Fuzzy Delphi Analytic Hierarchy Process Research Articles

Determinants of prioritised influencing factors on coal spontaneous combustion propensity – A Fuzzy-Delphi-geometric mean analytic hierarchy process

One of the most common hazards in coal mines is spontaneous combustion, a significant cause of coal loss in underground mines. Specifying a suitable approach for the determinants of prioritized influencing factors on coal spontaneous combustion propensity is challenging. There needs to be more research that directly addresses the uncertainty of human judgement in assessing the factors influencing coal propensity to self-combustion. This is the first attempt to address the aforesaid problem by ranking the factors influencing spontaneous coal combustion. The ranking was performed using the Fuzzy Delphi Analytic Hierarchy Process (FDAHP) with two variants of the Geometric Mean Method (GMM), which enabled the analysis of both quantitative and qualitative data related to the rating of each factor influencing spontaneous combustion risk and the relative importance of each factor related to coal seam characteristics, geological aspects, mining practices, and environmental aspects. The results show that ‘GMM as a whole’ is a comparatively best-aggregating approach to the AHP process. The presented case study of using this methodology in underground mine conditions confirms its efficacy in assessing susceptibility to coal spontaneous combustion. This mainly concerns the pace and reliability of the obtained results and the determination of risk evaluation system based on intrinsic and extrinsic factors influencing susceptibility to spontaneous combustion of coal. Finally, this systematic technique was validated in the research area by utilizing spontaneous combustion incident that occurred in Jharia and Raniganj coalfields, which revealed rather excellent concordance in Jharia and Raniganj coalfields. The study can be used in mine planning to develop engineering data to select the operational parameter and prevent the initiation of spontaneous heating by identifying intrinsic factors and optimizing extrinsic factors.

A Delphi fuzzy analytic hierarchy process framework for criteria classification and prioritization in food supply chains under uncertainty

Effectively managing food supply chains is critical for ensuring food security and safety. Identifying and prioritizing the criteria affecting food supply chain performance is imperative to manage uncertainty and avoid undesirable consequences in Supply Chain Management (SCM). This study aims to identify and prioritize critical criteria affecting food supply chains under uncertainty. We use the Delphi method to choose the predominating criteria classified into four groups: Resilience and Flexibility, Transparency and Traceability, Communication and Collaboration, and Regulation and Standardization. The fuzzy Analytic Hierarchy Process (FAHP) method is used next to prioritize the selected criteria based on their significance. The results show investment in research and development, transparency and traceability, risk-sharing and collaboration among stakeholders, are the top criteria for food supply chain security and safety. These findings contribute to formulating and developing effective strategies for securing food supply chains.

A flexible approach to select road traffic counting locations: System design and application of a fuzzy Delphi analytic hierarchy process

Although the diffusion of Information and Communication Technologies provided transportation analysists with new data sources (such as Floating Car and mobile devices), the use of permanent sensors installed on roads is still of paramount importance for traffic analysis. Continuous count stations are one of the main components of a road traffic monitoring program, which could fulfil several aims: (1) planning of a transportation system, (2) traffic management and operations, (3) improvement of road safety, (4) special monitoring for planned/emergency events, and (5) estimation of environmental impacts. In this research activity a Fuzzy Delphi Analytic Hierarchy Process (FDAHP) was applied to select the best locations for a fixed number of permanent count stations, as the basis of a traffic monitoring program that can reach the previously described targets. A real case study was developed in the Città Metropolitana di Venezia (Italy), where budget limitations imposed the need for a scientific and sound framework to decide where new sensors should be installed. Specific objectives and criteria were defined, as well as proper indicators to quantify them using available data. Their relative importance was evaluated by a panel of experts belonging to several agencies, therefore with different perspectives. The information obtained was analysed following the FDAHP approach to produce a ranking of the potential locations. The proposed holistic approach can be considered as a reference framework for a system to support local authorities in creating a traffic monitoring system and can be easily applied to other study areas.

