fuzzy inference

Shipping industries in ports, as one of the strategic industries, have performed an important role in the optimized management of the transportation business in a country.in particular on country's economy. The future status of port’s business management can be seen in planning , access to new technology in order to smartness, access to logistics, increase in specialized human resources and the impact of ports globalization. For this reason, the ports have to provide their services in a suitable qualification to plan for their development and demands supply.There have been major changes in ships technology that have affected the needs related to the construction and development of the port. Furthermore, the process of these changes will be more than this in the future which will have a direct effects on technology and the port’s facilities, In this article, in order to promote the ports and shipping industry, firstly, the main indicators of green and smart ports are identified by library studding and then interviews are conducted using the thematic analysis system approach. Next, the conceptual pattern of the research was drawn. Consequently, each index in the drawn pattern and the final index are evaluated in MATLAB software by (FIS). So, it is possible to determine the smartness and environmental indicators in the ports of the country for the first time. In this regard, Anzali port, one of the country's most important ports, will be implemented as a real example.

The creation of industrial clusters is a new form of development that aims to increase regional development. Undoubtedly, industrial groups play a pivotal role in the economic and industrial policies of many developed and developing countries. Due to the nature of the problem and the research propositions, a descriptive-survey research method was used in this research. Given that one of the research goals is to use the results of the findings to solve problems in the organization, then it is applied research. To determine the level and prioritize the identified factors, 25 experts and specialists in the fields of leather and footwear industrial clusters in the Industrial Estates Company, Industrial Department, Standard Office, Governor's Office, and also university professors were used. To collect the data and information required for this research, a modeling questionnaire of innovative shoe and leather industrial cluster establishment strategies has been used to become competitive using the fuzzy inference method. Also, in the second stage, the model of industrial clusters was developed using a fuzzy inference system (FIS). The results of this study lead to the design of solutions for establishing innovative shoe and leather industrial clusters to become competitive using the fuzzy inference method. With the completion of the present study, a practical step will be taken in managers' decision-making.

the health of administration and overshadow public interests. Therefore, this research has been carried out with the aim of presenting a management model of Trading in Iran's public Agencies. In order to form the expert group, 15 experts from the ministries and subordinate organizations who had expert conditions were selected by available sampling method. To test the model, the statistical population including 800 employees of the Information Technology Organization was considered. Also, 260 people were selected as a statistical sample using Morgan's table and simple random sampling method. The required data was collected through a researcher-made questionnaire, whose validity and reliability were confirmed through quantitative methods. In order to analyze the data, Lisrel software and Delphi technique and fuzzy inference system in the form of MATLAB software were used. The results showed that the model has three individual, organizational and cultural dimensions, and the organizational dimension with a factor loading of 0.83 has the largest contribution in explaining administrative Trading. Also, the individual value system component with a factor of 0.6 has the largest contribution in explaining the individual dimension; The ineffective evaluation system component with a factor loading of 0.75 has the largest contribution in explaining the organizational dimension and the short-sighted component with a factor loading of 0.75 has the largest contribution in explaining the cultural dimension. The results of the fuzzy inference system also showed that the minimum level of Trading in the organization is 0.464, and most of it is caused by individual Trading tendencies. In addition, the management of organizational and cultural factors has a significant impact on the control of administrative Trading. Based on the results, it can be said that paying attention to employing competent and ethical people is the first step in dealing with administrative Trading.

The aim of this study is to develop a systematic implementation method of Article 44 and to turn to the materials mentioned in the above principle, to provide a privatization model as a case study in the IRA Railway Company based on the fuzzy inference approach. The statistical population of this study was a group of university professors, specialists, managers and experts familiar with the field of railway and railway industry and the sample size was selected based on the chain method or snowball, 10 people. Data analysis was performed using fuzzy inference approach using MATLAB software. The results showed that the most desirable method for privatization in railways is the management contract method, the desirability of which was equal to 0.859, in which the cultural factor was the most effective component and the economic factor was the least effective component. On the other hand, the methods of offering shares to the public (0.822) with the priority of political and legal factor and the contracting method (0.810) with the priority of information factor were in the next ranks. Also, the lowest desirability was obtained for the method of decomposing larger units into smaller units with a value of 0.608.

