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DESICION MAKER
 

YALIN YENE
R

November 29, 2020
Methodology
Results
Conclusions
Introduction
Future Work
Introduction Methodology Results Conclusions Future Work Appendix
3
Finding optimal location based on person criteria.
Business Need
Finding optimal borough and region to move in London based on person criteria
Scenario
Introduction Methodology Results Conclusions Future Work Appendix
4
Performing AHP method on London Borough Pro
fi
le


Performing GIS Based Multi Criteria Decision method on Open Streep Map
Solution
Introduction Methodology Results Conclusions Future Work Appendix
5
–Rosaria de F.S.M. Russo and Roberto Camanho / Procedia Computer Science


The Analytic Hierarchy Process (AHP) is a method of
“measurement through pairwise comparisons and relies on
the judgments of experts to derive priority scales”
GIS Based Multi Criteria Decision is a method of
“transforms spatial data into value, by prioritising spatial layer
and geographical rules ”
6
Introduction Methodology Results Conclusions Future Work Appendix
VisualisationImplement AHP
Data WranglingData Acquire
De
fi
ning criteria


sub-criteria
Comparison criteria


weighted
GIS Based Analysis
7
Introduction Results Conclusions Future Work Appendix
Greater London Authority


• London Borough Pro
fi
le (cvs)

UK Open Government Licence

OGL v2


Spatial Data


• Open Street Map


• Borough Border (Polygon)


• Rail Station (Point)


• School (Point)


• Police Station (Point)


• Leisure and Sport (Point)


Methodology
Data Acquire Tools
Data


Manipulation
Data


Visualization
Analytics


Platform
Thematic


Map
8
Introduction Results Conclusions Future Work AppendixMethodology
Data Wrangling
row data
Insights
• Removing columns (unwanted)


• Removing special characters (£)


• Dealing missing value


• Renaming column names


• Converting column types (object to
fl
oat)
9
Introduction Results Conclusions Future Work AppendixMethodology
Implement Model - AHP
10
Introduction Results Conclusions Future Work AppendixMethodology
Implement Model - Criteria / Sub Criteria
Demography Diversity Labour Market Safety Housing
Environment Transport Children Health
Population


Inland Area (hectares)


Average Age


Propor of Pop. Age (0-15)


International Migration
% of Population Born Abroad


% of Largest Migrant Population


Main Language is Not English

New Migrant
Employment Rate


Household Income


% Adult Volunteered


Number of Jobs


Number of Business
Crime Rate


Fires / 1000 Population


Amb. Incident/ 100 Pop
House Price


Council Tax


New Homes
% of Area Greenspace


Total Carbon Emission


Waste Recycling Rate
Number of Cars


% of Adults Who Cycle


Public Transport Accessibility
Achievement of 5 or more at GCSE


Rates of Children Looked After


% of Pupils First Language is Not English


% Children Living in out-of-work
Male Life Expectancy


Female Life Expectancy


Life Satisfaction Score


Worthwhileness Score


Happiness Score


Anxiety Score


Mortality Rate
9 Criteria
37 Sub Criteria
11
Introduction Results Conclusions Future Work AppendixMethodology
Implement Model - Resampling
min max Resample


-1
Resample


1
Population 159000 389600 389600 159000
Inland Area 1212 15013 1212 15013
Average Age 31.40 40.30 40.30 31.40
Proportion of Age 0-15 15.90 27.20 15.90 27.20
Net International
Migration
568 11182 11182 568
Camden
Actual


Camden
Resampled
242500 0.28
2179 -0.86
36.4 -0.12
17.3 -0.75
7504 -0.31
-1.76
-5 50
Camden
12
Introduction Results Conclusions Future Work AppendixMethodology
Implement Model - Criteria Weighted
13
Introduction Results Conclusions Future Work AppendixMethodology
Implement Model - Sample Calculation
Camden
Actual


Camden
Resample
d
Criteria


Weighted
Weighted


Result
242500 0.28 4.6% 0.01
2179 -0.86 26.4% -0.23
36.4 -0.12 9.8% -0.01
17.3 -0.75 15.5% -0.12
7504 -0.31 43.6% -0.14
-1.76
Population
Inland Area
Average Age
Proportion of Age 0-15
Net International
Migration
-0.49
14
Introduction Results Conclusions Future Work AppendixMethodology
Visualisation - Heatmap for Demography
15
Introduction Results Conclusions Future Work AppendixMethodology
Visualisation- Thematic Map for Demography Criteria
16
Introduction Methodology Results Conclusions Future Work Appendix
Diversity Labour Market
Safety Housing
17
Introduction Methodology Results Conclusions Future Work Appendix
Environment Transport
Children Health
18
Introduction Methodology Results Conclusions Future Work Appendix
Criteria Weights
0.0
7.5
15.0
22.5
30.0
Demography Diversity Labour Market Safety Housing Environment Transport Children Health
20%22%
5.9%
11.2%
7.2%
23.9%
2.5%4.4%2.9%
19
Introduction Methodology Results Future Work Appendix
Richmond upon Thames, Bromley and
Kingston upon Thames are most suitable
boroughs for moving in Outer London. Because of
metrics that shown below:


