Emergency alternative evaluation and selection based on ANP,DEMATEL, and TL-TOPSIS

With the increasing occurrence frequency of emergency events, emergency management (EM) has been a very important issue in management science. One of the major activities of EM is to evaluate and select the most desirable emergency alternative(s). This paper proposes a new framework combining the analytic network process (ANP) method, the decision-making trial and evaluation laboratory (DEMATEL) technique, and 2-tuple linguistic technique for order preference by similarity to an ideal solution (TL-TOPSIS) method to solve the emergency alternative evaluation and selection problem. This study has been done in three stages. In the first stage, we use DEMATEL technique to obtain the network relation map (NRM) among emergency alternative evaluation criteria or sub-criteria. In the second stage, we use ANP method to calculate the global weight of each sub-criterion based on the NRM among emergency alternative evaluation sub-criteria. In the third stage, the ratings of emergency alternative with respect to each sub-criterion are described by linguistic items, and the TL-TOPSIS method is used to rank the emergency alternative. Finally, a practical example of urban fire emergency alternative selection is given to illustrate the application of the proposed framework.     

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.     

Applications of analytical hierarchy process (AHP) and analytical network process (ANP) for industrial site selections in Isfahan,Iran

Industrial sites are key factors in urban and regional land use planning. Therefore, determining the location of industrial areas is a critical and complex process for development and success. Industrial site selection aims in identifying the most suitable sites for industry creation, considering a set of influential criteria. Therefore, site selection generally and industrial site selection specifically can be categorised as a multi-criteria decision-making (MCDM) problem that requires detailed evaluation of various dimensions. This study developed a set of clusters containing 10 selection criteria for industrial site selection in Isfahan metropolitan area, Iran. The relationships between the criteria and clusters were modelled and analysed using analytical hierarchy process (AHP) and analytical network process (ANP). AHP and ANP agree in finding distance to water bodies and distance to other industries as the most and least important selection criteria. Four patches have been identified as suitable alternatives for industrial construction. While AHP found Borkhar Patch 1 as the most appropriate alternative, ANP demonstrated the superiority of Ardestan Patch over others. Conducting a sensitivity analysis for the models confirmed both models robustness in industrial site selection decisions.     

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.     

Choosing a municipal landfill site by analytic network process

In this study, analytic network process (ANP), one of the multi-criteria decision making (MCDM) tools has been used to choose one of the four alternative landfill sites for the city of Eskisehir, Turkey. For this purpose, Super Decision Software has been used and benefit opportunity cost and risk (BOCR) analysis has been done to apply ANP. In BOCR analysis, each alternative site has been evaluated in terms of its benefits, costs and risks; the opportunity cluster has been examined under the benefit cluster. In this context, technical, economical and social assessments have been done for the site selection of sanitary landfill. Also, results have been compared with analytic hierarchy process (AHP) which is another MCDM technique used in the study conducted before. Finally, the current site has been determined as the most appropriate site in both methods. These methods have not been commonly used in the discipline of environmental engineering but it is believed to be an important contribution for decision makers.     

The application of cascading consequences for emergency management operations

How societies organize themselves to respond to cascading impacts exacerbated by climate change will help define the future of disaster planning, mitigation, response, and recovery. Current emergency management risk analyses focus on identifying a broad array of threats and hazards that may affect an area. However, there is limited attention and understanding of the totality of hazard impacts, the relationship of consequences across disasters, and the dangers of not addressing critical capabilities necessary to rapidly managing consequences—including the potential to create new incidents within incidents. Through a focused review of the related literature and guiding policy documents, this study aims to provide a cascading consequence-based framework that can support emergency managers in the analysis of their jurisdictional risks, development of emergency operations plans, and decision-making. Results include the identification of an alternative framework to identify cascading networks, the creation of a supplementary model for downstream risk assessment, and refined Threat and Hazard Identification and Risk Analysis (THIRA) outputs for improved grant allocation. The proposed framework has the potential to help organizations factor both conspicuous and downstream consequences into their Emergency Operations Plans in the planning and mitigations phases. This proposed refinement, which looks deeper into the progression of a disaster, has both national and international implications.

     

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.     

