A rock mass classification model for caving roofs

Summary Evaluation of the caving behaviour of longwall roof rocks has thus far been based on a pot-pourri of classification systems, which ignore basic caving criteria. The paper outlines a new classification model of roof strata namely cavability using fuzzy set methodology and linguistic variables to assign ratings for individual roof beds. A microcomputer program has been developed to evaluate the decision ratings for cavability and the model applied to ten longwall case-histories from Indian coalfields. The classification model has excellent potential for being used as a standard tool for the evaluation of caving behaviour of longwall roof rocks.     

Landfill site selection by decision-making tools based on fuzzy multi-attribute decision-making method

Landfill site selection is a complex and time-consuming process, which requires evaluation of several factors where many different attributes are taken into account. Decision makers always have some difficulties in making the right decision in the multiple attribute environments. After identifying candidate sites, these sites should be ranked using decision-making methods. This study applies Chang’s fuzzy AHP-based multiple attribute decision-making (MADM) method for selection of the best site of landfills based on a set of decision criteria. The Fuzzy Analytic Hierarchy Process (FAHP) was designed to make pairwise comparisons of selected criteria by domain experts for assigning weights to the decision criteria. Analytic Hierarchy Process (AHP) is used to make pairwise comparisons and assign weights to the decision criteria. It is easier for a decision maker to describe a value for an alternative by using linguistic terms and fuzzy numbers. In the fuzzy-based AHP method, the rating of each alternative was described using the expression of triangular fuzzy membership functions. Once the global weights of the criteria is calculated by AHP, they are incorporated into the decision matrices composed by decision maker and passed to fuzzy-AHP method which is used to determine preference order of siting alternatives. In this study, a computer program based on the Chang’s fuzzy method was also developed in MATLAB environment for ranking and selecting the landfill site. As an example of the proposed methodology, four different hypothetical areas were chosen and implemented to demonstrate the effectiveness of the program. By using this program, the precision was improved in comparison with traditional methods and computational time required for ranking and selecting the suitable landfill site was significantly reduced.     

A new approach for forest fire risk modeling using fuzzy AHP and GIS in Hyrcanian forests of Iran

The presented research was performed in order to model the fire risk in a part of Hyrcanian forests of Iran. The fuzzy sets integrated with analytic hierarchy process (AHP) in a decision-making algorithm using geographic information system (GIS) was used to model the fire risk in the study area. The used factors included four major criteria (topographic, biologic, climatic, and human factors) and their 17 sub-criteria. Fuzzy AHP method was used for estimating the importance (weight) of the effective factors in forest fire. Based on this modeling method, the expert ideas were used to express the relative importance and priority of the major criteria and sub-criteria in forest fire risk in the study area. The expert ideas mean was analyzed based on fuzzy extent analysis. Then, the fuzzy weights of criteria and sub-criteria were obtained. The major criteria models and fire risk model were presented based on these fuzzy weights. On the other hand, the spatial data of 17 sub-criteria were provided and organized in GIS to obtain the sub-criteria maps. Each sub-criterion map was converted to raster format and it was reclassified based on risk of its classes to fire occurrence. Then, all sub-criteria maps were converted to fuzzy format using fuzzy membership function in GIS. The fuzzy map of each major criterion (topographic, biologic, climatic, and human criteria) was obtained by weighted overlay of its sub-criteria fuzzy maps considering to major criterion model in GIS. Finally, the fuzzy map of fire risk was obtained by weighted overlay of major criteria fuzzy maps considering to fire risk model in GIS. The actual fire map was used for validation of fire risk model and map. The results showed that the fuzzy estimated weights of human, biologic, climatic, and topographic criteria in fire risk were 0.301, 0.2595, 0.2315, and 0.208, respectively. The results obtained from the fire risk map showed that 38.74% of the study area has very high and high risk for fire occurrence. Results of validation of the fire risk map showed that 80% of the actual fires were located in the very high and high risk areas in fire risk map. It can show the acceptable accuracy of the fire risk model and map obtained from fuzzy AHP in this study. The obtained fire risk map can be used as a decision support system for predicting of the future fires in the study area.     