Safety


Children


Health


Wandsworth is most suitable borough for
moving in inner London. Because of


Safety (0.76)


Housing (0.78) metrics


Kensington and Chelsea is the second suitable
borough for moving in inner London Because of


Transport (0.74),


Health (0.96)


Children (0.65)


Conclusions
20
Introduction Methodology Results Future Work AppendixConclusions
21
Introduction Methodology Results Future Work AppendixConclusions
22
Introduction Methodology Results Future Work AppendixConclusions
Rail Station
23
Introduction Methodology Results Future Work AppendixConclusions
Rail Station


Police Station
24
Introduction Methodology Results Future Work AppendixConclusions
Rail Station


Police Station

Leisure or Sport Centre
25
Introduction Methodology Results Future Work AppendixConclusions
Rail Station


Police Station

Leisure or Sport Centre


School (Outstanding)


School (Good)
26
Introduction Methodology Results Future Work AppendixConclusions
Rail Station
27
Introduction Methodology Results Future Work AppendixConclusions
Rail Station


0.00 - 0.25 miles
28
Introduction Methodology Results Future Work AppendixConclusions
Rail Station


0.25 - 0.50 miles
29
Introduction Methodology Results Future Work AppendixConclusions
Rail Station


0.50 - 1.00 miles
30
Introduction Methodology Results Future Work AppendixConclusions
31
Introduction Methodology Results Future Work AppendixConclusions
32
Introduction Methodology Results Future Work AppendixConclusions
Building
33
Introduction Methodology Results Future Work AppendixConclusions
Building
34
Introduction Methodology Results Future Work AppendixConclusions
95970
35
Introduction Methodology Results Future Work AppendixConclusions
94
South
fi
elds
Putney
Earls
fi
eld
36
Introduction Methodology Results Conclusions Future Work Appendix
This project can be extended further by;


