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The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Articles | Volume XLII-4/W18
https://doi.org/10.5194/isprs-archives-XLII-4-W18-975-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/isprs-archives-XLII-4-W18-975-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
19 Oct 2019
| 19 Oct 2019
DISCOVER POINTS OF INTEREST BASED ON USERS’ INTERNET SEARCHES THROUGH AN ONLINE SHOPPING WEBSITE
G. Shahriari Mehr
School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran, Iran
M. R. Delavar
Center of Excellence in Geomatic Engineering in Disaster Management, School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran, Iran
C. Claramunt
Naval Academy Research Institute Lanveoc-Poulmic, BP 600, 29240 Brest Naval, France
B. N. Araabi
School of Electrical and Computer Engineering, School of Engineering, University of Tehran, Tehran, Iran
M. R. A. Dehaqani
School of Electrical and Computer Engineering, School of Engineering, University of Tehran, Tehran, Iran
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Preprint withdrawn
Short summary
Short summary
Accurate and significant wave height prediction with a couple of hours of warning time should offer major safety improvements for coastal and ocean engineering applications. However, significant wave height phenomenon is nonlinear and nonstationary, which makes any prediction simulation a non straightforward task. The aim of the research presented in this paper is to improve predicted significant wave height via a hybrid algorithm.
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