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Books on the topic 'Fuzzy Measures'

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Published: 4 June 2021

Last updated: 20 February 2023

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1

Beliakov, Gleb, Simon James, and Jian-Zhang Wu. Discrete Fuzzy Measures. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-15305-2.

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Ohlan, Anshu, and Ramphul Ohlan. Generalizations of Fuzzy Information Measures. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-45928-8.

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3

Intuitionistic fuzzy measures: Theory and applications. New York: Nova Science Publishers, 2006.

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4

Hassall, John. Evaluating information systems using fuzzy measures. Wolverhampton: Management Research Centre, Wolverhampton Business School, 1998.

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5

P, Klement E., ed. Triangular norm-based measures and games with fuzzy coalitions. Dordrecht: Kluwer Academic, 1993.

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6

Farhadinia, Bahram, and Zeshui Xu. Information Measures for Hesitant Fuzzy Sets and Their Extensions. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-3729-1.

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7

Butnariu, Dan, and Erich Peter Klement. Triangular Norm-Based Measures and Games with Fuzzy Coalitions. Dordrecht: Springer Netherlands, 1993. http://dx.doi.org/10.1007/978-94-017-3602-2.

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8

Controlling accidents and insurers' risks in construction: A fuzzy knowledge-based approach. Hauppauge, NY: Nova Science Publishers, 2009.

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9

Andersson, Leif. The theory of possibility and fuzzy sets: New ideas for risk analysis and decision making. Stockholm: Swedish Council for Building Research, 1988.

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10

Wang, Zhenyuan, and George J. Klir. Fuzzy Measure Theory. Boston, MA: Springer US, 1992. http://dx.doi.org/10.1007/978-1-4757-5303-5.

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11

Wang, Zhenyuan. Fuzzy measure theory. New York: Plenum Press, 1992.

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12

Luukka, Pasi. Similarity measure based classification. Lappeenranta: Lappeenranta University of Technology, 2005.

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13

Berkachy, Rédina. The Signed Distance Measure in Fuzzy Statistical Analysis. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-76916-1.

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14

Ulrich, Höhle, and Rodabaugh Stephen Ernest, eds. Mathematics of fuzzy sets: Logic, topology, and measure theory. Boston: Kluwer Academic Publishers, 1999.

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15

Riečan, Beloslav. Integral, measure, and ordering. Dordrecht: Kluwer Academic Publishers, 1997.

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16

Höhle, Ulrich. Mathematics of Fuzzy Sets: Logic, Topology, and Measure Theory. Boston, MA: Springer US, 1999.

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17

Statistical methods for fuzzy data. Hoboken, N.J: Wiley, 2010.

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18

Zhi jue mo hu cu cao ji li lun ji ying yong. Beijing: Ke xue chu ban she, 2013.

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19

Esipov, Yuriy, Besik Meshi, Mustafa Dzhilyadzhi, and Aleksandr Hazov. Scientific and applied tasks of technosphere safety. ru: INFRA-M Academic Publishing LLC., 2022. http://dx.doi.org/10.12737/1882552.

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The monograph sets and solves the following tasks in a complex: systematization of types of safety; formalization of the structure and models of accidents; unification of the concepts of "safety" and "risk", primarily in relation to technical systems "protection - object - subject - environment"; as well as the tasks of combining and (or) generalization of algorithms for calculating safety indicators and the risk of systems based on probabilistic and possibilistic (fuzzy) measures of occurrence of accidents and the establishment of application boundaries for "objective" and (or) "subjective" indicators of safety and risk of technical systems. Using typical examples, the methods and results of solving the stated tasks are considered. For students, postgraduates and teachers of technical and technological universities and faculties, as well as for a wide range of readers interested in technosphere security issues.

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20

service), SpringerLink (Online, ed. Extremal Fuzzy Dynamic Systems: Theory and Applications. New York, NY: Springer New York, 2013.

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21

Ohlan, Anshu, and Ramphul Ohlan. Generalizations of Fuzzy Information Measures. Springer, 2016.

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22

Ohlan, Anshu, and Ramphul Ohlan. Generalizations of Fuzzy Information Measures. Springer, 2018.

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23

Hooda, D. S., and Vivek Raich. Fuzzy Information Measures with Applications. Alpha Science International, Limited, 2015.