Land evaluation for ecotourism development—an integrated approach based on FUZZY,WLC, and ANP methods

Identification of capacities for development of ecotourism is an undeniable priority in any country. For this purpose, various methods have been proposed by different researchers for locating regions with a potential for the development of ecotourism. These regions have different strong and weak points depending on the regional conditions. Evidently, the use of quantitative methods and reduced expert involvement in the process of decision-making and evaluation can yield better results. Therefore, in this research, a multi-criteria evaluation method based on fuzzy logic and network analysis process (ANP) has been used for the evaluation of the development of ecotourism. Therefore, one of the semi-northern regions of the country—Taleghan county, Alborz province—which has different capacities regarding ecotourism was chosen and investigated. Ecological and socio-economic criteria and indices were first identified and then quantified by fuzzy method, after which they were normalized. Further, the weight of factors was determined by the ANP method. Thereafter, using weight linear combination (WLC) operator, all the layers were combined and the region’s potential for ecotourism was zoned. The outcomes show that out of the entire area, 75.2% has different abilities for ecotourism development, while the remaining area lacks any special ability. Further, the results of the research indicate that the concurrent use of fuzzy logic and ANP method in determining the priority and weight of criteria provides more logical and flexible conditions compared to other methods for land evaluation in the context of the mentioned aim through WLC method.     

Fast computation of Hankel Transform using orthonormal exponential approximation of complex kernel function

The computation of electromagnetic (EM) fields, for 1-D layered earth model, requires evaluation of Hankel Transform (HT) of the EM kernel function. The digital filtering is the most widely used technique to evaluate HT integrals. However, it has some obvious shortcomings. We present an alternative scheme, based on an orthonormal exponential approximation of the kernel function, for evaluating HT integrals. This approximation of the kernel function was chosen because the analytical solution of HT of an exponential function is readily available in literature. This expansion reduces the integral to a simple algebraic sum. The implementation of such a scheme requires that the weights and the exponents of the exponential function be estimated. The exponents were estimated through a guided search algorithm while the weights were obtained using Marquardt matrix inversion method. The algorithm was tested on analytical HT pairs available in literature. The results are compared with those obtained using the digital filtering technique with Anderson filters. The field curves for four types (A-, K-, H-and Q-type) of 3-layer earth models are generated using the present scheme and compared with the corresponding curves obtained using the Anderson sc heme. It is concluded that the present scheme is more accurate than the Anderson scheme     

Comparison and good regional equilibrium with a special look at Iran: empirical experiences

The shift to building capacity and the loss of regional equilibrium may undermine service delivery and create a hardness issue for governmental and non-governmental organizations. Different countries follow different frameworks for regional equilibrium to evaluate the results of their actions. To achieve good regional equilibrium, we have performed a comparative analysis between the 10 existing frameworks and put 5 main criteria along with 60 sub-criteria in a checklist. We examined the method of measuring these components with the help of various indicators and to distribute weight between these indicators, we consulted experts. Finally, Iran is discussed with examples of direct indicators that may be used to measure the sub-criteria of each specific criterion. The quantification process is also shown by several specific representative indicators. For example, Mobile phones to the population, general practitioners per population, health and social employees to the population. Researchers, policy-makers, decision-makers, and decision takers, are those who can use the method studied in this study to assess the level of regional equilibrium in their country specifically and according to the environmental conditions and the current situation in the region.

     

Opportunities provided by geographic information systems and volunteered geographic information for a timely emergency response during flood events in Cologne,Germany

The occurrence of disasters such as extreme flooding in urban environments has severe consequences, not only on the human population but also on critical infrastructures such as the road networks, which are of vital importance for everyday living and particularly for emergency response. In this article, our main goal is to present-conceptually and in praxis-a model that could be used from the emergency responders for timely and efficient emergency management and response in an urban complex environment. For the city of Cologne in Germany, we aim to indicate possible ways to decrease the emergency response time during an extreme flood scenario through the development of an accessibility indicator, which consists of different components. Therefore, we will investigate the opportunities that occur, in a flood risk scenario, from the use of geographic information in different forms such as Volunteered Geographic Information (VGI) and open-source data in an ArcGIS environment, to increase urban resilience through the decreasing emergency response time. We will focus on network analysis for the fire brigades (first acting emergency responders) during a flood scenario to calculate their emergency response ranges and emergency response routes through flooded road networks, for the assistance of the possibly affected hospitals, refugee homes and fire brigades, which can be flooded. At the end of the paper, we suggest that the vulnerable community of the refugees could be taken into consideration as a new source of VGI, as an additional component that would lead to the decrease in the emergency response time. The geo-located information that could be provided by the refugee community can be very useful in emergency situations, such as those examined in this article where timely information can be forwarded to the proper authorities for a more focused and timely emergency response, increasing the resilience of the urban population and their community.