Multifactor Prediction of the Water Richness of Coal Roof Aquifers Based on the Combination Weighting Method and TOPSIS Model: A Case Study in the Changcheng No. 1 Coal Mine.

Identifying the water richness of coal roof aquifers is an important and difficult goal of hydrogeological research to prevent and control roof water disasters. To evaluate the water richness of roof sandstone aquifers of the No. 1 coal seam in the Changcheng No. 1 coal mine, a multifactor prediction method based on the fuzzy Delphi analytic hierarchy process (FDAHP), entropy weight method (EWM), sum of squared deviations (SSD), and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) was proposed. Multisource geological data, including sandstone thickness, burial depth, lithological composition index, core recovery, fault scale index, fault intersections and endpoint density, and fold fractal dimension, were chosen as the primary indicators for evaluating the water richness of roof sandstone aquifers. The FDAHP and EWM were used to scientifically determine the subjective and objective weight vectors of these seven main factors, and the SSD was used to determine the optimal combination weights based on the objective and subjective weight vectors. On this basis, the water richness index (WRI) model was developed using the TOPSIS method to rank the water richness of samples in the study area. A water richness zoning map was created using the WRI values, revealing three zones: the weak water richness zone, moderate water richness zone, and strong water richness zone. Additionally, the map was refined by incorporating hydrogeologic data collected during mining operations, including pumping tests and actual water inrushes from roadways and working faces. It is believed that the proposed WRI model is effective for predicting the water richness of the roof sandstone aquifers of the No. 1 coal seam in the Changcheng No. 1 coal mine based on the engineering practice data used to validate the WRI model.

Deriving and comparing priority vectors for revised‐leachate pollution index (r‐LPI) using three fuzzy analytic hierarchy process

AbstractThe revised leachate pollution index (r‐LPI) developed using the fuzzy Delphi analytical hierarchy process (FDAHP) is a technique to quantify the contamination potential of landfill leachate. The steps involved in the formulation of the r‐LPI were the selection of parameters using the fuzzy Delphi method (FDM), computing relative weights of the parameters using the fuzzy analytic hierarchy process (FAHP), development of sub‐index curves, and finally, aggregation of sub‐indices. The calculation of the weights of the parameters has been one of the most crucial steps in the formulation of any index. The analytical hierarchy process (AHP) has been one of the most widely used methods for weight calculation. However, it was observed that the traditional AHP is inadequate to deal with the imprecise or ambiguous nature of linguistic evaluation. It also involves human subjectivity, which induces ambiguity and entails the use of decision‐making with uncertainty. The fuzzy AHP method was used in this study to overcome this difficulty. Three significant issues pertinent and essential to fuzzy AHP were addressed: contradictions in expert judgment, deriving priorities from inconsistent fuzzy judgment matrices, and group decision‐making. In this study, three FAHP methods: Chang's extent analysis (EA) method, fuzzy preference programming (FPP), and logarithmic fuzzy preference programming (LFPP) were used to calculate the weights of the r‐LPI parameters. The results of these methods were then compared, and it was determined that LFPP was the most suitable method for calculating the weights of the r‐LPI parameters.

Prioritizing the Potential Smartification Measures by Using an Integrated Decision Support System with Sustainable Development Goals (a Case Study in Southern Italy)

With the increasing population of cities, expanding roads as one of the essential urban infrastructures is a necessary task; therefore, adverse effects such as increased fuel consumption, pollution, noise, and road accidents are inevitable. One of the most efficient ways to mitigate congestion-related adverse effects is to introduce effective intelligent transportation systems (ITS), using advanced technologies and mobile communication protocols to make roads smarter and reduce negative impacts such as improvement in fuel consumption and pollution, and reduction of road accidents, which leads to improving quality of life. Smart roads might play a growing role in the improved safety of road transportation networks. This study aims to evaluate and rank the potential smartification measures for the road network in Calabria, in southern Italy, with sustainable development goals. For this purpose, some potential smartification measures were selected. Experts in the field were consulted using an advanced procedure: four criteria were considered for evaluating these smartification measures. The Integrated fuzzy decision support system (FDSS), namely the fuzzy Delphi analytic hierarchy process (FDAHP) with the fuzzy technique for order performance by similarity to ideal solution (FTOPSIS) were used for evaluating and ranking the potential smartification measures. The results demonstrated that the repetition of signals in the vehicle has the highest rank, and photovoltaic systems spread along the road axis has the lowest rank to use as smartification measures in the roads of the case study.

