fuzzy inference system

Evaluation is one of the most important necessities in the process of urban regeneration, which leads to the optimal decision to solve the problem of urban inefficiency. Evaluating decisions in the urban regeneration process, given its complexity, ambiguity and uncertainty, is a critical issue that requires identifying the criteria that affect its realization and using fuzzy decision-making methods. The purpose of this study is to introduce a fuzzy Delphi method based on qualitative reasoning to identify and localize the criteria affecting urban regeneration. The research method is a combination of quantitative and qualitative methods. The present study is applied in terms of developmental goal and descriptive-analytical in terms of researcher action. The content analysis method was used to develop the conceptual model of the research and the fuzzy inference system (FIS) and Matlab and SPSS software were used to analyze the components and criteria of urban regeneration. To obtain the required data for the research, open and closed questionnaires were distributed among experts and the expert group. Then, the obtained data were entered into the fuzzy inference system and their output was considered as research findings. According to the results of the study, 18 criteria were identified to evaluate the regeneration policy. These criteria were reduced to 12 criteria in the final selection stage, which was done by Delphi interview method. The results show that the most important and insignificant components of urban regeneration in Qom are economic, functional, physical, managerial, social and environmental components, respectively. General Transportation and Access to Urban Management Safety and Health, Housing and Infrastructure.

In the last few decades, a decreasing trend is observed in livability of cities due to growth of technology and applying the modernity concept in the construction of cities, which causes the adverse effects on urban spaces. One of the most prominent of these effects, which can be called urban damage, is the decline of values associated with the sense of place in the formation of these spaces. This concern is especially highlighted in metropolises where technology has naturally grown faster. This study provides a framework to estimate the livability in Tehran metropolitan district 1 by considering the sense of place factors. In this way, a novel predictive model is developed based on the integration of Adaptive Neuro-Fuzzy Inference System (ANFIS) and Genetic Algorithm (GA). To this end, several variables based on the sense of place including physical body, meaning, activity, social capital, sense of place, and mental quality of life are considered as predictive variables. Results indicate that the ANFIS-GA model (R=0.926) is the most accurate predictive model when all input parameters are included. Besides, the social capital index has very little effect on livability and the importance of mental quality of life index is more significantly than other indices and can lead to more improvements in livability of regions than other factors.

Public satisfaction is a multidimensional and dynamic concept that changes over time, so it must be evaluated at appropriate times. A major challenge for this evaluation, especially in large geographical areas such as one country, is the lack of regular procedures and updated relevant index values. In recent years, several indicators have been presented based on traditional methods of data collection, including the use of questionnaires, to measure public satisfaction. Since, in recent years, the use of User Generated Geo-Content (UGGC) has been widely considered, in this research, with a new perspective by using of location-based social networks (LBSNs), extraction of information and criteria that can somehow reflect public satisfaction has been done. Finally, considering the uncertainties in the input data and the definition of public satisfaction, a fuzzy inference system was used to evaluate and compare public satisfaction in Iranian provinces. The extracted indices in this study, include negative/positive tweet ratio, the ratio of joy and love tweets to all tweets, and the ratio of sadness, anger and fear tweets to all tweets. The results of the proposed method resulted in the classification of the provinces of Iran from favorable to unfavorable situations. The results of this study demonstrated the potential of UGGC for public satisfaction assessment in the role of complementary data rather than as an alternative to official data. The proposed method in this study is a step towards evaluating public satisfaction using data shared by users on location-based social networks.

Due to recent drought and severe storms, Sistan plain has specific geographic conditions in Sistan and Baluchestan and the country, and this particularity has always led to the availability of special and sustainable species of vegetation. This research has investigated various tree species that are resistant to and adapted to the geographical conditions of Zabol city. Using Fuzzy Inference System model and AHP, these species have been studied in terms of ecological and socio-functional criteria. By mentioning different dimensions of weakness and strength of each tree Has prioritized them, so that, using its results, it would be possible to decide on the focus of investment and the choice of the most suitable species for cultivation. The results of this study indicate that among the six plant species studied, Eucalyptus trees and ornamental palms with the final weights (0.273 and 0.263) were the most suitable trees for planting, and in contrast to the decorative berry tree with the score (0.125), the most inappropriate tree for planting In ecological and social-functional conditions of Zabol.

