جستجوی مقالات مرتبط با کلیدواژه « fuzzy » در نشریات گروه « مهندسی آب »

Comprehensive evaluation of organization performance is one of the most powerful tools for decision making. It helps managers to gain necessary information about the status of their organization. One of the most widely welcomed models in this regard is the Balanced Scorecard Model which provides comprehensive evaluation for various aspects in the Water and Wastewater Corporation. The present study was a descriptive-applied research in terms of objectives. The objectives included selecting a comprehensive evaluation pattern, recognizing and ranking the indexes and main sub-standards for evaluating the comprehensive performance with BSC model denoting various parts in water and wastewater corporations. The model was used in West Azarbayjan province water and wastewater company as a pilot. Data collection was based on the library and field study via 3 types of questionnaires and interview with staff, financial staff, and by the customers of the given company. Based on the correlation and regression coefficients, the mean variables test and the fuzzy method showed that the BSC fields are in the order of priority in the performance of the mentioned company. These included internal processes, learning and growth, and customer and financial perspective. In the regression dependent variable model, the performance of the company and independent variables included various variables in fields of the balanced scorecards, and the result showed that the most effective factors on the company performance were decreasing the unnecessary costs, increasing and developing new facilities, finding new custumers, providing infrastructures, and organizational resources through learning, increasing customer satisfaction, enhancing the efficiency and quality of the internal processes.

Supply of safe water as well as sanitation services are, as economic activities, the main purpose of the water and wastewater Company. To meet these goals there is a need to great financial supply as well as justified planning and optimized use of all facilities and talents available. One of the main challenges in this regard is the cost management which leads to increase in efficiency. This is why monitoring of efficiency in Water and Wastewater companies is vital. In this study group decision-making method is implemented using paired comparisons questionnaire to rank the costs of activities in West Azerbaijan Rural Water and Wastewater Company by fuzzy AHP approach. Then by applying the obtained weights typical model of measuring efficiency is provided. Result show that water costs with weight of 0.1458 and equipment costs with weight of 0.1446 are in priority. Total efficiency factor has a large fluctuation, which in this company with an average of 0.37 units. This is mainly due to reduced efficiencies in energy section and in human resources section. Applying the results of ranking and prioritizing the performance of the various types of company costs leads to more concerns on the necessary and unnecessary costs, without mistreating its core or basic functions.

Management of groundwater resources, especially in arid and semi-arid areas, has great importance. Natural and anthropogenic phenomena in recent decades have caused critical conditions and fall in groundwater table. In such situations artificial recharge of groundwater is amongst the most important management strategies. Purpose of this study is the use of AHP and statistical methods (fuzzy-statistical ranking and parameters optimization of artificial recharge model based on nonlinear regression and sensitivity analysis) to determine suitable areas of artificial groundwater recharge in Kashan aquifer. In this study, SMAGR artificial recharge model was used for site selection artificial recharge in Kashan aquifer based on seven parameters of groundwater contamination (GC), soil infiltration rate (IR), capability of hydraulic conductivity (HC), soil pollution (SP), land use (LU), topographic slope (TS), and water table (WT). Adding layer of aquifer pollution risk was also used for site selection of suitable areas based on considerations of groundwater environmental conditions. The information layers were prepared in GIS environment and the fuzzy-statistical rating was combined based on geometric mean with equal weights. In addition, removal sensitivity analysis was used to determine the effective weight of parameters and to optimize the model. Based on the results obtained from statistical method and optimized model about 15% and 0.1% of the western and southern parts of aquifer are suitable to very suitable for artificial recharge. Also the sensitivity of the model showed a decreasing trend associated to different parameters of removed groundwater contamination, soil infiltration rate, hydraulic conductivity, soil pollution, land use, topographic slope and water table with effective weights of 2.96, 2.83, 2.41, 2.33, 2.21, 2.07 and 1.89, respectively.

