3 edition of Fuzzy sets and series analysis for visual decision support in spatial data exploration found in the catalog.
Fuzzy sets and series analysis for visual decision support in spatial data exploration
Rob M. Hootsmans
by Koninklijk Nederlands Aardrijkskundig Genootschap, Faculteit Ruimtelijke Wetenschappen Universiteit Utrecht in Utrecht
Written in English
|Statement||Rob M. Hootsmans.|
|Series||Nederlandse geografische studies,, 202|
|LC Classifications||G70.212 .H66 1996|
|The Physical Object|
|Pagination||xvi, 168 p. :|
|Number of Pages||168|
|LC Control Number||97144484|
Abstract. Man-Machine Systems of the future will have to be different from to-day's de-finition. The economic situation is forcing us to make optimal use of all our resources; the work force and their trade union representatives demand the humanisation of work, a better quality of working life, the participation in designing the new systems, more liberties and more free options; there is also. Explore, understand, and find meaning in your data with dynamic, analytical maps. Bring together disparate data to see how things overlap and connect. Visualize spatial patterns in both 2D and 3D. Validate your assumption, evaluate the results, and aggregate data within a map.
The goal of this book is to present the current trends in visual and spatial analysis for data mining, reasoning, problem solving and decision-making. This is the first book to focus on visual decision making and problem solving in general with specific applications in the geospatial domain - combining theory with real-world cturer: Springer. Fuzzy set theory. Fuzzy set theory focuses on representing and managing vague information and is used in many complicated problems of the real world. A fuzzy set is essentially a set whose members have degrees of membership between 0 and 1, opposing to a crisp set in which each member must have either the membership degree of 0 or 1.
Go beyond simple map visualizations by integrating location data into your analysis. Answer spatial questions using the most comprehensive set of analytical methods and algorithms available. Use multiple data formats, sizes, and scales. Perform site selection, find clusters, make predictions, and quantify how patterns change over time. About. I am a Registered Professional Geologist (MAIG RPGeo) with a broad skill set in structural, generative and corporate geology honed during a 20+ year career in applied research and mineral exploration across a wide range of gold, base metals and uranium projects in Australia, Africa, North America, Europe and Asia.
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Visualization techniques benefit fuzzy spatial analysis in at least two aspects. One is in the field of exploratory analysis, and another is in the representation of uncertainty.
Hootsmans R.,Fuzzy Sets and Series Analysis for Visual. Decision Support in Spatial Data Exploration. PhD Thesis. Book. Jan ; Hans-Jürgen Zimmermann. Fuzzy Logic Spatial Decision Support System for Urban Water Management.
overcome the domain-speciﬁc spatial analysis problem is the. principle be those linked with available data sets.
Data Analysis. Elsevier Science Publishers B.V., pp. De Gruijter, J.J. et al., "Continuous soil maps - a fuzzy set approach to bridge the gap Fuzzy sets and series analysis for visual decision support in spatial data exploration.
PhD Thesis, University of Utrecht, Utrecht, pp. “An Application of Fuzzy Subsets Theory to the Analysis of the Consumer’s Spatial Preferences”, Fuzzy Sets and Systems, 5(), – MathSciNet zbMATH CrossRef Google Scholar Ponsard, C. “Producer’s Spatial Equilibrium with a Fuzzy Constraint”, European Journal of Operational Research, 10(a), –Cited by: 2.
Fuzzy Sets in Decision Analysis, Operations Research and Statistics includes chapters on fuzzy preference modeling, multiple criteria analysis, ranking and sorting methods, group decision-making and fuzzy game theory.
It also presents optimization techniques such as fuzzy linear and non-linear programming, applications to graph problems and fuzzy combinatorial methods such as fuzzy. By implementing: 1) fuzzy set membership as a method for representing the performance of decision alternatives on evaluation criteria, 2) fuzzy methods for both criteria weighting and capturing geographic preferences, and 3) fuzzy object oriented spatial databases for feature storage, it is possible to visually represent query results more.