Fuzzy set approaches to classification of rock masses

Rock mass classification is analogous to multi-feature pattern recognition problem. The objective is to assign a rock mass to one of the pre-defined classes using a given set of criteria. This process involves a number of subjective uncertainties stemming from: (a) qualitative (linguistic) criteria; (b) sharp class boundaries; (c) fixed rating (or weight) scales; and (d) variable input reliability. Fuzzy set theory enables a soft approach to account for these uncertainties by allowing the expert to participate in this process in several ways. Hence, this study was designed to investigate the earlier fuzzy rock mass classification attempts and to devise improved methodologies to utilize the theory more accurately and efficiently. As in the earlier studies, the Rock Mass Rating (RMR) system was adopted as a reference conventional classification system because of its simple linear aggregation.

The proposed classification approach is based on the concept of partial fuzzy sets representing the variable importance or recognition power of each criterion in the universal domain of rock mass quality. The method enables one to evaluate rock mass quality using any set of criteria, and it is easy to implement. To reduce uncertainties due to project- and lithology-dependent variations, partial membership functions were formulated considering shallow (<200 m) tunneling in granitic rock masses. This facilitated a detailed expression of the variations in the classification power of each criterion along the corresponding universal domains. The binary relationship tables generated using these functions were processed not to derive a single class but rather to plot criterion contribution trends (stacked area graphs) and belief surface contours, which proved to be very satisfactory in difficult decision situations. Four input scenarios were selected to demonstrate the efficiency of the proposed approach in different situations and with reference to the earlier approaches.     

Selection of wastewater treatment process based on the analytical hierarchy process and fuzzy analytical hierarchy process methods

This paper presents an application of the analytical hierarchy process and fuzzy analytical hierarchy process methods for selecting the best wastewater treatment process. The analytical hierarchy process is one of the best ways for deciding among the complex criteria structure in different levels, and the fuzzy analytical hierarchy process is a synthetic extension of the classical method when the fuzziness of the decision makers are considered. After reviewing aerobic treatment processes operated in Iran’s industrial estates and determining the main criteria used for treatment process evaluation, they are arranged in a hierarchy structure. Selection of the best wastewater treatment process is a multi-criteria decision making problem. Conventional methods are inadequate for dealing with the imprecise or vague nature of linguistic assessment. To overcome this difficulty, the fuzzy analytical hierarchy process is proposed for dealing with the vagueness of decision makers’ judgments. The alternatives consist of extended aeration, absorption bio-oxidation, integrated fixed-film activated sludge, sequencing batch reactor, aerated lagoon. Based on the general condition of industrial estate’s wastewater treatment plants, technical/administrative, economic and environmental criteria and their sub-criteria are weighted and then criteria evaluated and priorities of alternatives have been done by analytical hierarchy process and fuzzy analytical hierarchy process methods by the use of triangular fuzzy numbers. Finally, selection of the best process and ranking of these five processes are carried out by these foregoing methods, and some sensitivity analyses are conducted to show the results’ sensitiveness to the changes of the weights of the evaluation criteria.     

Comprehensive modeling of mineral potential mapping by integration of multiset geosciences data

This work has evaluated the functionality of various fuzzy-based fusion methods in the mineral potential mapping (MPM), by which a multi-criteria decision-making problem was solved to design a layout for drilling complementary boreholes through a comprehensive analysis of geospatial datasets. The novel methods employed were fuzzy c-means clustering, fuzzy gamma operator, fuzzy inference system (FIS), fuzzy outranking, and fuzzy ordered weighted averaging (FOWA). Kahang porphyry Cu-Mo deposit in the Isfahan province of Iran was chosen as a case study to examine the performance of these fuzzy methods in MPM. Extracted geospatial indicator layers for assessing the potential of porphyry-type mineralization were derived from four criteria, namely geology (rock units and faults), remote sensing (alteration map), geochemistry (Cu, Mo, and factor maps), and geophysics (reduced to the pole and analytical signal of magnetic data). The concentration-area multifractal method was utilized to reclassify each synthesized fuzzy favorability map into five classes. To appraise and compare the efficiency of each employed method, a productivity measure assumed as a cumulative summation of Cu grade multiplied by its thickness above an economical cut-off value of 0.2% was calculated along with each drilling (totally 33 ones). According to fuzzy favorability maps derived from running all fuzzy methods, the FIS and FOWA had the highest efficiency with 80 and 78% of accuracy, respectively. Eventually, taking all fuzzy maps into account led to the delineation of some new favorable zones, whereby further exploratory investigations are envisioned for determining their mining potential.     