Selection of optimal aggregation function for the revised leachate pollution index (r-LPI).

A tool to quantify the pollution potential of leachate, termed the revised leachate pollution index (r-LPI), has been developed. It was developed using the fuzzy Delphi analytic hierarchy process (FDAHP). The formulation entails four major steps: parameter selection, weight calculation, normalization of parameters, and aggregation of the parameters. Eleven leachate parameters categorized into three criteria were selected using the fuzzy Delphi method (FDM). The relative weights of the parameters and the criteria were computed using the fuzzy analytic hierarchy process (FAHP), and rating curves were used for normalization of the parameters. The selection of an aggregation function is one of the most critical steps in the development of a composite indicator. In this study, the concept of r-LPI was briefly discussed and 14 different aggregation functions were examined to estimate the pollution potential of landfill leachate. Based on accountability and non-accountability of weights of the parameters, ambiguity, eclipsing, and constant functional behavior, 8 aggregation functions were eliminated. The remaining six aggregation functions were subjected to sensitivity analysis. Furthermore, information lost due to aggregation of parameters was quantified. Based on the findings, it was concluded that the weighted additive function effectively quantifies the pollution potential of landfill leachate and thus recommended for the r-LPI.

Identifying and weighting of dimensions and indicators of individual job performance using fuzzy Delphi and fuzzy analytic hierarchy process techniques

PurposeThe purpose of the study was to identify and weight the dimensions and indicators of individual job performance (IJP).Design/methodology/approachTo identify dimensions and their measuring indicators, a literature review was conducted in PubMed, Embase™, ProQest, Scopus®, Web of Science™ and Google Scholar. Based on the results of the literature review and consensus among the research team, dimensions and measuring indicators were identified and an IJP framework was constructed. For weighting dimensions and indicators, fuzzy analytical hierarchy process (FAHP) and fuzzy Delphi technique (FDT) were conducted, respectively.FindingsBased on the results, the conceptual framework showed that IJP consisted of four dimensions as follows: task performance (TP), contextual performance (CP), counterproductive work behaviors (CWBs) and adaptive performance (AP). The results of FAHP showed that TP (0.358) had the highest weighting in measuring IJP. The weight of CWBs, CP and AP was 0.302, 0.244 and 0.096, respectively. The results showed that 102 indicators were identified to measure the dimensions. Using the FDT, 45 indicators were accepted and 57 were rejected. Of the accepted indicators, 12 indicators belonged to TP. In addition, 11, 12 and 10 belonged to CP, CWBs and AP, respectively.Research limitations/implicationsThe results of the article can be useful in research and practice and bridge the gap between theory and practice. In the research area, the researchers can use this model to develop questionnaires for evaluating IJP in all occupations. The researchers can choose the most effective dimensions or indicators in accordance with the corresponding occupation. Moreover, the results can be used in practice (economic and commercial impact), teaching, influencing public policy and helping to establish a more complete knowledge system.Originality/valueIn order to select dimensions and their measuring indicators, the work in the study took the unique approach to employ powerful decision-making methods combined with fuzzy methods to remove any ambiguity in opinions.