The construction of power lines is one of the most important concerns of the electricity industry in the country. The cost of building these lines on the one hand and the interaction of environmental factors on these lines on the other hand has led to different parameters in the routing of these lines. All of these parameters are directly related to the location of the transmission towers and equipment. GIS has various capabilities, including the ability to retrieve, retrieve, update, display, process and analyze reference location information, thus providing a suitable platform in which to define different conditions and parameters as information layers. And, based on the patterns defined by different experts, it was combined and achieved the desired results. The design and implementation of a suitable route in accordance with the natural and environmental conditions and the evaluation and comparison of the designed route with the existing and operating route (Muhammad Abad Line) is the main objective of this research. In this research, in order to find the optimal path between two points of interest, the fuzzy inference model is first obtained using suitable points for rig installation and cost map. The AHP method was also used to weight the factors. Then using the Cost Path function the optimal path between two points is obtained. Also, in order to integrate the information, the weighting method to fuzzy inference rules was evaluated. Finally, the fuzzy gamma model was selected as the best model in the latter method and it was used for routing between Yazd I Post and T-OFF site of Mohammad Abad.

Many quantitative research’s (and some qualitative cases) has are been done on the role of small and medium size cities in regional development. The present article is also in this regard, but with a slight change in the structure of the breakdown in the approach to the subject and the analysis of the problem, and the multi-faceted analysis of the data using the Fuzzy Inference System. The purpose of the research, with regard to the title, is a developmental - application and has a descriptive - analytical approach. The FIS application and increasing approach has four stages (in general): its Database and Fuzzification, the rules base, the engine, and the Defuzzification, which is parallel to the research process. In the glimpse (Knowledge Base), regional development indicators (10 indicators) and variables (more than 70 variables) in four pillars of regional development (economic, physical, infrastructure and human development) for the small and middle cities of Kurdistan province (9 cities of the city centers Except for Saravabad) were selected and mapped during two periods of 2006 - 2016, and then a detailed analysis of the process was performed on the data. The final result

The tourism industry has become a major economic activity in the early years of the 21st Century and is considered one of the most productive and most employment-oriented global industries. Tourism is one of the most important factors generating wealth and employment in the world. It is necessary to plan for the proper exploitation of this industry, The most important steps to plan are to locate sites for providing tourists with the services they need in the form of tourist villages, This research is for the city of Shush which is one of the most important tourist areas of Khuzestan province And since it has many ancient monuments, it has attracted many tourists, , But the city has been at a very low level in terms of having a space worthy of tourists. Therefore, the conditions reinforced the idea of creating a tourism village. In this research, location-based discussion was conducted through a fuzzy inference system, Finally, the Fuzzy Topsis method has been used to protect the environment and to some extent extend sustainable tourism development. The ranking of these sites is based on environmental criteria. In the fuzzy inference system by applying the layers required in this method, four sites are considered to be very suitable.Then, using Fuzzy Topsis, which includes 10 criteria and 4 options, identified the best site on site 4. This site will bring the least damage to the environment, Located on the banks of the Dez River, most of the area has been covered by ground. In terms of maintaining environmental criteria, the site has a completely organic environment than other sites.

