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Implementation of membership functions for Fuzzy Logic analysis requires a lot of steps for manual process. As most of the process is generic for different layers, the analysis procedure was automated by customizing the application. Therefore, for site selection, a manual and automated fuzzy logic analysis was performed by making use of GeoMedia.

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- 1. Fuzzy Logic and GeoMedia Supervisors: Prof. Dr. Dietrich Schröder Prof. Dr. Franz-Josef Behr 1
- 2. Agenda Introduction About Me Objectives Work Project on MapWindow Literature review ActiveX Inception of VnRPToolkit Study area and Data Scope of GeoMedia software Fuzzy logic approach Boolean logic Fuzzy and Boolean Comparisions Fuzzy Command Tool Conclusions 2
- 3. Introduction Site selection process - a screening technique Factors for selection of land fill (slope, river, road, geology, land use, etc.) Factors for restrictions (environmental, economic, social and legislative factors.) Boolean logic and Fuzzy logic 3
- 4. Objective Formulation of membership functions Primary goal - creation of generic Tool. Comparison of the results
- 5. Literature Review Conventional use of Fuzzy Logic - control systems Successful Implementation – analysis,and classification of RS. GIS software packages. IDRISI called FUZSIG. No incorporation of generic tool for process automation Fuzzy analysis - Extensive and laborious analysis. 5
- 6. Study area and Data Figure 3 : Map of Study Area 6
- 7. Scope of GeoMedia Software GeoMedia Professional 6.1 GeoMedia Grid 6.1 – An extension Single GIS environment Provides generic tools for manual fuzzy analysis Customization through VB, Visual C++ and Visual C# 7
- 8. Theory of Fuzzy Logic Lotfi Zadeh, Fuzzy Sets (1965). Fuzzy logic – Described to cope with fuzziness. Fuzzy sets – A superset of conventional (Boolean) logic MF range – 0 to 1. Reasoning using linguistic terms. If the distance is short then assign 0 membership 0 0 0 1 1 1 0 0 0.2 0.4 0.6 0.8 1 1 (a) Boolean Logic. (b) Fuzzy Logic. 8
- 9. Characteristic Function:Let X be the universe of discourse with elements x. Then for Boolean logic the Characteristic function fA(x) of AfA(x): X → {0, 1},where fA(x) = 1 if x is totally in A; fA(x) = 0 if x is not in A;However for a Fuzzy set A we haveμA(x): X → [0, 1], where μA(x) = 1 if x is totally in A; μA(x) = 0 if x is not in A; 0 < μA(x) < 1 if x is partly in A. 9
- 10. An exampleThe degree of Fuzzy sets is shown as follows:Layers Membership function MF = 0, if x < 500Settlements MF = 1, if x > 1500 MF = ((x-500)/1000), if 500 ≤ x ≤ 1500 Figure 1:Visual interpretation of Membership Function with respective graphs 10
- 11. Membership FunctionsLayers Membership function MF = 1, if 0 <x<5Slope MF = ((x-5)/10), if 5≤x≤15 MF = 0, if x>15 MF = 0, if 225≤x≤315 MF = ((x-135)/90) if 135<x<225Aspect MF = ((x-315)/90) if 315<x<45 (315<x<405) MF = 1, if 45≤x≤135 MF = 1, if x=361(flat areas) MF = 0, if x<200Wells MF = ((x-400)/200), if 400≤x≤600 MF = 1, if x>600 MF = 0, if x<250River MF = ((x-250)/500), if 250≤x≤750 MF = 1, if x>750Road MF = 0, if x>500 MF = ((500-x)/500), if 0<x≤500 MF = 0, if x<250settlements MF = ((x-500)/1000), if 500≤x≤1500 MF =1, if x>1500 MF = 0, if x > +125Geology MF = ((125-x)/250), if -125≤x≤+125 MF = 1, if x < -125
- 12. Fuzzy logic with basic analysis tool 01Settlement Membarship 0Membarship 500 m Membarship 1Void m 1Membarship 1500 Membarship Void
- 13. Fuzzy logic Analysis Rivers Aquifer Wells Legend Settlement 0 Aspect 0.1 0.2 Roads 0.3Slope 0.4 0.5 0.6 0.7 0.8 0.9 1
- 14. Fuzzy analysis results for Optimumsites Addition operation withFunction value of 5 Product a threshold Minimum operation Suitable areas 0 Membarship 1 Membarship
- 15. Boolean Analysis 0<Aspect <180 Slope < 10 degrees Minor Aquifer Settlement distance = 1000m Rivers distance = 500mRoads distance=500m Wells distance = 500m
- 16. Boolean analysis results for optimumsites
- 17. Fuzzy and Boolean Comparisions Minimum Function 0 Membarship 1 Membarship Boolean resultant areas
- 18. Fuzzy and Boolean Comparisions Boolean - sharp distinction with “YES” and “NO” areas Fuzzy - gradual delineation for selected landfill Flexibility to decide on threshold for fuzzy logic No need for repeated analysis No need for change in criteria and rules Saves time and reduces effort Decisions on threshold can be supplimented by field work
- 19. The Fuzzy Command Tool Input section Process Section To specify ascending or descending from a layer Output section Context Help Command buttons
- 20. Results of fuzzy command tool Settlement Wells RoadsRivers Unsuitable Suitable
- 21. Conclusions Successful implementation of the generic tool Applicability of the tool to any layer except for complicated fuzzy functions. Illustrates the Need for customizable GIS softwares. Demonstrates GeoMedia Grid as an example of software providing the framework for customizing applications
- 22. Conclusions Future Work – To improve upon the different functions other than linear. Future Work – customizing complicated fuzzy functions if the process is recurring.
- 23. About Me B.Sc. Maths, Physics and Geology M.Sc. Geology (Osmania University, Hyderabad, India) M.Sc. Geoinformatics (HFT, Stuttgart, Germany) Work Research Associate (Software Developer) Currently doing a job as a Software Engineer
- 24. Current Job Project – Integration ofMapWindowGIS Integration of MapWindowGIS into SAFIRA II MMS software Softwares and languages used MapWindowGIS Libraries MapWindow Active X Components Visual Basic 6 25
- 25. MapWindowGIS GIS application made using MapWindowGIS 26
- 26. Possibilities on Selection Single selection Multiple selection Multiple selection Switch selection Multi De-selection Single De-selection Different capabilities on polygon selection 27
- 27. Final integration of MapWinGIS projectFinal Integration of MapWinGIS application into SAFIRA MMS 28
- 28. Inception of MapWindow
- 29. 30

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