Recommender Thermometer for Measuring the Preparedness for Flood Resilience Management

A range of various thermometers and similar scales are employed in different human and resilience management activities: Distress Thermometer, Panic Thermometer, Fear Thermometer, fire danger rating, hurricane scales, earthquake scales (Richter Magnitude Scale, Mercalli Scale), Anxiety Thermometer, Help Thermometer, Problem Thermometer, Emotion Thermometer, Depression Thermometer, the Torino scale (assessing asteroid/comet impact prediction), Excessive Heat Watch, etc. Extensive financing of the preparedness for flood resilience management with overheated full-scale resilience management might be compared to someone ill running a fever of 41°C. As the financial crisis hits and resilience management financing cools down it reminds a sick person whose body temperature is too low. The degree indicated by the Recommender Thermometer for Measuring the Preparedness for Flood Resilience Management with a scale between Tmin=34,0° and Tmax=42,0° shows either cool or overheated preparedness for flood resilience management. The formalized presentation of this research shows how changes in the micro, meso and macro environment of resilience management and the extent to which the goals pursued by various interested parties are met cause corresponding changes in the “temperature” of the preparedness for resilience management. Global innovative aspects of the Recommender Thermometer developed by the authors of this paper are, primarily, its capacity to measure the “temperature” of the preparedness for flood resilience management automatically, to compile multiple alternative recommendations (preparedness for floods, including preparing your home for floods, taking precautions against a threat of floods, retrofitting for flood-prone areas, checking your house insurance; preparedness for bushfires, preparedness for cyclones, preparedness for severe storms, preparedness for heat waves, etc.) customised for a specific user, to perform multiple criteria analysis of the recommendations, and to select the ten most rational ones for that user. Across the world, no other system offers these functions yet. The Recommender Thermometer was developed and fine-tuned in the course of the Android (Academic Network for Disaster Resilience to Optimise educational Development) project

Priority Events Determination For The Risk-oriented Management Of Electric Power System

The task of risk-oriented management of the electric power system in conditions of multi-criteria choice is considered. To determine the most effective measures, the implementation of which will reduce the magnitude of the risk of an emergency situation, multi-criteria analysis methods are applied. A comparative analysis of the multi-criteria alternative (ELECTRE) ranking method based on utility theory and the Pareto method, which defines a subset of non-dominant alternatives, is carried out. The Pareto method uses in its algorithm only qualitative characteristics of the advantage and allows only to distinguish a group of competitive solutions with the same degrees of non-dominance. Given the large number of evaluation criteria, the Pareto method is ineffective because the resulting subset of activities is in the field of effective trade-offs, when no element of the set of measures can be improved without degrading at least one of the other elements. The ELECTRE method is a pairwise comparison of multi-criteria alternatives based on utility theory. This method allows to identify a subset of the most effective activities. The number of elements of the resultant subset is regulated by taking into account the coefficients of importance of optimization criteria and expert preferences

Knowledge dependencies in fuzzy information systems evaluation

Experience and research within the field of Information Systems Evaluation (ISE), has traditionally centered on providing tools and techniques for investment justification and appraisal, based upon explicit knowledge which encodes financial and other direct situational factors (such as accounting, costing and risk metrics). However, such approaches tend not to include additional causal interdependencies that are based upon tacit knowledge and are inherent within such a decision-making task. The authors show the results of applying a cognitive mapping approach, in the guise of a Fuzzy Cognitive Mapping (FCM) simulation, i.e. Fuzzy Information Systems Evaluation (F-ISE), in order to highlight the usefulness of applying such a technique. The authors highlight those contingent and necessary knowledge dependencies, in an exploratory sense, which relate to the investment appraisal decision-making task, in terms of the interplay between tacit and explicit knowledge, in this regard

"The connection between distortion risk measures and ordered weighted averaging operators"

Distortion risk measures summarize the risk of a loss distribution by means of a single value. In fuzzy systems, the Ordered Weighted Averaging (OWA) and Weighted Ordered Weighted Averaging (WOWA) operators are used to aggregate a large number of fuzzy rules into a single value. We show that these concepts can be derived from the Choquet integral, and then the mathematical relationship between distortion risk measures and the OWA and WOWA operators for discrete and nite random variables is presented. This connection oers a new interpretation of distortion risk measures and, in particular, Value-at-Risk and Tail Value-at-Risk can be understood from an aggregation operator perspective. The theoretical results are illustrated in an example and the degree of orness concept is discussed.Fuzzy systems; Degree of orness; Risk quantification; Discrete random variable JEL classification:C02,C60

Applying concepts of fuzzy cognitive mapping to model IT/IS investment evaluation factors