This research is an applied research in the field of organizational knowledge management and its main goal is to improve the process of knowledge acquisition in the studied organization. For this purpose, a fuzzy expert system has been designed to suggest the most suitable knowledge acquisition technique and after validation, it has been implemented and used in two departments of this organization.

This research is a descriptive research in terms of method. The knowledge required to design an expert system includes theoretical knowledge and practical knowledge.The theoretical support of the research was prepared by the method of library studies and the review of scientific sources, but the required practical knowledge was obtained by the questionnaire tool and by the field method. Fuzzy Delphi method was used to determine system inputs and T- Student method was used to determine system outputs. Data analysis was also done with SPSS and Excel software. Finally, Fuzzy toolbox of MATLAB software was used to design and test the system, and for validation, the system error rate was calculated.

The findings of the research include determining 9 knowledge acquisition techniques that can be used in the organization, as system output, determining 7 factors influencing the selection of knowledge acquisition technique as system input, explaining 184 fuzzy rules to form the required knowledge base and in Finally, the design of the fuzzy expert system suggests the appropriate technique of knowledge acquisition.

The designed system was implemented in two subsets of the studied organization (a educational center and a research center). In the educational center, the "concept map" technique and in the research center, the "round table" technique was suggested by the system as the most appropriate technique.

Today's complex environment confronts organizations with the constant challenge of achieving their goals. The existence of a performance appraisal system to monitor the performance of the organization in achieving goals is inevitable. Organizations in today's competitive environment are successful in putting their performance appraisal on the agenda with high accuracy. Therefore, the main purpose of this paper is to provide an integrated model to evaluate the performance of decision-making units with appropriate resolution. The research has a descriptive-explanatory aspect in terms of method. In terms of research orientation, it is developmental and has used survey strategies. The statistical population includes university experts in Semnan, 57 of whom were randomly selected. Data collection tool has made two researcher-made questionnaires whose content validity and structure based on experts' opinion and factor analysis and their reliability based on Cronbach's alpha value more than 0.7 have been confirmed. Fuzzy inference rules based on the opinion of five experts University selection was compiled. "Data Envelopment Analysis" was also used to evaluate the performance of the mathematical planning approach. Findings show that the resolution of decision-making units in the proposed model is more appropriate than conventional approaches to integrating indicators.

In today's competitive world where innovation is a condition for the survival of any organization, it is important to know the level of innovation capacity of the organization's resources, which is related to organizational policy, technology transfer, life and competition of the organization. The main purpose of this research is to design a model to determine and predict the level of innovation of organizational resources. After reviewing the available sources and interviewing experts, using confirmatory factor analysis, 12 main indicators in the form of 3 dimensions were determined as input to the fuzzy inference system. Among the new modeling methods, fuzzy systems have a special place in various sciences. Neuro-adaptive fuzzy inference system (ANFIS) is a good way to solve nonlinear problems. This method is a combination of fuzzy inference and artificial neural network that uses the ability of both to model. Using three types of model design methods in the fuzzy system and comparing the results, the best result for presentation was determined. To evaluate the performance of the model, the parameters of squared mean square error (RMSE), relative error percentage (ε), mean absolute error (MAE) and coefficient of determination (R2) were used, which were 0.047, 1.02%, 0.046 and 989 / Is achieved and indicates the accuracy and reliability of the model. This research is applied in terms of purpose and survey type according to the data collection method. The output of this study is ANFIS.

