan, the export potential is estimated to be higher. The average potential of pistachios in the recent period was 56.4 million dollars in pattern A and 53.5 million dollars in pattern B. The comparison between the results of model A and B showed that in most of the period, the effect of political interventions has reduced the export potential in countries that do not have friendly political relations with Iran, such as USA and Japan.

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

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.

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.

A well-defined roadmap is essential for any country to achieve social, economic, welfare, and cultural advancement. Such a roadmap clarifies national priorities and issues, enabling targeted attention, strengthening, and investment in critical areas. Recognizing the importance of these priorities and the value of cross-government comparisons, this study undertakes a comparative analysis of general welfare and social security policies in Iran’s 8th (Khatami) and 9th (Ahmadinejad) administrations, utilizing fuzzy logic. The research is applied in its purpose and comparative in nature, relying on library resources and high-level documents from the two presidential terms. In the theoretical section, books, journals, and databases are referenced, while in the empirical section, fuzzy logic techniques are used to analyze data. Data evaluation was conducted using fuzzy logic model tests, and SPSS software (version 22) was employed for statistical inference. Results indicate that the level of welfare and comfort was higher during the ninth administration, with citizens experiencing better housing, access to basic goods, and civic interactions. However, general welfare support was less extensive, though substantial housing support was provided for lower-income social classes. These findings highlight that social welfare in Iran is strongly connected to the specific policies of each government.

The purpose of this research is to investigate the impact of environmental stimuli on the implementation of the agility policy in logistics villages of Tehran province. The current research is applicable-developmental in terms of purpose. The statistical population of the research includes managing directors and members of the board of directors, deputies, managers and heads and supervisors of different departments of logistics villages in Tehran province, whose number is 99 and the sampling method is total number. The information collecting tool was the questionnaire of environmental stimuli made by the researcher, taken from the qualitative section. The reliability of the research was checked and confirmed using Cronbach's alpha criterion in SPSS software. SPSS software was also used for data analysis, and PLS software was used for structural equation modeling. The findings of the research showed that the acceptance percentage of the language term "very high pressure and impact" is confirmed for the category of the impact of environmental stimuli on the implementation of the agility policy of the administrative system of logistics villages in Tehran province, and also the model has a good fit.

Natural disasters such as earthquakes can cause irreparable damage to humans and the environment. Earthquakes are considered as natural disasters that cause many human and financial losses every year. Today, with the advancement of science and technology, suitable grounds have been provided for recognizing and reducing these natural hazards. Therefore, risk assessment is critical for proper management and reduction of losses. Risk assessment is determined by the process of estimating the probability of an event occurring, and the importance or severity of its adverse effects. The aim of this study was to assess the vulnerability of Bushehr province to earthquake risk. In this regard, by combining fuzzy and hierarchical logic models using GIS software, the vulnerability of Bushehr province to earthquake risk has been analyzed and extracted. Effective indicators in earthquake vulnerability are: distance from the fault, earthquake epicenter, earthquake magnitude, earthquake depth, land slope and lithology. The results show that 23% of Bushehr province, which is mostly located along faults, are very vulnerable in the danger zone.

In this research, the intelligent model of preventive maintenance and repairs based on artificial neural network methodology - fuzzy logic with the help of artificial intelligence environment of MATLAB software based on the structure of Falcon's five-layer model of artificial neural networks is presented, the research method is based on systems thinking. After determining the most important factors affecting preventive maintenance and repairs with the help of a questionnaire and based on a dataset of 2,000 samples of data and reports of the Director General of Textile and Clothing Industries of the Ministry of Safety during the years 1396 to 1401 (in the form of six and a half years) and validity Data evaluation by the maintenance and repair experts of 240 industrial units, a smart model was designed, which after the implementation of the model in Borujerd textile factories as the place of implementation of the plan can be claimed if (If); Five "technology" factors have values of 0.9129; Good condition (upper bound of good membership function), "Employees" has values of 0.9239; good condition (upper bound of good membership function), "working environment" has values of 0.8859; relatively good (lower limit of the membership function), "quality" has values of 0.9999; Perfect condition (highest function), "strategy" has values of 0.9999; good status (upper limit) in preventive maintenance and repairs, then: the status of the output variable of the research, i.e."Optimization of preventive maintenance and repairs performance (Y)" will be at its fifth level, i.e. very good, equal to 0.882.

