fuzzy inference system (fis)

The risk of natural hazards, particularly earthquakes, is a highly significant concern in urban environments. In this research, the initial phase entails estimating the vulnerability map of the building blocks in Kermanshah metropolis, as well as determining the number of individuals at risk during an earthquake. Subsequently, the research identifies and introduces safe zones or suitable locations for accommodating the vulnerable population during such seismic events. For the first part, the vulnerability map was obtained using maps of distance from faults, the structural integrity of the buildings, the strength of the building blocks, and the size of the infrastructure. A fuzzy inference system was utilized. Thus, the high-risk blocks were determined, and their population was estimated. In the second part of the research, distance maps derived from rivers, faults, high-voltage power lines, electric substations, fuel stations, roads, hospitals, fire stations, and police stations were used. These generated maps have then undergone fuzzification, and the weight of the criteria employed has been assessed using the fuzzy hierarchical analysis process (FAHP). Subsequently, by applying the weight associated with each criterion to the corresponding map and merging the resultant maps, maps depicting the suitability for temporal settlement of the vulnerable population during an earthquake were obtained. Finally, the most optimal inner-city and outer-city sites for individuals' lodging amid an earthquake have been chosen. Moreover, certain locations inside the suggested sites and their capacity were assessed. The field research revealed that the selected sites involve the expected conditions for settlement after the earthquake.

Having an integrated model of change management can simplify the inherent complexity of change by recognizing the relation between critical elements. Because of dynamic nature of variables and their interaction, developing a static model is not useful. This study tries to generate a new method for constructing a dynamic organizational change model in four steps with combining qualitative methods (content analysis and Delphi technique) and artificial neural networks (Fuzzy theory and genetic algorithm). In addition, by governing restrictions of various conditions, a road map is provided for managers to leading change. After recognizing and screening variables by qualitative methods, due to the complexity and scale of the problem the initial model is built with fuzzy theory and genetic algorithms are used for more accuracy. For governing restrictions and finding acceptable amount of variables to have a successful change program, genetic algorithm is used.

Energy is one of the necessary factors for industrial activities and a requirement for today life. Hence، demand and supply of energy in human society is increasing continuously. Population growth and its distribution، along with the increasing need of human being to newer and more efficient energy resources have changed the human approaches to natural renewable energy forms. Since the fossil fuels as the primary fuels of are going to exhaust rapidly and cannot be a reliable energy source as well as due to the global warming issue، the use of fossil fuels should be limited as soon as possible. Henceforth، renewable energy resources were proposed to solve these challenges. Solar energy is one of the best and most economical renewable energy in Iran. This energy not only can resolve many human concerns such as environmental pollutions، newborn diseases، energy finitude، and energy transformation، but can also be well developed in climate of Iran. As the photovoltaic systems are one of the most efficient systems in producing solar electricity and can be employed in a vast area of Iran، a significant proportion of energy consumption of Iran can be supplied by developing these systems. Photovoltaic cells transform solar energy into electricity directly. In this process، semiconductor materials such as Silicon، Gallium Arsenide، or Cadmium Telluride are used. Today، about 95 percent of the world solar cells are made of Silicon. Since the prime cost for establishing photovoltaic field is relatively high، optimizing the establishment sites of these systems can play a key role in increasing the efficiency of the system. The aim of this study is to introduce a new method for spatial optimization of the sites of photovoltaic fields in Iran. In this research the DELPHI technique was employed to identify the effective factors. The DELPHI is a systematic process for collecting and classifying the knowledge of experts through distributing questionnaire between the experts and studying the feedbacks. After the DELPHI technique carried out، 14 criteria were extracted and then classified into three main groups. In order to weight the criteria، the Analytical Network Process was employed. To do so، the pairwise comparison questionnaire was produced and distributed to the experts. According to the results derived from the questionnaire، the pairwise comparisons were done in Super Decision software and the weight of each criterion was calculated. An initiated model is introduced to combine Simple Additive Weighting method and Fuzzy Inference System. In the mentioned technique، the main entrance of the final layer is a result of Simple Additive Weighting. Primarily، the concluded layer from the Simple Additive Weighting was classified into six classes of very poor، poor، moderate، good، very good، and excellent using the trapezoidal membership functions and then the fuzzy laws were defined based on the requirement of the research. After the output distribution map was concluded for each law، all outputs were added together and the whole study area was divided into seven areas of inappropriate، very poor، poor، moderate، good، very good، and excellent. Finally، the experts'' viewpoints were used to estimate the accuracy of the results and according to the average of the results، the accuracy of the estimated sites is approximately 84 percent. The results indicated that the most effective factors on feasibility of lands in Iran to establish photovoltaic fields are 14 criteria in which the criteria of direct radiation، distance from the power lines، and temperature are of the most importance. However، except for the inappropriate class (mainly because of high slope and improper land use)، most of the regions (more than 31 percent of lands of Iran) are in classes of excellent، very good and good. Furthermore، only one percent of the lands are in class 1 (the class poor). According to the results، Provinces of Yazd، Kerman، South Khorasan، Sistan and Balouchestan، Isfahan، Fars، and Khorasan e Razavi، in order، have the most area in the class excellent، and Provinces of Guilan، and Mazandaran have the most area in the class very poor. Proper use of solar energy requires the identification of highly potential regions. Besides the benefits of using the photovoltaic technology، one of the difficulties of these technologies is the high cost of establishing such power plants. Therefore، recognizing the best regions for installing the photovoltaic equipments could be the main step in the establishment of photovoltaic power plants. In this article، authors have tried to introduce an applied method for optimizing the sites of photovoltaic equipment installation to have the most efficiency and lifetime. The results showed that Iran has very high potential to utilize the photovoltaic technology.

New product development (NPD) as modern approach applied for facing to environmental changes and is necessary to enter and remain (or survive) in competitive environment and achieve competitive advantages. Firms according to identify the critical success factors (CSF) of NPD and obtain the profitable results from these factor, can achieve competitive advantages. Researchers analysis CSFs of NPD in 35 years and concluded that managing of new product is more important factor. The important of NPD in complex and product system (CoPS) is highlighted. The firm can assess the process whit CSF’s and improve the process and achieve effectiveness of activities.Studying the relevant article and literature reviews, 40 factors influencing the success of NPD has identified in this paper. Applying fuzzy inference system (FIS) and studying some aerospace project as NPD projects that is relevant with CoPS, in the next step, input variety (the level of activity of factor in NPD projects and the level of project success from the viewpoint) and indicator (cost, time and quality of NPD’s product) are analyzed. The MATLAB software and SAJENO model of FIS were applied for analyzing of data. As result, the selected CSF’s whit brainstorming is categorized in 3 groups: development team abilities, organizational resources and organizational process and 20 factors as CSF of NPD identified and prioritized. Thus, focusing in these factors, managers can achieve the competitive advantages.

Urban Transportation Planning (UTP) has been one of the most important decisions in urban planning and development procedures in recent years. Meanwhile, accurate trip forecasting between two given regions of the city could be considered as the key success factor of urban transportation planning. Due to the importance of the problem, different models have been developed in the field. The overall problem of trip forecasting and transportation planning could be complicated because of its nature that results from the complicated nature of human behavior. Due to the complexity of the problem, it is always hard to develop forecasting models with acceptable forecasting errors and also low computational expenses particularly in developing countries in which historical data are not fully available.
In this paper, a three phase fuzzy model is proposed to forecast trips flow between two given regions of a metropolitan based on mapping demographical and social variables to total number of trips flow. The overall model is to explore the subjective pattern of transportation experts and transfer the subjective model to a mathematical framework.