• Developing GUI and Performing AHP and GIS Based Multi Criteria Decision


• Obtain additional data both pro
fi
le and spatial


• Number of crime types details

• Shopping Centre, Cafe, Pub etc.
THANK YOU
YALIN YENE
R

+44 7786 76155
9

yalinyener@gmail.com


https://github.com/yalinyener


https://medium.com/@yalinyener


https://www.linkedin.com/in/yalinyener

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Decision maker

  • 1. DESICION MAKER YALIN YENE R November 29, 2020
  • 3. Introduction Methodology Results Conclusions Future Work Appendix 3 Finding optimal location based on person criteria. Business Need Finding optimal borough and region to move in London based on person criteria Scenario
  • 4. Introduction Methodology Results Conclusions Future Work Appendix 4 Performing AHP method on London Borough Pro fi le Performing GIS Based Multi Criteria Decision method on Open Streep Map Solution
  • 5. Introduction Methodology Results Conclusions Future Work Appendix 5 –Rosaria de F.S.M. Russo and Roberto Camanho / Procedia Computer Science The Analytic Hierarchy Process (AHP) is a method of “measurement through pairwise comparisons and relies on the judgments of experts to derive priority scales” GIS Based Multi Criteria Decision is a method of “transforms spatial data into value, by prioritising spatial layer and geographical rules ”
  • 6. 6 Introduction Methodology Results Conclusions Future Work Appendix VisualisationImplement AHP Data WranglingData Acquire De fi ning criteria sub-criteria Comparison criteria weighted GIS Based Analysis
  • 7. 7 Introduction Results Conclusions Future Work Appendix Greater London Authority • London Borough Pro fi le (cvs) UK Open Government Licence OGL v2 Spatial Data • Open Street Map • Borough Border (Polygon) • Rail Station (Point) • School (Point) • Police Station (Point) • Leisure and Sport (Point) Methodology Data Acquire Tools Data Manipulation Data Visualization Analytics Platform Thematic Map
  • 8. 8 Introduction Results Conclusions Future Work AppendixMethodology Data Wrangling row data Insights • Removing columns (unwanted) • Removing special characters (£) • Dealing missing value • Renaming column names • Converting column types (object to fl oat)
  • 9. 9 Introduction Results Conclusions Future Work AppendixMethodology Implement Model - AHP
  • 10. 10 Introduction Results Conclusions Future Work AppendixMethodology Implement Model - Criteria / Sub Criteria Demography Diversity Labour Market Safety Housing Environment Transport Children Health Population Inland Area (hectares) Average Age Propor of Pop. Age (0-15) International Migration % of Population Born Abroad % of Largest Migrant Population Main Language is Not English New Migrant Employment Rate Household Income % Adult Volunteered Number of Jobs Number of Business Crime Rate Fires / 1000 Population Amb. Incident/ 100 Pop House Price Council Tax New Homes % of Area Greenspace Total Carbon Emission Waste Recycling Rate Number of Cars % of Adults Who Cycle Public Transport Accessibility Achievement of 5 or more at GCSE Rates of Children Looked After % of Pupils First Language is Not English % Children Living in out-of-work Male Life Expectancy Female Life Expectancy Life Satisfaction Score Worthwhileness Score Happiness Score Anxiety Score Mortality Rate 9 Criteria 37 Sub Criteria
  • 11. 11 Introduction Results Conclusions Future Work AppendixMethodology Implement Model - Resampling min max Resample -1 Resample 1 Population 159000 389600 389600 159000 Inland Area 1212 15013 1212 15013 Average Age 31.40 40.30 40.30 31.40 Proportion of Age 0-15 15.90 27.20 15.90 27.20 Net International Migration 568 11182 11182 568 Camden Actual Camden Resampled 242500 0.28 2179 -0.86 36.4 -0.12 17.3 -0.75 7504 -0.31 -1.76 -5 50 Camden
  • 12. 12 Introduction Results Conclusions Future Work AppendixMethodology Implement Model - Criteria Weighted
  • 13. 13 Introduction Results Conclusions Future Work AppendixMethodology Implement Model - Sample Calculation Camden Actual Camden Resample d Criteria Weighted Weighted Result 242500 0.28 4.6% 0.01 2179 -0.86 26.4% -0.23 36.4 -0.12 9.8% -0.01 17.3 -0.75 15.5% -0.12 7504 -0.31 43.6% -0.14 -1.76 Population Inland Area Average Age Proportion of Age 0-15 Net International Migration -0.49
  • 14. 14 Introduction Results Conclusions Future Work AppendixMethodology Visualisation - Heatmap for Demography
  • 15. 15 Introduction Results Conclusions Future Work AppendixMethodology Visualisation- Thematic Map for Demography Criteria
  • 16. 16 Introduction Methodology Results Conclusions Future Work Appendix Diversity Labour Market Safety Housing
  • 17. 17 Introduction Methodology Results Conclusions Future Work Appendix Environment Transport Children Health
  • 18. 18 Introduction Methodology Results Conclusions Future Work Appendix Criteria Weights 0.0 7.5 15.0 22.5 30.0 Demography Diversity Labour Market Safety Housing Environment Transport Children Health 20%22% 5.9% 11.2% 7.2% 23.9% 2.5%4.4%2.9%
  • 19. 19 Introduction Methodology Results Future Work Appendix Richmond upon Thames, Bromley and Kingston upon Thames are most suitable boroughs for moving in Outer London. Because of metrics that shown below: Safety Children Health Wandsworth is most suitable borough for moving in inner London. Because of Safety (0.76) Housing (0.78) metrics Kensington and Chelsea is the second suitable borough for moving in inner London Because of Transport (0.74), Health (0.96) Children (0.65) Conclusions
  • 20. 20 Introduction Methodology Results Future Work AppendixConclusions
  • 21. 21 Introduction Methodology Results Future Work AppendixConclusions
  • 22. 22 Introduction Methodology Results Future Work AppendixConclusions Rail Station
  • 23. 23 Introduction Methodology Results Future Work AppendixConclusions Rail Station Police Station
  • 24. 24 Introduction Methodology Results Future Work AppendixConclusions Rail Station Police Station Leisure or Sport Centre
  • 25. 25 Introduction Methodology Results Future Work AppendixConclusions Rail Station Police Station Leisure or Sport Centre School (Outstanding) School (Good)
  • 26. 26 Introduction Methodology Results Future Work AppendixConclusions Rail Station
  • 27. 27 Introduction Methodology Results Future Work AppendixConclusions Rail Station 0.00 - 0.25 miles
  • 28. 28 Introduction Methodology Results Future Work AppendixConclusions Rail Station 0.25 - 0.50 miles
  • 29. 29 Introduction Methodology Results Future Work AppendixConclusions Rail Station 0.50 - 1.00 miles
  • 30. 30 Introduction Methodology Results Future Work AppendixConclusions
  • 31. 31 Introduction Methodology Results Future Work AppendixConclusions
  • 32. 32 Introduction Methodology Results Future Work AppendixConclusions Building
  • 33. 33 Introduction Methodology Results Future Work AppendixConclusions Building
  • 34. 34 Introduction Methodology Results Future Work AppendixConclusions 95970
  • 35. 35 Introduction Methodology Results Future Work AppendixConclusions 94 South fi elds Putney Earls fi eld
  • 36. 36 Introduction Methodology Results Conclusions Future Work Appendix This project can be extended further by; • Developing GUI and Performing AHP and GIS Based Multi Criteria Decision • Obtain additional data both pro fi le and spatial • Number of crime types details • Shopping Centre, Cafe, Pub etc.
  • 37. THANK YOU YALIN YENE R +44 7786 76155 9 yalinyener@gmail.com https://github.com/yalinyener https://medium.com/@yalinyener https://www.linkedin.com/in/yalinyener