Implementing an effective recruitment process is directly related to the performance of the organization. the shortage of talent is the biggest Barrier to growth in the organizations, This study aimed to design the optimal model of elite recruitment in public agencies. Research has a quantitative and qualitative approach. In the qualitative part, a hybrid technique was used to achieve the appropriate model. At this point, after identifying elite categories, concepts, and codes, an initial conceptual model was formed. In the next step, mathematical modeling technique (fuzzy expert system) in MATLAB software was used to achieve the desired combination of dimensions. The results showed that in the ideal combination the coefficient of ssocio-cultural factor is 11%, economic factor is 16%, political-legal factor is 12%, job attractions is 17%, organizational attractions is 10%, cultural attractions is 17% and ideal attractions is 15%. Therefore, enhancing job attractions such as challenging jobs, competing salaries and competencies, job-to-employee fit, outsourcing, job security, utilizing up-to-date technology, and creating opportunities for advancement and promotion can facilitate the recruitment of elites. Concerning cultural attractions, it will also be important to respect the principle of meritocracy in installing, promoting justice, elite respect, and promoting a culture of elitism and central talent in attracting elites to government agencies.

The aim of this study is to develop a systematic implementation method of Article 44 and to turn to the materials mentioned in the above principle, to provide a privatization model as a case study in the IRA Railway Company based on the fuzzy inference approach. The present study was a descriptive-survey research in terms of applied purpose and based on its nature and method. The statistical population of this study was a group of university professors, specialists, managers and experts familiar with the field of railway and railway industry and the sample size was selected based on the chain method or snowball, 10 people. Data analysis was performed using fuzzy inference approach using MATLAB software. The results showed that the most desirable method for privatization in railways is the management contract method, the desirability of which was equal to 0.859, in which the cultural factor was the most effective component and the economic factor was the least effective component. On the other hand, the methods of offering shares to the public (0.822) with the priority of political and legal factor and the contracting method (0.810) with the priority of information factor were in the next ranks. Also, the lowest desirability was obtained for the method of decomposing larger units into smaller units with a value of 0.608. Therefore, it is necessary for the managers of the railway industry to use the best method in privatization methods according to the requirements of this industry.

Roadmap and especially technology roadmap is a management tool and technique to achieve future goals in order to link business to technology. With the increasing trend and the need to use different types of roadmaps, new tools are needed to analyze the complex relationships between layers and roadmap elements. The purpose of this study is to focus on a new tool for analyzing the relationships between roadmap layers with a combined method with a proposed framework. Previous research has addressed relationships between layers only with tools such as quality function deployment (QFD) and the linking grid. Although DSM and TRM have been extensively studied independently so far, this study, therefore, proposes an integrated six-step framework combining a multi-domain matrix and design structure matrix and fuzzy set theory in designing, creating, and developing technology roadmaps for Suggest systems to support decision making and case studies. In this study, multi-domain MDM matrix and fuzzy inference, and network theory were used in designing the technology roadmap. The advantage of using a multi-domain matrix is ​​the simultaneous analysis of each domain specifically in the DSM format as well as the entire domain in the MDM format. The results of the present study indicate the provision of detailed instructions for managers to prepare a suitable roadmap.

Global competition and rapid changes in demand and the need for agile supplies have increased the importance of knowledge management as a strategic issue and a source of competitive advantage in supply chains. Choosing a knowledge management strategy in supply chains is important, because if the right strategy is not adopted with the supply chain, the knowledge management success probability in the supply chain will decrease. In the first step of the present study, the variables affecting the knowledge management strategy in the supply chain are identified and a model for strategy selection is proposed. In this model, supply chain strategy, cultural factors, distribution network structure, knowledge-intensive areas, knowledge creation and dissemination processes, human resources approach and information technology maturity of the supply chain are examined, respectively, and the relationship of each one with system-oriented and human-oriented KM strategies is specified. In order to validate the model, the opinions of experts in the field of knowledge management are used. In the next step, in order to model the effect of factors on strategy selection, a fuzzy inference system is designed using the MATLAB software. Iran Khodro company's is selected as a case study and the factors affecting the knowledge management strategy in this company's supply chain are examined, based on the opinions of chain managers and using the proposed model and system. The results show that the appropriate strategy for this chain is a system-oriented strategy, and finally the supply chain knowledge management strategies based on the selected strategy are presented to the company under study. The proposed system in this study can be used to select the knowledge management strategy in any supply chain.