Landfill site selection using integrated fuzzy logic and analytic network process (F-ANP)

Locating a suitable place to dispose the municipal solid wastes hygienically (sanitary landfill) is one of the fundamental subjects relating the environmental stability of cities and, in general, the human settlements. This final stage of solid waste management requires observance of a series of principles and criteria mainly including environmental, social, economical, and general acceptance criteria. The set of these criteria along with their sub-criteria causes some complexities in decision making for landfill site selection. Considering effective parameters and criteria, we developed an integrated fuzzy logic and analytic network process (i.e. F-ANP) to locate a suitable location for landfilling municipal solid wastes generated in Kahak Town, Qom, Iran. Our findings revealed that integration of fuzzy logic and ANP can give better idea compared with other models like AHP, fuzzy logic, and ANP (individually). Therefore, this model can be applied in site selection for landfill of other similar places.     

DEFLOGIC: a method for assessment of groundwater potential in karst terrains: Gurpi Anticline,southwest Iran

A new hydro-tectonic model, includes eight layers that affect karst hydrogeology was proposed for mapping of groundwater potential in karst areas of Gurpi Anticline, southwest Iran. To produce the groundwater potential map, remote sensing (RS) and GIS techniques were combined with fuzzy logic modeling. Criterion maps include the distances from discharge sites (D), the elevation difference from discharge sites (E), the distance from fractures (F), the fracture length density (L), the slope (O), the lithology (G), the distance from fractures intersections (I), and the fractures intersection density (C) were produced using GIS and RS techniques (DEFLOGIC layers). The approach of fuzzy sets was used to commensurate criterion maps, then fuzzy algebraic sum and gamma operators were applied to aggregate them. The weights of parameters of DEFLOGIC proposed in the range of 1 to 5, which standardized between 0 to 1, based on their importance in karst hydrogeology, professional judgments, and available exploration data. The final groundwater potential maps were verified by geoelectric and well-drilling data. The potential map prepared using fuzzy gamma operator with γ?=?0.92, which it is a flexible distinctive parameters of sum and product of fuzzy operator, depicts the best coincidence with exploration data. The final DEFLOGIC map shows the high groundwater potential in karst formations between Hati and Pebde valleys. The results support the efficiency of DEFLOGIC model to evaluating of groundwater potential in karst terrains, especially in Zagros ranges.     

A comparative study of conventional, ANN black box, fuzzy and combined neural and fuzzy weighting procedures for landslide susceptibility zonation in Darjeeling Himalayas

Landslides are one of the most destructive phenomena of nature that cause damage to both property and life every year, and therefore, landslide susceptibility zonation (LSZ) is necessary for planning future developmental activities. In this paper, apart from conventional weighting system, objective weight assignment procedures based on techniques such as artificial neural network (ANN), fuzzy set theory and combined neural and fuzzy set theory have been assessed for preparation of LSZ maps in a part of the Darjeeling Himalayas. Relevant thematic layers pertaining to the causative factors have been generated using remote sensing data, field surveys and Geographic Information System (GIS) tools. In conventional weighting system, weights and ratings to the causative factors and their categories are assigned based on the experience and knowledge of experts about the subject and the study area to prepare the LSZ map (designated here as Map I). In the context of objective weight assignments, initially the ANN as the black box approach has been used to directly produce an LSZ map (Map II). In this approach, however, the weights assigned are hidden to the analyst. Next, the fuzzy set theory has then been implemented to determine the membership values for each category of the thematic layer using the cosine amplitude method (similarity method). These memberships are used as ratings for each category of the thematic layer. Assuming weights of each thematic layer as one (or constant), these ratings of the categories are used for the generation of another LSZ map (Map III). Subsequently, a novel weight assignment procedure based on ANN is implemented to assign the weights to each thematic layer objectively. Finally, weights of each thematic layer are combined with fuzzy set derived ratings to produce another LSZ map (Map IV). The maps I–IV have been evaluated statistically based on field data of existing landslides. Amongst all the procedures, the LSZ map based on combined neural and fuzzy weighting (i.e., Map IV) has been found to be significantly better than others, as in this case only 2.3% of the total area is found to be categorized as very high susceptibility zone and contains 30.1% of the existing landslide area.     

