Spatial data mining techniques to determine optimal policy in lithology applications /
Amira Sobhy Mahmoud
Spatial data mining techniques to determine optimal policy in lithology applications / تقنيات استخراج البيانات المكانية لتحديد السياسة المثلى في تطبيقات علم الخصائص الحجرية Amira Sobhy Mahmoud ; Supervised Omar Soliman , Safaa Mohammed Hassan - Cairo : Amira Sobhy Mahmoud , 2015 - 96 Leaves : charts , facsimiles ; 30cm
Thesis (M.Sc.) - Cairo University - Faculty of Computers and Information - Department of Operations Research and Decision Support
Data Mining (DM) and Decision support Systems (DSS) are two disciplines used to solve difficult practical problems. Decision support tends to rely on the knowledge acquired from experts while data mining attempts to extract it from data. The integration of DM and DSS may improve the quality of problem-solving methods, processes, and achieved objectives. It is becoming an increasingly important tool to transform this data into information. One of important application in data mining is classification of remotely sensing data. Remote Sensing engages electromagnetic sensors to measure and monitor changes in the earths surface and atmosphere. This thesis focuses firstly, to enhance the performance of lithological classification for multispectral Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Satellite Imagery. Two study areas have been applied to extract lithological information; the first area is Wadi- Atalla area is located at Central Eastern Desert of Egypt.
Llithology applications Optimal policy Spatial data
Spatial data mining techniques to determine optimal policy in lithology applications / تقنيات استخراج البيانات المكانية لتحديد السياسة المثلى في تطبيقات علم الخصائص الحجرية Amira Sobhy Mahmoud ; Supervised Omar Soliman , Safaa Mohammed Hassan - Cairo : Amira Sobhy Mahmoud , 2015 - 96 Leaves : charts , facsimiles ; 30cm
Thesis (M.Sc.) - Cairo University - Faculty of Computers and Information - Department of Operations Research and Decision Support
Data Mining (DM) and Decision support Systems (DSS) are two disciplines used to solve difficult practical problems. Decision support tends to rely on the knowledge acquired from experts while data mining attempts to extract it from data. The integration of DM and DSS may improve the quality of problem-solving methods, processes, and achieved objectives. It is becoming an increasingly important tool to transform this data into information. One of important application in data mining is classification of remotely sensing data. Remote Sensing engages electromagnetic sensors to measure and monitor changes in the earths surface and atmosphere. This thesis focuses firstly, to enhance the performance of lithological classification for multispectral Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Satellite Imagery. Two study areas have been applied to extract lithological information; the first area is Wadi- Atalla area is located at Central Eastern Desert of Egypt.
Llithology applications Optimal policy Spatial data