| Title | Assessment of Geological Hazards in Ningde Based on Hybrid Intelligent Algorithm |
| Authors | Zhang, Shiliang Wang, Yuxia Chang, Tingcheng |
| Affiliation | Ningde Normal Univ, Dept Comp Sci, Ningde 352100, Fujian, Peoples R China. Peking Univ, Inst Remote Sensing & Geog Informat Syst, Beijing 100087, Peoples R China. |
| Keywords | geological hazard neural network hazards assessment WNN LANDSLIDE HAZARD AHP GIS REGRESSION MODELS |
| Issue Date | 2018 |
| Publisher | SENSORS AND MATERIALS |
| Citation | SENSORS AND MATERIALS. 2018, 30(3,SI), 565-575. |
| Abstract | In recent years, geological hazards have occasionally occurred throughout the world, and have caused immense damage to roads and lives in places where landslides have occurred. Thus, it is of great importance to coordinate the work of regional hazard prevention and reduction. Under these circumstances, hybrid intelligent algorithm (HIA) combined with genetic algorithm (GA) and wavelet neural network (WNN) is proposed with the geological risk assessment analysis in our study. The HIA integrated both the geographic information system (GIS) technology and the artificial neural network model. In the HIA, GA is adopted to initialize the network connection weights and thresholds of WNN. Moreover, in simulations, measurement-obtained data of geological hazards were collected by a geological environment monitoring station and statistic data which were extracted from the map and statistics text data from Ningde City in eastern China. The proposed HIA provides us with increased accuracy compared with established methods using traditional back propagation (BP) neural networks. Our result is of great importance for regional geological hazard prevention, land resources rational development, and proper protection of the geological environment. |
| URI | http://hdl.handle.net/20.500.11897/524892 |
| ISSN | 0914-4935 |
| DOI | 10.18494/SAM.2018.1770 |
| Indexed | SCI(E) EI |
| Appears in Collections: | 地球与空间科学学院 |