Energy is one of the essential components for industrial activities and the need of all people, therefore, its supply and demand is continually increasing in human societies. Population growth, its expansion and distribution, along with the ever-increasing human need for new and more efficient energy, have forced man to turn to natural renewable energies. The sun is considered to be the largest energy source in the world, which can be used in many ways. Being non-polluting, clean, free and accessible, are the important features for using renewable solar energy. Solar energy is one of the best and most economical renewable energy in Iran, which not only reduces many human concerns, such as environmental pollution, energy exhaustibility, energy conversion, etc., but also considering the climate of Iran, it can well develop in Iran. Despite the great potential of using solar energy in the country due to the intensity of radiation as well as a very good area for installation and use of solar energy, it is possible to install photovoltaic panels. Regarding the climate of Ahwaze city in terms of radiation intensity (According to the statistics of the New Energy Organization, about 4.5-5 kWh / m 2 / day) and sunny days and on the other hand, due to the establishment of important factories and large industries in the city, it faces the problem of energy and pollution caused by fossil fuels. Therefore, the study of solar energy and its potential for using solar energy to plan for the use of this energy seems necessary. Since no significant steps have been taken in this regard, this study focuses on this important issue, so that by designing a Web GIS system, one can take a step in the direction of data management and decision-making to improve the status quo.
The present research seeks to exploit renewable solar energy using solar technologies. The spatial distribution modeling of this renewable resource was performed using GIS analyses and computational intelligence. For this purpose, during the implementation of the survey, Solar Analyst Model available in ArcGIS software was used to estimate the solar radiation in the region. Also, in order to prioritize the region based on having the required potential to exploit solar photovoltaic systems, three categories of effective criteria including environmental criteria, building-density criteria and technical criteria were identified. Then, modeling was done using Fuzzy Inference System. The knowledge of available solar energy and the area of building rooftops are essential components for calculating the potential of electricity generation of photovoltaic systems, but there are technical considerations that must be taken into account in these calculations. In most cases, the calculation of photovoltaic potential requires the consideration of the output capacities of the panels. For this purpose, the technical potential of photovoltaic systems was calculated based on the formulas, the requirement of which is to estimate the geographic potential of the study area. The final stage is the design and implementation of the solar energy Web GIS system.
Discussion and Estimation of the total radiation received by the earth in the study area using Solar Analyst model, showed the total solar radiation from 0.4 to 1461 kWh per square meter per year. Also, the calculation of the geographic potential of the region and in particular the geographic potential of the rooftops, was performed using Digital Surface Model (DSM) and the results showed that major parts of the region had the potential from 1 to 49 kW per day. Technical potential of photovoltaic systems (Ei) for the roofs, was calculated using the geographical potential and its value varies from 0.1 to 138 kW per day. The results of fuzzy inference system shows that 10 square kilometers of the total area has a medium development priority and 0.7 square kilometers of the total area has a high development priority that form the highest and the lowest respectively.
Based on what has been stated so far, it can be said that the findings of the present study indicate the success of the integration of two Web GIS and solar energy knowledge in meeting predetermined objectives of the research. Utilizing this process, while providing the opportunity to assist in the decision-making process, provides web-based solar maps using spatial data. In fact, the designed system can be considered as a decision-making tool, if it allows users to view spatial information in the form of a map in addition to providing descriptive information about the region’s potential of energy generation. Users can use this system to identify appropriate locations for installing solar equipment and maximize their benefits.

Marand city is located in very dangerous zone in terms of seismicity status, Therefore the problem of temporary settlement and optimization of the population settlements in the occurrence of earthquake is very important. This study has been implemented with the aim of identifying and spatial modeling of temporary settlement area in order to manage the earthquake crisis. Eight effective criteria in modeling temporary settlement has been extracted by studying research theoretical foundations and using the opinions of experts, then by using two models; Fuzzy Analytic Hierarchy Process (FAHP) and Fuzzy Inference System (FIS), the area with proper conditions for temporary settlement in earthquake disaster management was determined. By comparing the results from the two models Based on expert’s opinions and Feasibility, optimization and practical of the Suggested zones among the zones with very good condition in Fuzzy Inference system, 232723 square meters And in the Fuzzy Analytical Hierarchy Process Model 44995 square meters, are Confirmed by experts and have most proper condition. The results indicates more accuracy in results of fuzzy inference system In comparison with fuzzy analytic hierarchy process.