In recent decades, the application of intelligent evolutionary methods and hybrid models for forecasting groundwater spatiotemporal fluctuations were more focused by researchers. Genetic algorithm and Neuro-Fuzzy are new methods which are applicable in single and hybrid forms for forecasting in complex and nonlinear problems. In this research, aforementioned methods were applied to study the Hadishahr plain aquifer. The Hadishahr plain is located in the north of East Azerbaijan province and it is a part of Julfa–Duzal study area. This aquifer suffers from groundwater level declination due to groundwater withdrawal increase. To achieve practical ways for spatio-temporal groundwater level forecasting, the artificial intelligence methods such as neuro–fuzzy (NF), genetic programming (GP) and combination their best model with geostatistical methods were used. Precipitation and evaporation in t0 time step and groundwater table in t0-1 time step were the inputs to the Neuro-Fuzzy and Genetic Programming. The results showed that the average RMSE of selective piezometers for genetic programming and neuro-fuzzy were 19 and 23 centimeter in the test step, respectively. Then, genetic programming was used to present a hybrid model in combination with the geostatistical model (kriging). Finally, the hybrid model “genetic - kriging” were applied to predict the spatiotemporal prediction of the groundwater level. The simulated results were extended to the whole plain and the area with no groundwater level monitoring network.

In this study, an adaptive neuro-fuzzy inference system (ANFIS) has been applied to model activated sludge wastewater treatment process of Mobin petrochemical company. The correlation coefficients between the input variables and the output variable were calculated to determine the input with the highest influence on the output (the quality of the outlet flow) in order to compare three neuro-fuzzy structures with different number of parameters. The predictions of the neuro-fuzzy models were compared with those of multilayer artificial neural network models with similar structure. The comparison indicated that both methods resulted in flexible, robust and effective models for the activated sludge system. Moreover, the root mean square of the error for neuro-fuzzy and neural network models were 5.14 and 6.59, respectively, which means the former is the superior method.

Water resources are among basics for sustainable development. The non uniform temporal and spatial distribution of water resources is led to shortage water in arid and semi arid regions. The inter basin water transfer projects are one remedy to this problem. According to the diversity of the feasible water transfer projects, ranking of the projects with different criteria is currently one of the important issues in water resources management. Fuzzy Multiple Criteria Decision Making (FMADM) is a collection of methodologies which can be used to compare, select, or rank multiple alternatives that typically involve incommensurate attributes. The aim of this research was to use some of the fuzzy multiple attribute group decision making methods for ranking some inter-basin water transfer projects of Karoon River, western Iran. Maximizing and minimizing sets method, the Bonissone’s method for group decision making, Fuzzy TOPSIS for group decision making, and Fuzzy Decision Making software were used in this study. A set of 10 interbasin water transfer projects with 8 criteria were considered. First, the weight of each criterion was determined within a group of five water resources experts, Then the rating preference for each alternative were obtained by the samegroup of experts. Finally, the results of different methods were compared. The results showed that the Tunnel Koohrang 1 posses the higher rank. Also, the Spearman rank correlation coefficient was obtained between different methods. The results showed that the Fuzzy TOPSIS and Bonissone method provide the best correlation. For evaluating the criteria weightings, the sensitivity analysis was conducted and the results were compared.

River flow forecasting in water resources management is of great importance. But, due to the high uncertainty in the factors affecting the rainfall-runoff process, the results are usually problematic. One of the procedures that can alleviate this problem is incorporating uncertainty analysis in forecasted results. Such an analysis has been traditionally used for statistical methods but less attention has been given to the Artificial Neural Networks (ANNs) and the Neuro- Fuzzy (ANFIS) models. These models have gained much popularity in recent years. This research has aimed to analyze the uncertainty of these techniques for 1 to 3 months forecasting of river flow. Sofy-Chay River at Tazekand gauging station in the northwest of Iran is selected as the study site to explore the methodology. The results show that ANFIS overall gave more accurate forecasts and less uncertainty. But, when it comes to high flows, the confidence interval for the two models increases quite obviously and this increases the risk for application of the results.

Dealing with Water Scarcity is one of the important probleme in water resources management. There is no one of financial capability to execute all the water resources projects in onelot, so it is important to rank execution projects. In this study, one of the fuzzy multiple attribute decision making methods was employed for ranking some of the inter-basin water transfer projects, by using different critaria and modifying the Raj and Kumar method for both benefit and cost critaria conditions. The approach has been applied to the Karun river basin. For ranking alternatives, first critaria and their weight were determined and then 10 inter-basin water resources projects of Karun river with 8 critaria were considered. The weight of each criterion determined by 5 water resources experts. The fuzzy weights of alternatives are computed by using standard fuzzy arithmatic. The concept of maximizing snd minimizing sets are used to computed the total utility of each of alternatives. Finally, the results of maximizing and minimizing method were compared to FDM software.