The current research was conducted with the aim of providing a fuzzy model for the evaluation of business plans focused on the development of new products. This research can be used in the industrial cluster of chemical production and systematically examines and analyzes the development of new products. It is an exploratory-modeling research method in terms of practical purpose and in terms of implementation. . In this research, the present research community consists of 12 experts from chemical industry companies. In order to analyze the data, fuzzy Delphi technique has been used. The results show that 6 exogenous variables were selected as key variables in the selection and development of a new product in the organization. In order to determine the importance of exogenous variables that experts doubt in specifying their importance, the method of fuzzy fuzzy analysis technique was used. (0.239), new product development strategy (0.209), level of passing standards and requirements (0.136), absorption of product development research funding (0.077) and absorption of applied research funding (0.061). The dynamic product development model, which is based on the cause and effect relationship, needs to be designed and tested in future studies to simulate the current and future decision-making performance.

Today, the maximum utilization of human capital for organizations has become inevitable for reasons such as the rapid development of various technologies in response to increasing demand to increase production and reduce costs. Accordingly, in the present study, we decided to identify and prioritize the factors affecting coaching in improving human resource training in the Social Security Organization.

This research is based on the purpose in the category of applied research. The sample of the present study consists of 10 specialists and experts in the field of coaching and training of human resources.

The results of the study indicate the fact that out of 31 variables affecting the role of coaching in improving human resource training, 16 top indicators were identified and prioritized. Based on the results, the role of coaching through the education channel on reducing information and motivational barriers, respectively; The reduction of content barriers and the reduction of structural barriers are in the first to third ranks.

According to the results of the effect of coaching on human resource training in the Social Security Organization is a multidimensional process and coordination between human resource needs assessment processes (reduction of information and motivational barriers), planning (reduction of content barriers) and implementation and evaluation (reduction of structural barriers) Increase the effectiveness of training courses through the channel of the coaching process.

The present study was applied in terms of purpose and In terms of the descriptive research method, it is a survey with a comparative causal approach. A number of 100 companies listed on the Tehran Stock Exchange in 2014 to 2019 were selected as a sample. Data were collected from the databases of the Central Bank of Iran, Statistics Center of Iran, Codal website, and WDI website and Tehran Stock Exchange website, and then analyzed using Excel, 9Eviews, and Matlab software. In this study, the determinants of venture capital on the Tehran Stock Exchange (capital volume, export volume, company tax, disclosure index, rule of law index, industry diversity, diversity of company life cycle stages, type of property, number of divisions and subsidiaries, company capital, company, size and company age) By studying the research literature and using neural network and fuzzy logic, a predictive model was created to determine the investment risk based on the determined indicators.. The classification model was presented using neural network without SOM supervision and fuzzy logic flexibility. The evaluation parameters of design, accuracy of the proposed ensemble classifier, mean error of the squares, and coefficient of explanation. The simulation results indicated that the performance of the proposed design compared to the classification by MLP neural network method was improved and the presented model based on the training provided predicted the status of capital with good accuracy.

Today, the construction industry has a significant share of the economy and is considered as a leading and employment-generating industry. Due to various and sometimes risky activities during construction, there is a possibility of risks and personal and financial injuries, the control of which can be very effective in the success of the project. In the present study, a model for evaluating the safety risks of construction projects has been presented and new powerful tools such as fuzzy expert system improved with genetic algorithm have been used. Therefore, at first, the main factors influencing the safety of construction projects were identified by studying the literature and consulting with experts. Then, a questionnaire was provided to the experts to obtain their views and assess the severity of the risk effect and the probability of the occurrence of each risk. Then, based on the experts’ views, an expert system was obtained to assess the risks, which instead of using zero and one logic, governing expert systems, fuzzy logic was used. In the proposed model, to improve the performance of the fuzzy expert system, the genetic algorithm was employed as an optimizer. The research results indicated the optimal performance of the proposed model in assessing the safety risks of construction projects, so that the error rate of the model was acceptable. The model can also provide an effective tool for project managers in assessing and refining the safety situation in the construction site.

