Using advanced soft computing techniques for regional shoreline geoid model estimation and evaluation |
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| Authors: | Mosbeh R Kaloop Mostafa Rabah Ahmed Zaki |
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| Institution: | 1. Department of Civil and Environmental Engineering, Incheon National University, Incheon, South Korea;2. Incheon Disaster Prevention Research Center, Incheon National University, Incheon, South Korea;3. Department of Public Works and Civil Engineering, Mansoura University, Mansoura, Egypt;4. Department of Civil Engineering, Benha Faculty of Engineering, Benha University, Banha, Egypt;5. Department of Civil Engineering, El-Shorouk Academy, El-Shrouk City, Egypt |
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| Abstract: | This study aims at evaluating the global geoid model for a regional shoreline fitting using advanced soft computing techniques and global navigation satellite system/leveling measurements. Artificial neural networks, fuzzy logic, and least square support vector machine models are developed and used to fit the global geoid model for the north coastal Egyptian line. In addition, a novel estimation geoid model is designed and evaluated based on the latest global geoid models. The results of the three estimation models show that they can be used to correct the shoreline geoid model, in terms of root mean square error that ranges from 1.7 to 8.5?cm. Moreover, it is found that the least square vector machine model is a competitive approach with certain advantage in solving complex problems represented by missing data. |
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| Keywords: | ANN fuzzy geoid GNSS least square |
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