Vulnerability assessment and management planning for the ecological environment in urban wetlands

As a special ecosystem in cities, urban wetland parks have important environmental regulation and social service functions. This paper proposes a new methodology of urban wetland planning and management based on the vulnerability of the ecological environment. The Jixi National Wetland Park (JNWP) was taken as the research area to analyze the ecological, geological and environmental factors that affect urban wetlands. A remote sensing image, digital elevation model, and environmental quality interpolation processing were used to generate the factor layer, and a comprehensive evaluation index system was established. The fuzzy Delphi analytic hierarchy process (FDAHP) method was used to calculate the comprehensive weight of each evaluation factor. A model to evaluate the ecological environment vulnerability of the JNWP was established. Then, an improved k-means clustering algorithm was used to classify the ecological environment of the study area. The ecological environment vulnerability of the wetland was evaluated. The results showed that the vulnerability of the ecological environment in the study area could be divided into five levels, including very low, low, medium, high and very high vulnerability areas. According to the vulnerability level and the results of k-means++ cluster analysis, the JNWP is divided into five areas. The wetland buffer zone is the main factor that determines the distribution of ecological environment vulnerability in urban wetlands. However, cultivated land development and ecological environmental restoration are the main factors that determine the evolution of ecological environment vulnerability in urban wetlands. The FDAHP and geographic information systems (GIS), combined with cluster analysis, are effective methods to evaluate the vulnerability of the ecological environment of urban wetlands, which provides a scientific and accurate methodology for the management and sustainable development of urban wetlands.

Sustainable Development Assessment in Underground Coal mining by Developing a Novel Index

A novel index is presented in this paper to evaluate sustainable development in underground coal mining. Eleven parameters were chosen as impacting factors that define three aspects of sustainable development, including environmental, economic, and social. Fuzzy Delphi Analytical Hierarchy Process (FDAHP) was used to develop a new rating system in the form of a classification system. Subsequently, a sustainable development index (SDi) was defined as a simple summation of ratings for all parameters to classify the sustainability level of underground coal mining qualitatively. Applicability of the new index was examined through applying it to a case study, and the results were compared with a benchmark model. The results indicate that SDi possesses a higher performance in sustainable development evaluation in the actual case when compared to common models. This performance is because it is developed for underground coal mining, especially in a scientific manner that considers three aspects of sustainable development together.

Evaluation of the Water Yield of Coal Roof Aquifers Based on the FDAHP-Entropy Method: A Case Study in the Donghuantuo Coal Mine, China

The water yield of coal seam roof aquifers is the key factor for evaluating and controlling water disasters in coal seam roofs. To evaluate the water yield of the sandstone aquifer in the roof of the Carboniferous-Permian Damiaozhuang Formation no. 8 coal seam in the Donghuantuo Mine, North China, seven main controlling factors affecting the water yield of sandstone aquifers are determined, including the permeability coefficient, consumption of drilling fluid, core recovery, aquifer thickness, brittle-plastic rock thickness ratio, fault scale index, and fault point density. Further, the fuzzy Delphi analytic hierarchy process (FDAHP) and entropy weight method (EWM) are used to calculate the subjective and objective weights of each main factor, respectively, and a combination weight model (CWM) is proposed based on the least square method to compose the comprehensive weights. Then, an improved water yield property index (IWYPI) model is established, and the water yield zoning map of sandstone aquifers is acquired. Engineering practice shows that the evaluation accuracy of the water yield property index (IWYPI) model based on the CWM is as high as 93.75%, which is 18.75% and 12.5% higher than that of the water yield property index (WYPI) model based on the FDAHP and EWM, respectively. The research results propose a novel method for evaluating the water yield of coal seam roof aquifers and can provide scientific guidance for the prevention and control of water disasters in the no. 8 coal seam roof of the Donghuantuo Coal Mine.