Decision making under uncertainty using a qualitative TOPSIS method for selecting sustainable energy alternatives

Multi-criteria decision-making methods support decision makers in all stages of the decision-making process by providing useful data. However, criteria are not always certain as uncertainty is a feature of the real world. MCDM methods under uncertainty and fuzzy systems are accepted as suitable techniques in conflicting problems that cannot be represented by numerical values, in particular in energy analysis and planning. In this paper, a modified TOPSIS method for multi-criteria group decision-making with qualitative linguistic labels is proposed. This method addresses uncertainty considering different levels of precision. Each decision maker’s judgment on the performance of alternatives with respect to each criterion is expressed by qualitative linguistic labels. The new method takes into account linguistic data provided by the decision makers without any previous aggregation. Decision maker judgments are incorporated into the proposed method to generate a complete ranking of alternatives. An application in energy planning is presented as an illustrative case example in which energy policy alternatives are ranked. Seven energy alternatives under nine criteria were evaluated according to the opinion of three environmental and energy experts. The weights of the criteria are determined by fuzzy AHP, and the alternatives are ranked using qualitative TOPSIS. The proposed approach is compared with a modified fuzzy TOPSIS method, showing the advantages of the proposed approach when dealing with linguistic assessments to model uncertainty and imprecision. Although the new approach requires less cognitive effort to decision makers, it yields similar results.     

Use of fuzzy synthetic evaluation for assessment of groundwater quality for drinking usage: a case study of Southern Haryana,India

A method based on concept of fuzzy set theory has been used for decision-making for the assessment of physico-chemical quality of groundwater for drinking purposes. Conventional methods for water quality assessment do not consider the uncertainties involved either in measurement of water quality parameters or in the limits provided by the regulatory bodies. Fuzzy synthetic evaluation model gives the certainty levels for the quality class of the water based on the prescribed limit of various regulatory bodies and opinion of the experts from the field of drinking water quality. In this paper, application of fuzzy rule based optimization model is illustrated with twenty groundwater samples from Sohna town of Gurgaon district of Southern Haryana, India. These samples were analysed for 15 different physico-chemical parameters, out of them nine important parameters were used for the quality assessment using fuzzy synthetic evaluation approach. From this study, it has been concluded that all the water samples are in acceptable category whose certainty level ranges from 44 to 100%. Water from these sources can be used for the drinking purposes if alternate water source is not available without any health concern on the basis of physico-chemical characteristics.     

Site selection in municipal solid waste management with extended VIKOR method under fuzzy environment

Nowadays, selection of the suitable disposal site in municipal solid waste (MSW) management has become a challenge task for the municipal authorities, especially in fast-growing areas. Site selection can be viewed as a complicated multi-criteria decision-making (MCDM) problem requiring consideration of multiple alternative solutions and conflicting quantitative and qualitative criteria. In this paper, linguistic variables, which can be expressed as trapezoidal fuzzy numbers, are used to assess the ratings and weights for the selection criteria. The ordered weighted averaging operator is utilized to transform the fuzzy decision matrix into crisp values considering the decision maker’s attitudinal character. For selecting the best site, the extended VIsekriterijumska optimizacija i KOmpromisno Resenje (VIKOR) method is applied to determine the priority ranking of alternatives. As a result, a hierarchy MCDM model based on fuzzy set theory and VIKOR method is proposed to deal with the site selection problems in the MSW management system. An empirical study in Shanghai, China, is provided and comparison with the existing approach is conducted to illustrate the applicability and benefits of the proposed method.     

Earth dam site selection using the analytic hierarchy process (AHP): a case study in the west of Iran

Earth dam site selection is one of the most important problems in water resources management. It depends on a set of qualitative and quantitative criteria, and they may even be in conflict with each other. This study aims to develop a multicriteria decision-making approach to locate the dam site and construct a multipurpose earth dam in Harsin City at the western part of Iran. For this purpose, firstly, the influential criteria for locating the earth dam site were determined using a comprehensive literature review and the experts’ opinions. Then, some watersheds in the surrounding areas of Iran’s Harsin City were studied and four feasible sites proposed. In the final stage, these sites, in order to construct a multipurpose earth dam, were prioritized using the analytic hierarchy process approach and the most optimal site was selected.     