uman life is highly dependent on the environment and the services that are provided by the environment. Environmental quality is a set of properties and characteristics of the environment, either generalized or local, as they may also impinge on human beings and other organisms. It is a measure of the condition of an environment relative to the requirements of one or more species and or to any human need or purpose. Environmental quality is a general term which can refer to varied characteristics that relate to the natural environment as well as the built environment, such as air and water purity or pollution, noise and the potential effects which such characteristics may have on physical and mental health caused by human activities.
THEORETICAL FRAMEWORK: Areas with better environmental conditions are more suitable contexts for life and human activities. Environmental quality is dependent on understanding the interaction between man and nature as well as the concept that forms the cornerstone of sustainable development. In general, environmental quality depends on the relationship between humans and the environment as well as the dominance of man over nature. The divergence of the human and environment results in the worsening of environmental conditions, resource depletion, and pollution of all kinds as well as social and spiritual problems.
2.1. Eco centrism vs. Anthropocentrism
The relationship between two motives underlying environmental attitudes was examined. These two environmental attitudes are eco centrism, which means valuing nature for its own sake, and anthropocentrism, which refers to valuing nature because of material or physical benefits it can provide for humans. From a philosophical viewpoint, anthropocentrism is based on this fact that human beings are the central or most significant entities in the world. Anthropocentrism regards humans as separate from and superior to nature and holds that human life has intrinsic value while other entities including animals, plants, mineral resources, and so on are resources that may justifiably be exploited for the benefit of humankind.
2.2. Economic Growth and Environmental Quality
The environmental Kuznets curve is a hypothesized relationship between various indicators of environmental degradation and income per capita. In the early stages of economic growth, degradation and pollution increase, but beyond some level of income per capita, which will vary for different indicators, the trend reverses meaning that at high-income levels economic growth leads to environmental improvement. This implies that the environmental impact indicator is an inverted U-shaped function of income per capita.
2.3. Ecosystem Services and Environmental Quality
Humankind benefits in a multitude of ways from ecosystems. Collectively, these benefits are known as ecosystem services. Ecosystem services are regularly involved in the provisioning of clean drinking water and the decomposition of wastes. Ecosystem services can be grouped into four broad categories including provisioning services (e.g., the production of food and water), regulating services (e.g., the control of climate and disease), supporting services (e.g., nutrient cycles and crop pollination), and cultural services (e.g., spiritual and recreational benefits).
The data for the present study were collected from rural areas of Ghochan in Khorasan Razavi and Faruj in North Khorasan province, Iran.
In order to address environmental quality in the study area, the evaluation criteria considered are as follows: 5 main components (soil and water resources, climate, physiography, environmental risk) and 15 criteria (climate, temperature, comfort, elevation, slop, landform, earthquake, flood, erosion, fault, soil, protected zones, water, vegetation cover). To assess the environmental quality, knowledge based systems, which are based on fuzzy inference system, were used. Fuzzy inference is the process of formulating the mapping from a given input to an output using fuzzy logic. The mapping then provides a basis from which decisions can be made, or patterns be discerned. The process of fuzzy inference involves all of the pieces that were described in the previous sections including membership functions, fuzzy logic operators, and if-then rules. There are two types of fuzzy inference systems that can be used, namely, Mamdani-type and Sugeno-type. These two types of inference systems vary somewhat in the way outputs are determined. In the present study, the Mamdani type was used.
3.1. Procedure
The data base was created for geographic information. Having used ArcGIS10.2, base maps were produced, modeled, and then, the data were analysis. The basic unit of study is based on square regular network which is same as raster data, but it is vector. A unique code was assigned to each spatial unit. Afterwards, the data were transferred to the base unit. The table of shape files were changed to text format, and then imported into excel and prepared for linking to Matlab. With function 'xlsread' in Matlab, were imported data into Matlab. The functional operations in fuzzy expert system pass through the following steps: fuzzification, fuzzy Inference (apply knowledge base), aggregation of all outputs, and defuzzification.
The data for the study were collected from the counties Ghochan and Faruj in Razavi and Northern Khorasan. This area is suitable for agriculture. Good rainfall and fertile plains provide a good environmental quality for living.
The results of survey have two output: 1) The knowledge base which to help the assessment of environmental quality. 2) Environmental quality map of Ghochan-Faruj. Components that are made of four input criteria such as water and soil resources, climate, and environmental risk create 81 rules ( ), and components that are made of three input criteria create 27 rules ( ). The advantage of decomposing of model is reduction of complexity of model. Before decomposing, with 15 criteria have to create 1438907 rule. The rule base help to predict status of environmental quality. Based on the knowledge base to assess the environmental quality in the study area have dealt. As a result of the evaluation, determined the suitability of location quality based on each of the components that encoded in the range of 0 to 1. Finally, with the help of gamma phase 4 layer overlayed with Γ = 0.6. Given the alpha cut equal to 0.7, about 65.53 % area, characterized of very good quality and less than 9% in terms of environmental quality are poor.