A Hybrid Fuzzy MCDM Approach to Determine an Optimal Block Size in Open-Pit Mine Modeling: a Case Study

The computer-based 3D modeling of ore bodies is one of the most important steps in the resource estimation, grade determination, and production scheduling of open-pit mines. In the modeling phase, the volume of the orebody model is required to be filled by the blocks and sub-blocks. The determination of Block Size (BS) is important due to the dependence of the geostatistical issues and calculations related to mining capabilities on it. There are some factors effective in the determination of an optimal BS including the metal content, estimation error, recovery percentage, mining ability, safety, and dilution. In this work, an optimal BS is determined using a two-stage approach. In the proposed approach, the Fuzzy Delphi Analytic Hierarchy Process (FDAHP) and Fuzzy Multi-Objective Optimization by Ratio Analysis (FMOORA) methods are used. In the first phase, the weight of each criterion is calculated based on the opinions of the experts using the FDAHP method. In the second phase, the FMOORA method is applied in order to determine a suitable BS for the design and operation of mining considering the extracted weights in the previous phase. The block model of the Sungun copper mine is studied as a case study to evaluate the capability of the proposed approach. The results of implementation of this approach are desirable because of converting the opinions of the experts to fuzzy values, weighing the experts according to the experience and technical knowledge, weighting the criteria by FDAHP, and choosing the optimal option with FMOORA. Furthermore, the 12.5×12.5×12.5 m3 block (A5) is chosen as an appropriate BS, which is compatible with the real conditions of the studied mine.

An assessment of water yield properties for weathered bedrock zone in Northern Shaanxi Jurassic coalfield: a case study in Jinjitan coal mine, Western China

Jurassic weathered bedrock is widely distributed in the Jurassic coalfield of Northern Shaanxi Province. Its fracture network is connected with each other well, which provides a good space foundation for groundwater storage. It makes bedrock weathered zone become one of the important aquifers that endanger coal mine safe production. It is quite necessary to predict bedrock weathered zone aquifer water yield property scientifically to provide a technical guarantee for mine water inrush hazard prevention and control. In order to find out the characteristics of bedrock weathered zone aquifer water yield property, the 5 main control factors affecting weathered bedrock aquifer water yield property, characteristics of overlying aquifer, weathered bedrock strata age, lithologic composition feature, weathering intensity of bedrock, and bedrock weathered zone thickness, are selected to establish a water yield property index mathematical model on weathered bedrock aquifer by the fuzzy Delphi analytic hierarchy process (FDAHP) method and protracted water yield property partition map with the help of ArcGIS. Through analysis and comparison, established water yield property index model and partition map are feasible with a relative high accuracy. Meanwhile, it has some good directive significance to predict weathered bedrock aquifer water yield property type for surrounding mines with similar conditions.

Assessment of eco-geo-environment quality using multivariate data: A case study in a coal mining area of Western China

Abstract Coal resource extensive development and utilization seriously threatens the region fragile ecological environment in Western China. Using the Yushenfu coal mining area as a study site, the ecological and geological environment (eco-geo-environment) factors affected by coal mining were analyzed. Spatiotemporal data extracted from remote sensing images was combined with survey data to establish an evaluation and prediction model. Integrated eco-geo-environmental quality was established by calculating the combined weight of each factor using the fuzzy delphi analytic hierarchy process method to develop a comprehensive multi-factor eco-geo-environment quality evaluation map. Results shows that the eco-geo-environment quality was divided in five grades of worse, bad, medium, good and better, the overall condition of the study region is moderate and it is apparent that regions with less intensive mining activities (Yushen sub coal mining area) are in better condition as compared to those regions where intensive mining is well established (Shenfu sub coal mining area). Comparisons with the classified eco-geo-environment categories revealed that different eco-geo-environment quality grades were affected different eco-geo-environment categories after a period of coal resources exploitation, but eco-geo-environment quality generally has been declining since the development and utilization of coal resources. The model provides a more scientific and accurate method to evaluate regional eco-geo-environmental quality, which is important for the coordinated development between coal mining and the fragile eco-environment.

Assessing human vulnerability in industrial chemical accidents: a qualitative and quantitative methodological approach.

