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Support Vector Machine (SVM) Aggregation Modelling
Details
The study of this book is concerned with computation methods for environmental data analysis in order to enable better and faster decision making when dealing with environmental problems. This book addressed the spatio-temporal problem using decentralized computational technique named Scalable SVM Ensemble Learning Method (SSELM). Evaluation criteria for computational air pollution analysis includes: classification accuracy, prediction, spatio-temporal and decentralized analysis, we assert that these criteria can be improved using the proposed SSELM. Special consideration is given to distributed ensemble in order to resolve the spatio-temporal data collection problem (i.e. the data collected from multiple monitoring stations dispersed over a geographical location). Moreover, the experimental results demonstrated that the proposed SSELM produced impressive results compared to SVM ensemble for air pollution analysis in Auckland region. The study of this book is concerned with computation methods for environmental data analysis in order to enable better and faster decision making when dealing with environmental problems.
This book addressed the spatio-temporal problem using decentralized computational technique named Scalable SVM Ensemble Learning Method (SSELM). Evaluation criteria for computational air pollution analysis includes: classification accuracy, prediction, spatio-temporal and decentralized analysis, we assert that these criteria can be improved using the proposed SSELM.
Special consideration is given to distributed ensemble in order to resolve the spatio-temporal data collection problem (i.e. the data collected from multiple monitoring stations dispersed over a geographical location). Moreover, the experimental results demonstrated that the proposed SSELM produced impressive results compared to SVM ensemble for air pollution analysis in Auckland region.
Autorentext
Shahid Ali is Lecturer in Economics at University of Swat. He has done his M. Phil from Applied Economics Research Centre, Karachi. He has recieved a Gold Medal in M Sc Economic. He has published his research papers in reputed national and international journals. He is actively involved in research and his area of interest includes Public Finance.
Weitere Informationen
- Allgemeine Informationen
- Sprache Englisch
- Anzahl Seiten 192
- Herausgeber LAP LAMBERT Academic Publishing
- Gewicht 304g
- Untertitel Spatio-temporal Air Pollution Analysis
- Autor Shahid Ali
- Titel Support Vector Machine (SVM) Aggregation Modelling
- Veröffentlichung 24.05.2021
- ISBN 6203841412
- Format Kartonierter Einband
- EAN 9786203841411
- Jahr 2021
- Größe H220mm x B150mm x T12mm
- GTIN 09786203841411