Books on the topic 'Fuzzy-set approach'

This article distinguishes between ‘measurement’ and ‘calibration’. It is organized around the distinction between measurement and calibration. The main message of this article is that fuzzy sets, unlike conventional variables, must be calibrated. It also argues that fuzzy sets provide a middle path between quantitative and qualitative measurement. It explores the common measurement practices in quantitative and qualitative social research. It then further demonstrates that fuzzy sets resonate with both the measurement concerns of qualitative researchers, where the goal often is to recognize between relevant and irrelevant variation, and the measurement concerns of quantitative researchers, where the goal is the precise placement of cases relative to each other. Current practices in quantitative social science undercut serious attention to calibration. Set-theoretic analysis without careful calibration of set membership is an exercise in futility.

This article investigates the tradition of case-oriented configurational research, focusing specifically on qualitative comparative analysis (QCA) as a tool for causal inference. It first presents two analytic procedures commonly used by comparative researchers. A short description of the state-of-the-art of QCA applications is offered, in terms of discipline, types of cases, models, combinations with other methods, and software development. It then reviews different uses of QCA, as well as generic ‘best practices’. Some key recent evolutions are illustrated: on the one hand the development, beyond dichotomous ‘crisp set’ QCA (csQCA), of multi-value QCA (mvQCA), fuzzy sets, and fuzzy-set QCA (fsQCA), and on the other hand technical advances and refinements in the use of the techniques. Finally, the article gives some concluding reflections as to expected developments, upcoming innovations, remaining challenges, expansion of fields of application, and cross-fertilization with other approaches.

Part II, ‘Doctrinal Perspectives’, is structured in two chapters: Chapter 3 and Chapter 4. Chapter 4, which is concerned with the state’s compliance with the obligation to adopt a National Human Rights Action Plan (NHRAP), addresses two sets of questions. The first section of Chapter 4 examines the question as to whether states are expected to adopt separate rights-specific action plans or just one global action plan covering all the rights (and rights-related topics) at once. By adopting a mixed methods approach, including a qualitative textual analysis, a quantitative content analysis, and a fuzzy-set method, the second section of this chapter attempts to clarify the ‘obligation to take all appropriate measures’ (OTAAM) from which the obligation to adopt a national human rights action plan is derived. It seeks to address the questions as to what ‘measure’ and ‘appropriateness’ mean in international human rights law? How to determine the degree of appropriateness of each measure taken by the state?

Comparative constitutional law’s methodological matrix is fuzzy and amorphous. A close look at social science methods suggests a toolkit of considerations to be addressed in conducting comparative constitutional inquiry, thus supporting various types of comparative constitutional studies. The meanings, purposes, and modes of comparative inquiry in contemporary comparative constitutional studies are identified; some basic principles of case selection and research design employed in inference-oriented small-N studies are presented; and the emerging world of multivariate, large-N studies is explored. It is argued that no research method enjoys an a priori advantage over another without taking into account the scope and nature of the studied phenomenon or the question the research purports to address. Thus, attempts to outline an “official” comparative method are not only unrealistic but also unwise. Comparative constitutionalists should settle instead on a set of several more sensible guiding principles, common rules of casuality, and a multi-method approach.

The quality of data collected in official spatial databases is crucial in making strategic decisions as well as in the implementation of planning and design works. Awareness of the level of the quality of these data is also important for individual users of official spatial data. The author presents methods and models of description and evaluation of the quality of spatial data collected in public registers. Data describing the space in the highest degree of detail, which are collected in three databases: land and buildings registry (EGiB), geodetic registry of the land infrastructure network (GESUT) and in database of topographic objects (BDOT500) were analyzed. The results of the research concerned selected aspects of activities in terms of the spatial data quality. These activities include: the assessment of the accuracy of data collected in official spatial databases; determination of the uncertainty of the area of registry parcels, analysis of the risk of damage to the underground infrastructure network due to the quality of spatial data, construction of the quality model of data collected in official databases and visualization of the phenomenon of uncertainty in spatial data. The evaluation of the accuracy of data collected in official, large-scale spatial databases was based on a representative sample of data. The test sample was a set of deviations of coordinates with three variables dX, dY and Dl – deviations from the X and Y coordinates and the length of the point offset vector of the test sample in relation to its position recognized as a faultless. The compatibility of empirical data accuracy distributions with models (theoretical distributions of random variables) was investigated and also the accuracy of the spatial data has been assessed by means of the methods resistant to the outliers. In the process of determination of the accuracy of spatial data collected in public registers, the author’s solution was used – resistant method of the relative frequency. Weight functions, which modify (to varying degree) the sizes of the vectors Dl – the lengths of the points offset vector of the test sample in relation to their position recognized as a faultless were proposed. From the scope of the uncertainty of estimation of the area of registry parcels the impact of the errors of the geodetic network points was determined (points of reference and of the higher class networks) and the effect of the correlation between the coordinates of the same point on the accuracy of the determined plot area. The scope of the correction was determined (in EGiB database) of the plots area, calculated on the basis of re-measurements, performed using equivalent techniques (in terms of accuracy). The analysis of the risk of damage to the underground infrastructure network due to the low quality of spatial data is another research topic presented in the paper. Three main factors have been identified that influence the value of this risk: incompleteness of spatial data sets and insufficient accuracy of determination of the horizontal and vertical position of underground infrastructure. A method for estimation of the project risk has been developed (quantitative and qualitative) and the author’s risk estimation technique, based on the idea of fuzzy logic was proposed. Maps (2D and 3D) of the risk of damage to the underground infrastructure network were developed in the form of large-scale thematic maps, presenting the design risk in qualitative and quantitative form. The data quality model is a set of rules used to describe the quality of these data sets. The model that has been proposed defines a standardized approach for assessing and reporting the quality of EGiB, GESUT and BDOT500 spatial data bases. Quantitative and qualitative rules (automatic, office and field) of data sets control were defined. The minimum sample size and the number of eligible nonconformities in random samples were determined. The data quality elements were described using the following descriptors: range, measure, result, and type and unit of value. Data quality studies were performed according to the users needs. The values of impact weights were determined by the hierarchical analytical process method (AHP). The harmonization of conceptual models of EGiB, GESUT and BDOT500 databases with BDOT10k database was analysed too. It was found that the downloading and supplying of the information in BDOT10k creation and update processes from the analyzed registers are limited. An effective approach to providing spatial data sets users with information concerning data uncertainty are cartographic visualization techniques. Based on the author’s own experience and research works on the quality of official spatial database data examination, the set of methods for visualization of the uncertainty of data bases EGiB, GESUT and BDOT500 was defined. This set includes visualization techniques designed to present three types of uncertainty: location, attribute values and time. Uncertainty of the position was defined (for surface, line, and point objects) using several (three to five) visual variables. Uncertainty of attribute values and time uncertainty, describing (for example) completeness or timeliness of sets, are presented by means of three graphical variables. The research problems presented in the paper are of cognitive and application importance. They indicate on the possibility of effective evaluation of the quality of spatial data collected in public registers and may be an important element of the expert system.