Iran as a developing country is experiencing the industrialization process quickly and is thus exposed to different industrial hazards mostly derived from chemicals. In the light of this problem, this study estimated the human vulnerability in chemical accidents using the software simulation of accidental chlorine gas releases. A mixed method (qualitative and quantitative) study carried out in 4 phases during 2015-2017 in Ray County, Tehran Province. It included a systematic literature review, software simulation, Fuzzy Delphi Analytical Hierarchy Process (FDAHP) hierarchy process study, and creating a reliable tool for purpose of this study in at-risk areas. The valuable finding indicated that decreasing the human vulnerability depends on both social and physical characteristics of area and even the social vulnerability indicators have more important role when compared with the physical vulnerability indicators. The statistical analysis revealed that the human vulnerability has the significant relationship with factors such as type of living place (rural or urban) areas, nationality, economic situation of households, the distance between housing and the nearest exit to main road, health centers, and manufacturing or storing chemical plants (P value < 0.01). The result also showed that the area under study is vulnerable from average to very high, both in its physical and social domains, against industrial chemical accidents. Additional comparative studies are needed to develop and generalize the appropriate set of indicators of human vulnerability to human induced disasters in Iran.

A new classification system for evaluation and prediction of unplanned dilution in cut-and-fill stoping method

Production planning in mineral exploitation should be undertaken to maximize exploited ore at a minimum unplanned dilution. Unplanned dilution reduction is among the ways to enhance the quality of products, and hence, reduce the associated costs, resulting in a higher profit. In this way, firstly, all the parameters contributing to unplanned dilution in underground stopes and specifically the cut-and-fill stoping method are identified. Secondly, the parameters are weighed using the fuzzy-Delphi analytical hierarchy process. Thirdly, the most effective parameters are selected among the pool of effective parameters. Finally, in order to present a novel classification system for an unplanned dilution assessment, a new index called stope unplanned dilution index (SUDI) is introduced. SUDI represents the extent to which a cut-and-fill stope is susceptible to unplanned dilution. That is, having the value of this index, one may classify the cut-and-fill stopes into five groups according to robustness versus unplanned dilution: very strong, strong, moderate, weak, and very weak. SUDI is applied to10 stopes in different parts of Venarch Manganese Mines (Qom, Iran). In this way, a semi-automatic cavity monitoring system is implemented in the stopes. The regression analysis method shows that there is a relationship between SUDI and the actual unplanned dilution in equivalent linear overbreak/slough with a correlation coefficient (R2 = 0.8957).

An Extended Multifactorial Fuzzy Prediction of Hard Rock TBM Penetrability

This paper presents an extended multifactorial fuzzy evaluation of hard rock tunnel boring machine performance. Several modifications have been applied to an earlier work of the authors team in 2009 to capture better prediction capabilities of TBM penetrability modeling. In this new work, five linguistic categories, ranging from “Very Poor” to “Very Good”, have been considered to represent penetrability classes which are described by Sigmoidal fuzzy membership functions to consider the relationship between machine’s rate of penetration and the ground characteristics including intact rock and rock mass properties. A comprehensive database of a total of 151 tunnel sections was employed for this purpose. Also, several experts from different fields of tunneling have been asked to evaluate the criteria using fuzzy Delphi analytical hierarchy process technique instead of relying upon the authors’ knowledge and expertise. The results have been verified by comparisons to the actual field penetration data as well as the results of other predictive models from the literature, showing a very good conformity between measurements and predictions of this research compared to all the previous models. It proves not only the superiority of the utilized methodology, but also its field applicability in future tunneling projects in similar geological conditions.