The meaning of BPR is that we overview and breakdown current business process. This method, by using more efficient processes, enables your company to decrease costs and increase profitability.This research has been attempted to evaluate and ranking the indicators which are effective on BPR, in order to improve efficiency of industries by using fuzzy ANP combined methodology. The study population of this research can be classified into two general groups: first group is the masters of university who are expert in BPR, second group is experts working in manufacturing industries. Actually the sampling method in this research is a combination of targeted non-probability sampling method and snowball sampling. Due to the nature of the sampling method, finally the sample volume of this study is equal to 30 person of Experts available and willing to cooperate. Due to the finall analysis and prioritizing criteria, it is visible that “technological and educational factors” with final weight of 0.252; “Empowerment” with weight of 0.177; “organizational culture” with weight of 0.122; has been defined as the most important ANP integrated model criteria for BPR in order to improve the efficiency of manufacturing industries.

Environmental management systems and supply chain management are complementary, and their implementation not only improves the environment within the country, but can also increase the sustainability and environmental performance of the global supply chain. The present study evaluates the supply chain management in the pharmaceutical system of selected public hospitals in Mazandaran province.

A questionnaire was designed and completed by experts to rank the factors affecting the evaluation of supply chain management in the pharmaceutical system. After collecting the data, they were analyzed using fuzzy hierarchical analysis technique. For this purpose, by studying the research background, various factors and models were identified and the conceptual model of the research was presented by experts in four categories of main criteria and 16 sub-criteria. These factors include: managerial and employee factors, economic factors, organizational factors and cultural factors.

The results showed that economic factors with a weight of 0.266 are the most important in terms of experts and have the first rank, followed by managerial and employee factors, organizational factors and cultural factors, respectively. Also, among the sub-criteria, the factors of adopting a business strategy commensurate with environmental goals with a weight of 0.0936, first place, designing a competitive business plan for optimal price and quality with a weight of 0.0878, second place, and modeling the trade policies of leading countries with a weight of 0.0846, third place. Has earned.

Given the importance of factor-related criteria in the implementation of supply chain management, this article examines the factors that affect managers to help find a suitable model for their future investment plans.

This study is struggled to reply this question; the existence of the strategic alignment in the international marketing domain would caused export performance improvement. After that a decision support system (DSS) about export strategy alignment is presented. This research from the view of objective is a casual research and because of the research presents a model in the strategic level for export strategies, it is a developmental research. The study performed in Iran’s petrochemical companies which had export performance. The level of analysis is organization. The method of data gathering for export performance is external secondary data (Industrial Management Org. reports about IMI500 and the financial statement of the companies) and for determining the degree of strategic alignment the strategic reference points (SRP's) theory is applied. The result shows that: (1) Higher export strategies alignment caused increasing in the export performance, (2) Fuzzy measurements of strategic alignment and export performance caused a more accurate statement for reality, (3) In this research the utility of the fuzzy model to present a DSS for management has approved.

Coaching is one of the methods of staff training that is used for the growth of human resources. On the basis of the present research to identify and prioritize the factors affecting social security organizations have managed to improve education. This research is in applied research category. The research sample is 16 coaching and training experts. In the next phase of the procedure for considering the uncertainty of Non-rank compared Electre Tuesday to increase the priority was used. Based on the results, reducing information and motivational barriers, respectively; The reduction of content barriers and the reduction of structural barriers are in the first to third ranks. According to the PLS results, if the coaching process index increases by one unit, the training process will increase by 0.849 units. According to the results of the process of the effect of coaching on training is a multidimensional process and coordination between the processes of manpower needs assessment (reduction of information and motivational barriers), planning (reduction of content barriers) and implementation and evaluation (reduction of structural barriers), the effectiveness of training courses The coaching process builds more.