Human resource branding is a relatively new approach taken from the field of "marketing" which is regarded as the essence of human resource marketing. This emerging arena provides a tremendous opportunity for enhancing human resource assumptions and stabilizing estate organizations as brands. This mixed-method study was undertaken to design an optimal model of human resource brand in estate organizations based on the Fuzzy Inference Method. The first phase of the study, thus, employed a qualitative method to propose a comprehensive model of human resource branding. Further, the initial conceptual model of the research was formed after the categories, concepts and codes of the human resource brand were identified.In the second phase, the mathematical model of Fuzzy Expert System was employed to provide a desirable combination of the components of the model that could optimize the human resource brand. The findings emerging from the study revealed that human resource brand of the organization employees can be optimized by 49.5 if they concentrate on organizational values (13.3%), cultural values (17.7%), social values (44.2%), Iranian-Islamic cultural values (76.3%), Individual competencies (29.9%), professional competencies (88.6%), and employer's brand (29.3%).

Accommodating needs and supplies and presenting superior value to the customers are among the main goals of customer relationship management (CRM) and their effectiveness has a crucial role in gaining competitive advantage. Accordingly, the aim of this paper is presenting a model to evaluate the effectiveness of CRM through fuzzy approach. The statistical population consists of the customers of Tabriz-Kar Machine Manufacturing Industry. To do this, the researcher designed a questionnaire according to Kim & Kim (2009) viewpoint, and its validity and reliability were measured and approved. To conduct the research, a five-stage model was designed based on fuzzy logic. In the first phase, a fuzzy system was designed with the four dimensions of effective CRM as its inputs and the CRM effectiveness score as its output. In the second phase, the inputs and outputs were converted to fuzzy numbers after the classification. In the third phase, inference rules were explained, and in the fourth phase, defuzzification was carried out. In the final stage the model was tested and the results showed the validity of the model. Finally, by using the designed model, the effectiveness rate of CRM in Tabriz-Kar Machine Manufacturing Company was evaluated.The results show that the effectiveness of CRM in the company with the membership degree of 0.748 is on average rate.

Nowadays expert systems are used as one of the most useful and most practical decision support systems. These systems are relying on knowledge of experts in certain domain combines valuable experience with speed and accuracy of computer and improve the quality of their judgments. One of the most extensive applications of these systems is medical diagnostic fields. Different from what happened in most prior researches in the development of expert systems, in the present study using the situational logic in the process of knowledge acquisition and fuzzy inference engine architecture approach is recommended. Identify the type of epilepsy has always been one of the most challenging deliberations among the neurologist doctors and strict distinction between the types of the disease, according to the closely signs Creates conflict among the field's doctors that the expert system is able to solve this problem with the accuracy of 83 percent. Forming a comprehensive knowledge base using analysis of competing hypotheses (ACH) modeling in order to distinguish between 14 types of epilepsy disease is the distinctive features of this study. Research done on the project can be used to diagnose other diseases that have similar symptoms closely and to be pragmatic. The proposed system can be used in situations where access to neurologist doctors is impossible can be very useful.

In this context and for helping to manufacturing industries in this research an attempt has been made to provide a method to managers of evaluating and ranking of agility strategies by using of a fuzzy inference system which is a branch of artificial intelligence. This research has been performed in three sequential phases. Firstly، some variables، as factors of agility drivers، agility capabilities and agility strategies، have been extracted from literature of research. Agility driver factors of industry، based on importance of attention and responsibility، have been ranked by using fuzzy TOPSIS technique and key drivers have been selected. Secondly، agility capabilities، based on the effect of capability to overcome the key drivers، have been ranked with the use of fuzzy TOPSIS technique and then essential capabilities have been selected. Lastly، the strategies، based on the effect of strategies to improve the essential capabilities، have been evaluated by planning and using a fuzzy inference system.