River flow estimation in every region is one of the fundamental and important issues in agricultural planning and also in the water resources management. Therefore presenting a suitable strategy is more beneficial to accurate estimation of rivers flow rate. The purpose of this research is to evaluate the capability of the intelligent models such as Gene Expression Programming, Artificial Neural Network and Nero-Fuzzy Inference Systems in order to estimate the flow rate in Mordagh Chay River. Three different methods are used to estimate the flow rate in these models, the flow rate data of the previous daily flow and the mixture of each of these states with one to five days of delay period in daily scale. Totally 45 kinds of different data were applied and the estimation was conducted. Mordagh Chay River basin has been located on Eastern Azerbaijan Province. The findings were compared with the observed data by coefficient of determination and the root mean square errors criteria. With regard to the results obtained from the models all of the three methods were of acceptable accuracy. Finally the adoptive Nero- fuzzy inference systems model was chosen for the highest precision and was recommended to be useful in this basin.

Earthquake is one of the most destructive natural disasters which frequently occurs with different intensities. Earthquakes cause severe damage to buildings, main roads and most importantly, loss of life. Detection of damaged buildings caused by such an event at the right time is a critical issue for crisis management and disaster relief. The aim of this study is to detect earthquake damaged buildings using very high resolution (VHR) satellite imagery. To achieve this result, the satellite images with very high resolution before and after the earthquake in Port-au-Prince in Haiti as well as the observed destruction map in 2010 were used. In this study, the optimum features extracted from the image were selected using correlation analysis. The buildings destroyed were classified using fuzzy inference system and the values of selected textures. Finally, the damage map obtained from the proposed algorithm was compared to the map of the area. The kappa criterion estimated from the results of the proposed method is 82% while the index- Jaccard parameter is 89.69%.