Recognition of an enhanced multi-element geochemical signature of porphyry copper deposits for vectoring into mineralized zones and delimiting exploration targets in Jiroft area,SE Iran

Delimiting exploration targets using geochemical exploration data can be a challenging issue when different geochemical signatures represent the same deposit-type sought. In this regard, fuzzy operators have been used to integrate different geochemical evidence layers into a single model for generating target areas. In this paper, a GIS-based expected value function was adapted to integrate different geochemical evidence layers into a stronger geochemical signature for delimiting exploration targets. Then, the expected value function and fuzzy operators were compared. The comparison demonstrated that the former is more efficient than the later for generating a stronger geochemical evidence layer. The higher efficiency of the expected value function is because it simultaneously uses the value of all input variables and their relative importance in the process of integration. The proposed approach was evaluated by using a lithogeochemical data set for prospecting porphyry-Cu deposits in Jiroft area, Kerman province, southeast of Iran, as a case study.     

Delineation of groundwater potential zones using remote sensing,GIS, and AHP technique in Tehran–Karaj plain,Iran

Evaluation of groundwater resources in dry areas without enough data is a challenging task in many parts of the world, including Tehran–Karaj plain in Iran, which includes Tehran, the capital city of Iran and Karaj, one of Iran’s biggest cities. Water demand due to increasing agricultural and industrial activities caused many problems in the field of water resources management. In this study, the potential of groundwater resources was evaluated using remote sensing, geographic information system (GIS), and analytic hierarchy process (AHP) for the first time. Digital Elevation Model from Shuttle Radar Topography Mission was used to generate a slope map and drainage density map. Three Landsat-8 satellite images were utilized to provide lineament density and land cover/land use maps. Geological and soil type maps were provided from the Geological Survey and Mineral Explorations of Iran (GSI). Tropical Rainfall Measuring Mission data were used to prepare average annual precipitation map. Discharge values from 102 pumping wells in the time period of 2002–2014 were used to evaluate the results. Seven data layers were prepared, and the geodatabase was made in GIS. The layers and their classes were assigned weights using AHP method. Finally, the layers were overlaid based on their weights, and the potential map of groundwater resources was generated. The area was classified into five zones with very high, high, moderate, low, and very low potentials. The zones covered 5.95, 32.90, 22.70, 10.20, and 28.25% of the study area, respectively. The results showed good agreement with the field data obtained from discharge wells.     

Landfill site selection using combination of fuzzy logic and multi-attribute decision-making approach

During the last decades, growth of urbanization and industrialization led to an increase in solid waste generation. Landfilling is the most prevalent ultimate disposal method for the municipal solid wastes in developing countries. The rapid municipal solid waste generation in Markazi province (central part of Iran) causes the need for precision in finding a suitable landfill site selection. In the present study, 12 factors (environmental and socioeconomic factors) have been applied to select the landfill site in Markazi province, Iran. The different methods including the analytic network process (ANP) combined with fuzzy linguistic quantifier, ordered weighted average (OWA), and weighted linear combination (WLC) approach in geographic information system was applied to find an appropriate landfill site. The OWA operator function permits the evaluation of the wide spectrum of consequences (with different scenario) obtained from different management strategies. Results revealed that integration of fuzzy logic, ANP, and OWA provides flexible and better ideas compared to the Boolean logic and WLC to select a suitable landfill site.     