     

Random field characterization of uniaxial compressive strength and elastic modulus for intact rocks

Rock properties exhibit spatial variabilities due to complex geological processes such as sedimentation,metamorphism, weathering, and tectogenesis. Although recognized as an important factor controlling the safety of geotechnical structures in rock engineering, the spatial variability of rock properties is rarely quantified. Hence, this study characterizes the autocorrelation structures and scales of fluctuation of two important parameters of intact rocks, i.e. uniaxial compressive strength(UCS) and elastic modulus(EM).UCS and EM data for sedimentary and igneous rocks are collected. The autocorrelation structures are selected using a Bayesian model class selection approach and the scales of fluctuation for these two parameters are estimated using a Bayesian updating method. The results show that the autocorrelation structures for UCS and EM could be best described by a single exponential autocorrelation function. The scales of fluctuation for UCS and EM respectively range from 0.3 m to 8.0 m and from 0.3 m to 8.4 m.These results serve as guidelines for selecting proper autocorrelation functions and autocorrelation distances for rock properties in reliability analyses and could also be used as prior information for quantifying the spatial variability of rock properties in a Bayesian framework.     

Urban Sustainability Evaluation Based on Remote Sensing and Network Data Support: Progress and Prospect

The sustainable development of the city is the key to the realization of the global sustainable development goals. Urban sustainability evaluation is a measure to the sustainable development of cities, and basis of sustainable urban development. The current evaluation method is based on statistical data which is low spatial resolution, long period and high cost. In recent years, remote sensing data, network data and the multivariate data have been used for the evaluation for the sustainable development of cities, and there have been many related research cases, which provides a new idea and method to carry out the high resolution evaluation of urban sustainable development rapidly, accurately and cheaply. This article reviewed the remote sensing data and network data in the progress of the application in the evaluation to the sustainable development of cities, and discussed the advantages of remote sensing and network big data in the objectivity, accuracy, and timeliness of evaluation compared with traditional data. Based on the sustainable urban development indicators of the United Nations Sustainable Development Goals (SDG), a basic framework for the evaluation of sustainable development of cities with high temporal and spatial resolution of big data such as remote sensing data and network big data was proposed. The introduction of remote sensing and network big data will change the inherent paradigm of sustainability assessment, make high-resolution real-time evaluation possible, further innovate analytical techniques, improve data accuracy, and make clear the alternative relationship with traditional data being the focus and the only way to realize the replacement of traditional data by remote sensing and network big data.     

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.     

Assessing flood hazard using flood marks and analytic hierarchy process approach: a case study for the 2013 flood event in Quang Nam,Vietnam

The production of flood hazard assessment maps is an important component of flood risk assessment. This study analyses flood hazard using flood mark data. The chosen case study is the 2013 flood event in Quang Nam, Vietnam. The impacts of this event included 17 deaths, 230 injuries, 91,739 flooded properties, 11,530 ha of submerged and damaged agricultural land, 85,080 animals killed and widespread damage to roads, canals, dykes and embankments. The flood mark data include flood depth and flood duration. Analytic hierarchy process method is used to assess the criteria and sub-criteria of the flood hazard. The weights of criteria and sub-criteria are generated based on the judgements of decision-makers using this method. This assessment is combined into a single map using weighted linear combination, integrated with GIS to produce a flood hazard map. Previous research has usually not considered flood duration in flood hazard assessment maps. This factor has a rather strong influence on the livelihood of local communities in Quang Nam, with most agricultural land within the floodplain. A more comprehensive flood hazard assessment mapping process, with the additional consideration of flood duration, can make a significant contribution to flood risk management activities in Vietnam.     

Reliability Analysis of Quick Sand Condition

First order reliability method (FORM) is generally used for reliability analysis in geotechnical engineering. This article adopts generalized regression neural network (GRNN) based FORM, Gaussian process regression (GPR) based FORM and multivariate adaptive regression spline (MARS) based FORM for reliability analysis of quick sand condition. GRNN is related to the radial basis function (RBF) network. GPR is developed based on probabilistic framework. MARS is a nonparametric regression technique. A comparative study has been carried out between the developed models. The performance of GPR based FORM and MARS based FORM match well with the FORM. This article gives the alternative methods for reliability analysis of quick sand condition.     