1- Establishing power transmission lines is one of the most important activities of ourcountry’s electricity industry. But great expense of the establishment on one hand, and mutual effects of natural and environmental causes on the other hand, make us to consider different parameters in route-finding of these lines. All these parameters are in direct relation with location of masts and power transmission lines’ equipment. 2- Methodology The method of study was incorporation of fuzzy and AHP for optimal rout –finding of power transmit ion lines. For the aim of this paper which is GIS application in electricity industry specially rout finding of power transmission of GIS software capabilities in electricity network and its function has been considered. 3– At first, usual and conventional methods of rout finding of transmission lines is presented, later the rout-finding direction of transmission lines including stages like; determining the study location, preparing conceptual model, selecting rout-finding method ad data structure, determining the effective factors in route-finding of power transmission lines, preparing the information, analyzing the data using MATLAB software, incorporating the information, locating the masts, evaluating routes and selecting the optimal route is covered in this research. In order to find the most optimal route between two intended points, first of all we need to write software in MATLAB environment and by using Fuzzy Interface System, the suitable points for setting the masts and measuring cost map would be available. Then we may get the shortest distance between the two points using Short Path Function. For weighting the factors used the AHP model. In order to incorporate the information different models of FIS would be examined. After road designing in GIS environment, each road should be evaluated in terms of environmental characteristic, standard observation, shortest regarding other routes to select an optimal route. Regarding this study aim which is an optimal rout selection of power transmission lines, 5 detected routs were compared base on deferent fuzzy rules (Table 1). Table 1: Route parameters calculatedbased on different operator for optimal rout Image MODEL PATH LENGTH(KM) Coincidence (%) QUALIFICATION fuzzy And 311.21 35% WEAK fuzzy Or 644.21 30% WEAK fuzzy Product 099.21 45% GOOD fuzzy Sum 750.20 40% MEDIUM probabilistic-OR 285.21 55% GOOD fuzzy Gamma 21.762 60% GOOD fuzzy Gamma IN Weighted Role 216.21 70% EXCELLENT In addition to these routs designed route by electricity engineers was selected as an index and obtained results were compared with each other. Finally, the rout optima by operator GAMA in weight rule have been selected as an optimal route (Fig1). Fig1: The comparison of Gamma fuzzy designed rout with existing rout.4– In the method, fuzzy inference which is actually the incorporation of AHP and fuzzy method was selected as the best method from experts point of view, because each rule was selected based on its relative importance. FuzzyProductmodel and probabilistic-OR model are better than other models after Gamma fuzzy and gamma fuzzy usingWeighted Role. Also, fuzzy model results have better modeling than linear models, this is because of the vagueness in the expert's view and nonlinear parameter dependence in rout finding of power transmission line. If rout finding of power transmission is done by paying attention to new factors and their role in rout finding, it is expected that better results to occur.

Mineral potential mapping process is introduced as a complex process due to the presence of multiple factors, variety of both quantitative and qualitative data to explore mineral deposits as well as the expertise and different interests. In this process, considering the fuzzy nature of mineral exploration in the process of modeling exploratory data, applying expert knowledge and flexibility for all types of mineral deposits in form of an integrated system play essential roles. To verify this, in the study, a new method has been presented using fuzzy inference systems and relations, and the mentioned method has been implemented in the ChahFiroozeh copper deposit.This study was conducted in two stages. First, the primary factor maps using asymmetric fuzzy relation analysis are weighted and using multilevel fuzzy comprehensive evaluation are combined together. And second, the factor maps which have been obtained in pervious stage, were integrated using a fuzzy inference system and then the mineral potential map has been generated.In the resulted mineral potential map, Porphyry copper mineralization prone area is located in central regions with north-south extension. For evaluation exploration boreholes in the area have been complying with the mineral potential map. The highest compliance rate in mineral potential map is calculated as 83.33%.

Today, in order to achieve more complete and precise information extracted from the complex and heavy hyperspectral data, there have been introduced more specialized and advanced methods for analyzing data. Among the effective methods is the spectral target detection algorithms, at the first step 14 algorithms have been evaluated in three groups, including deterministic measures, statistical measures and anomaly detection. Then the higher accuracy algorithms in each set have been selected as follows: Spectral Correlation Similarity (SCS) and Spectral Angle Measure (SAM) from deterministic measures set, Spectral Information Divergence (SID) and Jeffries-Matusita Distance (JMD) from statistical measures set, and Covariance-based Matched Filter Measure (CMFM), Constrained Energy minimizing (CEM) and Correlation-based Matched Filter Measure (RMFM) from anomaly detection set. These seven algorithms are fused by different strategies and methods. There were two strategies, including sequential and simultaneous fusion too. In the sequential fusion strategy, the mentioned selected algorithms from each set were fused in the first step and their results were fused in the second step by using these four Boolean, Euclidian, Fuzzy Inference System (FIS) and Adaptive Neuro-Fuzzy Inference System (ANFIS) fusion. In the simultaneous fusion strategy, the results of the mentioned seven algorithms were fused at once by ANFIS method. The experiments on the roof detection application, through a compact Airborne Spectrographic Imager (CASI) hyperspectral imagery, taken from one of the Toulouse urban areas in southern France, showed that the simultaneous fusion strategy via ANFIS was the most precise automatic one among other primary and synthetic target detection methods.