Due to the fuzzy nature of the analysis approach, suitable visualization techniques to support the analysis process are highly needed. In this paper, the fundamentals of fuzzy spatial analysis are outlined and consecutively, the visualization tools supporting the exploration process are focused on.
Fuzzy sets and series analysis for visual decision support in spatial data exploration. Ph.D. Dissertation, University of Utrecht, Netherlands, pp. Google Scholar. Two solutions have been proposed to represent the vagueness of spatial data which are fuzzy set theory and intuitionistic fuzzy set theory.
series analysis for visual decision support in. The book includes examples of the use of fuzzy sets in representational issues such as terrain features, landscape morphology, spatial extents and approaches for spatial interpolation, plus applications using fuzzy sets covering data mining, spatial decision making, ecological simulation, and reliability in GIS.
Decision analysis and decision support is an area in which applications of fuzzy set theory, have been found since the early s. Algorithmic as well as knowledge-based approaches have been suggested. The meaning of the term “decision” has also been defined differently in different areas, as has the meaning of “uncertainty”.
Key Terms in this Chapter. Fuzzy Spatial Algebra: It is a system of fuzzy spatial data types including a comprehensive set of fuzzy spatial operations and fuzzy spatial predicates and satisfying closure properties. Geometric Anomaly: This occurs when the results of geometric set operations on fuzzy regions are, from an application standpoint, considered degeneracies like isolated or dangling.
And by providing a graphic and conceptual framework for addressing uncertainty in geographical data, interactive decision support systems grounded in fuzzy set theory offer a more reliable approach to exploratory spatial analysis (Hootsmans, ).
Fuzzy sets and series analysis for visual decision support in spatial data exploration. NGS. Fuzzy sets and series analysis for visual decision support in spatial data exploration.
Article. Jan ; R.M. Hootsmans; Classifications of spatial data with predefined boundary thresholds cause. Montana, in International Encyclopedia of Public Health, GIS Methods and Applications in Public Health.
Spatial analysis functions of GIS range from the topological and geometrical tasks to spatial statistics, which apply statistical methods to the analysis of spatial data. The most common methods in GIS are the former. These include query and selection, intersection, union, overlay.
It is argued that the process of application offuzzy set theory is very useful in supporting the process of decision-making in spatial planning. Combining a Geographical Information System (GIS) with applications offuzzy set theory is an appropriate methodology to support location choice and land suitability assessment.
Mackay, D.S. and V.B. Robinson. A multiple criteria decision support system for testing integrated environmental models. International Journal of Fuzzy Sets and Systems, (1), 53– Google Scholar. Decision Support The IDRISI Project's commitment from has been to provide a very strong spatial decision support system.
Version 2 continues the tradition by adding uncertainty management and decision strategy analysis to the already substantial set of tools for multi-criteria decision analyses. The potential importance of fuzzy sets for geographical applications is demonstrated in [3, 20, 26] where also examples of application-speciﬂc mem-bership functions are given.
The beneﬂts of fuzzy set theory for approximate spatial reasoning and fuzzy query languages is shown in [10, 11, 19, 27].
. Spatial analytics and data science are fueling a transformation in the connected age. Today, more than exabytes ( billion gigabytes) of data are generated daily.Hootsmans R.,Fuzzy Sets and Series Analysis for Visual Decision Support in Spatial Data Exploration. PhD Thesis Utrecht University, the Netherlands, ISBN Kruse R., Schewecke E., Heinsohn J.,Uncertainty and Vagueness in knowledge based systems, Numerical Methods.
Spring-Verlag, USA.This book includes the proceedings of the Intelligent and Fuzzy Techniques INFUS Conference held at Izmir, Turkey, July 21–23,and contains the collection of the most recent developments in fuzzy & intelligence systems and real complex systems.