The justification process is a major concern for many organisations that are considering the adoption of Information Technology (IT) and Information Systems (IS), and is a barrier to its implementation. As a result, the competitive advantage of many companies is being put at risk because of management's inability to evaluate the holistic implication of adopting new technology, both in terms of on the benefit and cost portfolios. This paper identifies a number of well-known project appraisal techniques used in IT/IS investment justification. Furthermore, the concept of multivalent, or fuzzy logic, is used to demonstrate how inter-relationships can be modeled between key dimensions identified in the proposed conceptual evaluation model. This is highlighted using fuzzy cognitive mapping (FCM) as a technique to model each IT/IS evaluation factor (integrating strategic, tactical, operational and investment considerations). The use of an FCM is then shown to be as a complementary tool which can serve to highlight interdependencies between contributory justification factors

ISIPTA'07: Proceedings of the Fifth International Symposium on Imprecise Probability: Theories and Applications

B

Designing an expert knowledge-based Systemic Importance Index for financial institutions

Defining whether a financial institution is systemically important (or not) is challenging due to (i) the inevitability of combining complex importance criteria such as institutions’ size, connectedness and substitutability; (ii) the ambiguity of what an appropriate threshold for those criteria may be; and (iii) the involvement of expert knowledge as a key input for combining those criteria. The proposed method, a Fuzzy Logic Inference System, uses four key systemic importance indicators that capture institutions’ size, connectedness and substitutability, and a convenient deconstruction of expert knowledge to obtain a Systemic Importance Index. This method allows for combining dissimilar concepts in a non-linear, consistent and intuitive manner, whilst considering them as continuous –non binary- functions. Results reveal that the method imitates the way experts them-selves think about the decision process regarding what a systemically important financial institution is within the financial system under analysis. The Index is a comprehensive relative assessment of each financial institution’s systemic importance. It may serve financial authorities as a quantitative tool for focusing their attention and resources where the severity resulting from an institution failing or near-failing is estimated to be the greatest. It may also serve for enhanced policy-making (e.g. prudential regulation, oversight and supervision) and decision-making (e.g. resolving, restructuring or providing emergency liquidity).Systemic Importance, Systemic Risk, Fuzzy Logic, Approximate Reasoning, Too-connected-to-fail, Too-big-to-fail. Classification JEL: D85, C63, E58, G28.

Characterizing urban landscapes using fuzzy sets

Characterizing urban landscapes is important given the present and future projections of global population that favor urban growth. The definition of “urban” on a thematic map has proven to be problematic since urban areas are heterogeneous in terms of land use and land cover. Further, certain urban classes are inherently imprecise due to the difficulty in integrating various social and environmental inputs into a precise definition. Social components often include demographic patterns, transportation, building type and density while ecological components include soils, elevation, hydrology, climate, vegetation and tree cover. In this paper, we adopt a coupled human and natural system (CHANS) integrated scientific framework for characterizing urban landscapes. We implement the framework by adopting a fuzzy sets concept of “urban characterization” since fuzzy sets relate to classes of object with imprecise boundaries in which membership is a matter of degree. For dynamic mapping applications, user-defined classification schemes involving rules combining different social and ecological inputs can lead to a degree of quantification in class labeling varying from “highly urban” to “least urban”. A socio-economic perspective of urban may include threshold values for population and road network density while a more ecological perspective of urban may utilize the ratio of natural versus built area and percent forest cover. Threshold values are defined to derive the fuzzy rules of membership, in each case, and various combinations of rules offer a greater flexibility to characterize the many facets of the urban landscape. We illustrate the flexibility and utility of this fuzzy inference approach called the Fuzzy Urban Index for the Boston Metro region with five inputs and eighteen rules. The resulting classification map shows levels of fuzzy membership ranging from highly urban to least urban or rural in the Boston study region. We validate our approach using two experts assessing accuracy of the resulting fuzzy urban map. We discuss how our approach can be applied in other urban contexts with newly emerging descriptors of urban sustainability, urban ecology and urban metabolism.This research was partially supported by "Boston University Initiative on Cities Early Stage Urban Research Awards 2015-16" (Gopal & Phillips) and the Frederick S. Pardee Center for the Study of the Longer-Range Future at Boston University. We thank the anonymous reviewers for their careful reading of our manuscript and their many insightful comments and suggestions. (Boston University Initiative on Cities Early Stage Urban Research Awards; Frederick S. Pardee Center for the Study of the Longer-Range Future at Boston University)https://doi.org/10.1016/j.compenvurbsys.2016.02.002Published versio

Occupational Cultures as a Challenge to Technological Innovation

This paper explains conflict over technological process innovation in cultural terms, drawing primarily on a case study of electric power distribution and strategies to automate its operation