Classification of the type of eco-geological environment of a coal mine district: A case study of an ecologically fragile region in Western China

Western China is characterized by abundant coal resources but it also faces the problems of poor water resources and fragile ecological environment, which have become more prominent due to the large-scale exploitation of coal resources in recent years. Shennan coal mine district is located at the border area between the Loess Plateau and Mu Us Desert of Northern Shaanxi province, which belongs to the typical arid and semi-arid ecologically fragile region of Western China, The geological features and ecological environmental characteristics of this district show wide variations with spatial distribution. However, intense coal mining activities will inevitably lead to further deterioration of the already fragile ecological and geological (eco-geological) environment, making recovery increasingly difficult. Therefore, investigating the different characteristics and classifying the types of the eco-geological environment are of great significance to in selecting appropriate mining methods, which would help in realizing coordinated exploitation of coal resources and environmental protection before coal exploitation. In this study, based on the remote sensing and geographic information system technology, Landsat8 remote sensing image, regional geological data, Digital Elevation Model (DEM), borehole data, hydrological data were analyzed. Furthermore, the eco-geological environment of the study area was classified into three types with the Normalized Difference Vegetation Index, surface elevation, terrain slope, surface lithology, geomorphic type, and hydrographic net are selected as the main control factors to classify eco-geological environment type. Each control factor was quantified using ArcGIS, with the aid of MATLAB 2014b as the computing platform, eco-geological environment of study area is classified into three types combining weighted fuzzy C-means (WFCM) clustering algorithm and the weight of each main control factor determined by fuzzy Delphi analytic hierarchy process (FDAHP) method. Finally, the classification of the eco-geological environment was verified through a field survey of the Hongliulin coal mine, and the results showed high accuracy.

Designing Integrated Management Criteria of Creative Ideation Based on Fuzzy Delphi Analytical Hierarchy Process

In the more competitive new economy, recognizing and designing criteria and parameters to strengthen idea generating is vital so that these ideas will be used for the development of industries and the whole country. This paper designs a model for integrated management of creative ideation. Accordingly, we examine target population of 22 professors and entrepreneurs to determine priority of parameters that we define, and encourage them to propose new parameters to be added into the model, and these parameters improve ideation process. Therefore, we conduct an online survey, which employs snowball sampling method. After gathering data and determining weights of parameters based on fuzzy Delphi analytical hierarchy process, we rank each criterion’s parameters based on the opinions of the panelists and finally we design the model. This research suggests that an organization establishes to work on the principles based on the criteria and prioritized parameters that this paper specifies in its model. In addition, it proposes designing a web-based system within the organization, in which the system provides a database of creative ideas and manages processes in different levels (idea creation, idea training, and practical) to motivate intellectuals to generate new ideas, and facilitate the connection between creative thinkers and industry.

Presenting an engineering classification system for coal spontaneous combustion potential

The phenomenon of coal spontaneous combustion is one of the common hazards in coal mines and also one of the important reasons for the loss of coal in piles and mines. Based on previous researches, different types of coals have different spontaneous combustion characteristics. For coal loss prevention, a measure is necessary for prediction of coal spontaneous combustion. In this study, a new engineering classification system called ‘‘Coal Spontaneous Combustion Potential Index (CSCPI)’’ is presented based on the Fuzzy Delphi Analytic Hierarchy Process (FDAHP) approach. CSCPI classifies coals based on their spontaneous combustion capability. After recognition of the roles of the effective parameters influencing the initiation of a spontaneous combustion, a series of intrinsic, geological, and mining characteristics of coal seams are investigated. Then, the main stages of the implementation of the FDAHP method are studied and the weight of each parameter involved is calculated. A classification list of each parameter is formed, the CSCPI system is described, and the engineering classifying system is subsequently presented. In the CSCPI system, each coal seam can be rated by a number from 0 to 100; a higher number implies a greater ease for the coal spontaneous combustion capability. Based on the CSCPI system, the propensity of spontaneous combustion of coal can be classified into three potential levels: low, medium, and high. Finally, using the events of coal spontaneous combustion occurring in one of the Iranian coal mines, Eastern Alborz Coal Mines, an initial validation of the mentioned systematic approach is conducted. Comparison of the results obtained in this study illustrate a relatively good agreement.