9786200487728 - Volcano Hotspots Identification using Computing techniques: Identification of VolcanoHotspots in Satellite Images Using Soft Computing Techniques de Gopi, Karnam; R... (9 resultados)

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Taschenbuch. Condición: Neu. Volcano Hotspots Identification using Computing techniques | Identification of VolcanoHotspots in Satellite Images Using Soft Computing Techniques | Karnam Gopi (u. a.) | Taschenbuch | Englisch | 2019 | LAP LAMBERT Academic Publishing | EAN 9786200487728 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Application of technology for mitigating suffering due to natural disasters has always been fore front of researchers. Use of soft computing techniques in disaster prediction and management has interested measures at different levels. Soft computing techniques have given the humans the power and capability to identify events preluded the occurrence of major disasters. Even though it¿s quit impossible to forecast all natural calamities, it is imperative to identify methods that can fore warn the possible occurrence of an event.Soft computing techniques have extensively used by researchers to provide these fore warning capabilities.Multi spectral satellite data have been employed for image processing and analysis. Suitable modification and improvements has been suggested for existing techniques like KNN, SVM, ANN to increase the prediction performance and accuracy. As a part of this an ANFIS based system classifier has also been developed and tested for its performance. 188 pp. Englisch.

Kartoniert / Broschiert. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Gopi KarnamDr. S. Muni Rathnam obtained his Bachelor s degree in Electronics and Communication Engineering (ECE) from JNTU Hyderabad, India. Then he obtained his Master s degree in Electronics Design &Technology from NIT Calicut, Ind.

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Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Application of technology for mitigating suffering due to natural disasters has always been fore front of researchers. Use of soft computing techniques in disaster prediction and management has interested measures at different levels. Soft computing techniques have given the humans the power and capability to identify events preluded the occurrence of major disasters. Even though it's quit impossible to forecast all natural calamities, it is imperative to identify methods that can fore warn the possible occurrence of an event.Soft computing techniques have extensively used by researchers to provide these fore warning capabilities.Multi spectral satellite data have been employed for image processing and analysis. Suitable modification and improvements has been suggested for existing techniques like KNN, SVM, ANN to increase the prediction performance and accuracy. As a part of this an ANFIS based system classifier has also been developed and tested for its performance.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 188 pp. Englisch.

Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Application of technology for mitigating suffering due to natural disasters has always been fore front of researchers. Use of soft computing techniques in disaster prediction and management has interested measures at different levels. Soft computing techniques have given the humans the power and capability to identify events preluded the occurrence of major disasters. Even though it¿s quit impossible to forecast all natural calamities, it is imperative to identify methods that can fore warn the possible occurrence of an event.Soft computing techniques have extensively used by researchers to provide these fore warning capabilities.Multi spectral satellite data have been employed for image processing and analysis. Suitable modification and improvements has been suggested for existing techniques like KNN, SVM, ANN to increase the prediction performance and accuracy. As a part of this an ANFIS based system classifier has also been developed and tested for its performance.