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24

James, Simon, Gleb Beliakov, and Jian-Zhang Wu. Discrete Fuzzy Measures: Computational Aspects. Springer, 2019.

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25

Fuzzy Measures and Integrals: Theory and Applications (Studies in Fuzziness and Soft Computing). Physica-Verlag Heidelberg, 2000.

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26

Butnariu, D., and Erich Peter Klement. Triangular Norm-Based Measures and Games with Fuzzy Coalitions. Springer London, Limited, 2013.

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27

Butnariu, D. Triangular Norm-Based Measures and Games with Fuzzy Coalitions. Springer, 2010.

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28

Butnariu, D., and Erich Peter Klement. Triangular Norm-Based Measures and Games with Fuzzy Coalitions. Springer, 2013.

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29

Xu, Zeshui, and Bahram Farhadinia. Information Measures for Hesitant Fuzzy Sets and Their Extensions. Springer, 2018.

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30

Kamardeen, Imriyas. Controlling Accidents and Insurers' Risks in Construction: A Fuzzy Knowledge-Based Approach. Nova Science Publishers, Incorporated, 2009.

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31

Klir, George J., and Wang Zhenyuan. Fuzzy Measure Theory. Springer, 2010.

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32

Wang, Zhenyuan Zhenyuan, and George J. Klir. Fuzzy Measure Theory. Springer London, Limited, 2013.

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33

Bhatt, Rajen. Fuzzy-Rough Approaches for Pattern Classification: Hybrid Measures, Mathematical Analysis, Feature Selection Algorithms, Decision Tree Algorithms, Neural Learning, and Applications. Independently Published, 2017.

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34

Chalabi, Azadeh. Compliance with the Obligation to Adopt a NHRAP. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198822844.003.0005.

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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?

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35

Riecan, Beloslav, and Tibor Neubrunn. Integral, Measure, and Ordering. Springer, 2013.

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36

Riecan, Beloslav. Integral, Measure, and Ordering. Springer, 2010.

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37

Mathematics of Fuzzy Sets: Logic, Topology, and Measure Theory. Springer, 2012.

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38

Höhle, Ulrich, and S. E. Rodabaugh. Mathematics of Fuzzy Sets: Logic, Topology, and Measure Theory (The Handbooks of Fuzzy Sets). Springer, 1998.

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39

Yu, Wen, and Suresh Thenozhi. Active Structural Control with Stable Fuzzy PID Techniques. Springer London, Limited, 2015.

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40

Yu, Wen, and Suresh Thenozhi. Active Structural Control with Stable Fuzzy PID Techniques. Springer International Publishing AG, 2016.

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41

Berkachy, Rédina. Signed Distance Measure in Fuzzy Statistical Analysis: Theoretical, Empirical and Programming Advances. Springer International Publishing AG, 2022.

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42

Berkachy, Rédina. Signed Distance Measure in Fuzzy Statistical Analysis: Theoretical, Empirical and Programming Advances. Springer International Publishing AG, 2021.

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43

McCleary, Richard, David McDowall, and Bradley J. Bartos. Construct Validity. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780190661557.003.0008.

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Chapter 8 focuses on threats to construct validity arising from the left-hand side time series and the right-hand side intervention model. Construct validity is limited to questions of whether an observed effect can be generalized to alternative cause and effect measures. The “talking out” self-injurious behavior time series, shown in Chapter 5, are examples of primary data. Researchers often have no choice but to use secondary data that were collected by third parties for purposes unrelated to any hypothesis test. Even in those less-than-ideal instances, however, an optimal time series can be constructed by limiting the time frame and otherwise paying attention to regime changes. Threats to construct validity that arise from the right-hand side intervention model, such as fuzzy or unclear onset and responses, are controlled by paying close attention to the underlying theory. Even a minimal theory should specify the onset and duration of an impact.

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44

Intuitionistic Fuzzy Sets Studies in Fuzziness and Soft Computing. Physica-Verlag, 2010.

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45

Sirbiladze, Gia. Extremal Fuzzy Dynamic Systems: Theory and Applications. Springer, 2014.

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46

Ślusarski, Marek. Metody i modele oceny jakości danych przestrzennych. Publishing House of the University of Agriculture in Krakow, 2017. http://dx.doi.org/10.15576/978-83-66602-30-4.

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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.

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