Nature of occurrence of phosphatic bands in Owk Formation,Neoproterozoic Kurnool basin,Andhra Pradesh

Rock slope instabilities are a major hazard for human activities often causing economic losses, property damages and maintenance costs, as well as injuries or fatalities. For slope stability analysis of open pit mines, series of studies must be carried out in order to identify the criteria which should take into consideration. In this research geotechnical parameters; Geological Strength Index (GSI), Rock Quality Designation (RQD), Cohesion (C), angle of internal friction (φ), uniaxial compressive strength (UCS) and Rock mass deformation modulus (E_m) which are obtained from data measured within geotechnical boreholes and pore pressure (U) are considered as the criteria to evaluate stability of pit No.1 of the Gole Gohar iron mine, located in Kerman province, south east of Iran. Since human judgments and preferences are often vague and complex and decision makers cannot estimate their preferences with an exact scale, we can only give linguistic assessments instead of exact ones. So fuzzy set theory introduced into Analytical Hierarchy Process (AHP). Fuzzy AHP (FAHP) is put forward to solve such uncertain problems. In this paper, FAHP method is used to determine the weights of the criteria by decision makers and then classification of the stability of blocks are determined by TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method by the shortest distance to positive ideal solution (PIS) and the longest distance to negative ideal solution (NIS).     

Using fuzzy TOPSIS method for mineral processing plant site selection

Site selection for the mineral processing is the most important decision made by owner that has a significant impact on the efficiency of the whole process. This is a critical decision which involves considering a number of criteria and finding the best location among feasible alternatives. Therefore, a multicriteria decision-making method is necessary to apply site-selection process to find the best location that meet desired conditions set by the selection criteria. This paper presents an application of TOPSIS method based on fuzzy sets (fuzzy TOPSIS), which is one of the broader multicriteria decision making means, used to select an appropriate site for mineral processing plant for Sangan iron ore mine (phase 2). For this purpose, at first considering the geological, technical, economical, and environmental factors, three feasible alternatives were selected for the processing plant using Geographical Information System. Then, based on the technical and experimental experiences and through judgment of the decision makers and experts, 14 criteria were established and these alternatives were evaluated. Finally, the alternatives were ranked and the best location was recommended.     

Exploration feature selection applied to hybrid data integration modeling: Targeting copper-gold potential in central Iran

A Sugeno-type fuzzy inference system is implemented in the framework of an adaptive neural network to map Cu–Au prospectivity of the Urumieh–Dokhtar magmatic arc (UDMA) in central Iran. We use the hybrid “Adaptive Neuro Fuzzy Inference System” (ANFIS; Jang, 1993) algorithm to optimize the fuzzy membership values of input predictor maps and the parameters of the output consequent functions using the spatial distribution of known mineral deposits. Generic genetic models of porphyry copper–gold and iron oxide copper–gold (IOCG) deposits are used in conjunction with deposit models of the Dalli porphyry copper–gold deposit, Aftabru IOCG prospect and other less important Cu–Au deposits within the study area to identify recognition criteria for exploration targeting of Cu–Au deposits. The recognition criteria are represented in the form of GIS predictor layers (spatial proxies) by processing available exploration data sets, which include geology, stream sediment geochemistry, airborne magnetics and multi-spectral remote sensing data. An ANFIS is trained using 30% of the 61 known Cu–Au deposits, prospects and occurrences in the area. In a parallel analysis, an exclusively expert-knowledge-driven fuzzy model was implemented using the same input predictor maps. Although the neuro-fuzzy analysis maps the high potential areas slightly better than the fuzzy model, the well-known mineralized areas and several unknown potential areas are mapped by both models. In the fuzzy analysis, the moderate and high favorable areas cover about 16% of the study area, which predict 77% of the known copper–gold occurrences. By comparison, in the neuro-fuzzy approach the moderate and high favorable areas cover about 17% of the study area, which predict 82% of the copper–gold occurrences.     

Evaluation of ecotourism potential in the northern coastline of the Persian Gulf

This research has identified areas located in the northern coastline of the Persian Gulf in the south of Iran, as strategic and ecological sites, based on tourism potential assessing criteria. To this end coastal limits were identified by satellite imagery in terms of shorelines and the maximum extent of water approach into the land and taking into consideration the characteristics of the nearby coastal villages. The studied region was then compared to similar international criteria and experiences. The original criteria were then divided into three main and four sub criteria. The Kangan region was found to have a potential for tourism industry according to the mentioned criteria. Naiband Gulf with a score of 20 was ranked first followed by Asalouyeh with a score of 18 and finally Taheri and Kangan Ports with scores of 16 and 15, respectively. With a high tourism industry potential in the studied region the necessity of ecotourism quality enhancement and environmental management planning for the northern shoreline of the Persian Gulf becomes of vital importance.