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REMOTE SENSING AND GIS  BASED PAVEMENT PERFORMANCE  PREDICTION MODEL USING  ARTIFICIAL NEURAL NETWORK ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
INTRODUCTION ,[object Object],[object Object],[object Object]
Objectives ,[object Object],[object Object],[object Object],[object Object],[object Object]
Scope of Work ,[object Object],[object Object],[object Object],[object Object]
Study Area ,[object Object],[object Object]
 
Data to be Used ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
 
Calculation of PSI ,[object Object],[object Object],[object Object],[object Object],[object Object]
Pavement Condition Scale
Present PSI Scale Along S.P Road
Present Condition Map
Development of ANN Structure
Comparison of ANN architecture of the model
Comparison of ANN and PSI for PPP for testing set
Comparison of ANN and PSI for PPP for testing set
Predicted PSI value along SP Road
Future condition map
Pavement Condition Distribution Graph
Future Condition Distribution
Conclusion ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Future Recommendation ,[object Object],[object Object]
References ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Contd
 ,[object Object],[object Object],[object Object],[object Object],[object Object]
 

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