A statistical power analysis approach to estimate groundwater-monitoring network size in Victoria County Groundwater Conservation District,Texas

A properly designed groundwater-monitoring network is critical to evaluate groundwater management policies and regulations and establish a scientifically credible, risk-informed approach towards management of aquifer resources. To achieve proper design, the network must comprise a sufficient number of wells that comprehensively covers the area of interest. In this study, statistical power analysis is utilized to define the size of a proposed monitoring network within the Victoria County Groundwater Conservation District (VCGCD). In particular, the network seeks to provide empirical information to evaluate whether the VCGCD is meeting the criteria of the desired future conditions (DFC) established by the Groundwater Management Area 15 (GMA 15) through the joint planning process, as required by the statutes of Texas. The evaluation of DFCs is expressed as a hypothesis-testing problem with the null hypothesis stating that the VCGCD complies with the DFC, and the alternative hypothesis stating that the VCGCD does not comply with the DFC. The power analysis quantifies the ability of the statistical test to correctly reject the null hypothesis. The power of the statistical test is a function of the sample size and this relationship can be exploited to determine the size of the required groundwater-monitoring network if the effect size can be specified. However, prior to establishing a monitoring network, the groundwater level monitoring tends to be ad hoc; therefore, the statistical moments required for characterizing the effect size are not likely to be known with a high degree of certainty. As such, an innovative framework that integrates power analysis with bootstrap resampling protocols was developed to estimate monitoring network size under uncertainty. The results of the study indicated that a minimum set of approximately 70 wells is required within the VCGCD to statistically evaluate the compliance with DFCs with 90 % reliability and at a significance level of 10?% and 90 % power. The number of wells increased to about 85 when the significance level was reduced to 5 %. Geostatistical analysis indicated that these monitoring wells must be at least 3 miles apart to ensure statistically independent information. The developed methodology provides a practical framework to size a groundwater-monitoring network under data sparse situations.     

Monitoring, prediction, and early warning using ground-based radar interferometry

In order to define adequate prevention measures and to manage landslide emergencies, real-time monitoring is required. This paper presents two different applications of the remote sensing technique: the ground-based synthetic aperture radar interferometry, here proposed as a monitoring and early warning support for slope instability. Data acquisitions carried out through a ground-based synthetic aperture radar interferometer, operating in K_u band, installed in front of the observed slopes, are discussed. Two case studies, based on the use of the same apparatus (formerly developed by the Joint Research Center of the European Commission and by Ellegi-LiSALab srl), are reported: the first one concerns the monitoring of a large landslide, named Ruinon (Valfurva, Italy). The second one deals with the monitoring of the NW unstable slope in the Stromboli island aimed to implementing an early warning system. Acquired interferometric data are processed to provide displacements and velocity maps of the monitored area. The monitoring services ongoing on the Ruinon landslide and on Stromboli demonstrate the capability of this technique to operate in different operative settings (i.e., different phenomena and geological framework) and for different aims (monitoring for prevention, early warning, and emergency assessment). This methodology has also been proved by national and regional authorities of civil protection in order to provide a real-time monitoring for emergency management.     

Modeling the Neuman’s well function by an artificial neural network for the determination of unconfined aquifer parameters

An artificial neural network is designed as an improved alternative approach to the conventional type-curve matching technique for the determination of unconfined aquifer parameters. The network is implemented in a six-step protocol consisted of input selection, data splitting, design of network architecture, determination of network structure, network training, and network validation. The network is trained for the well function of unconfined aquifers by the back-propagation technique, adopting the Levenberg-Marquardt optimization algorithm. By applying a principal component analysis (PCA) on the training input data and through a trial-and-error procedure, the structure of the network is optimized with the topology of (3 × 6 × 3). The replicative, predictive, and structural validity of the developed network are evaluated with synthetic and real field data. The network eliminates graphical error inherent in the type-curve matching technique and provides an automatic and fast procedure for aquifer parameter estimation, particularly when analyzing many alternative pumping tests routinely obtained from continuous data loggers/data collection systems.     

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.