Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer International Society for the Prevention and Mitigation of Natural Hazards, vol. " Aftershock probabilistic seismic hazard analysis for Bushehr province in Iran using ETAS model," Nader Davoudi & Hamid Reza Tavakoli & Mehdi Zare & Abdollah Jalilian, 2020." Applications of artificial intelligence for disaster management," Wenjuan Sun & Paolo Bocchini & Brian D." Forecasting Social Conflicts in Africa Using an Epidemic Type Aftershock Sequence Model,"įorecasting, MDPI, vol. Gilian van den Hengel & Philip Hans Franses, 2020." Prediction of Landslide Displacement Based on the Variational Mode Decomposition and GWO-SVR Model," " Locally weighted minimum contrast estimation for spatio-temporal log-Gaussian Cox processes,"Ĭomputational Statistics & Data Analysis, Elsevier, vol. D'Angelo, Nicoletta & Adelfio, Giada & Mateu, Jorge, 2023." Exploring traffic flow databases using space-time plots and data cubes," " Space–time inhomogeneous background intensity estimators for semi-parametric space–time self-exciting point process models,"Īnnals of the Institute of Statistical Mathematics, Springer The Institute of Statistical Mathematics, vol. Chenlong Li & Zhanjie Song & Wenjun Wang, 2020." Forecasting social conflicts in Africa using an Epidemic Type Aftershock Sequence model,"ĮI2018-31, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute. " Warnings about future jumps: properties of the exponential Hawkes model,"ġ3/2020, University of Verona, Department of Economics. Rachele Foschi & Francesca Lilla & Cecilia Mancini, 2020.These are the items that most often cite the same works as this one and are cited by the same works as this one. 85(1), pages 471-486, January.įull references (including those not matched with items on IDEAS) " Earthquake magnitude prediction in Hindukush region using machine learning techniques," " The casualty prediction of earthquake disaster based on Extreme Learning Machine method," Huang Xing & Song Junyi & Huidong Jin, 2020." Forecasting the magnitude of the largest expected earthquake," Robert Shcherbakov & Jiancang Zhuang & Gert Zöller & Yosihiko Ogata, 2019." Prediction of landslide displacement using multi-kernel extreme learning machine and maximum information coefficient based on variational mode decomposition: a case study in Shaanxi, China," Qing Ling & Qin Zhang & Jing Zhang & Lingjie Kong & Weiqi Zhang & Li Zhu, 2021.Journal of the American Statistical Association, American Statistical Association, vol. " Stochastic Declustering of Space-Time Earthquake Occurrences," " One neuron versus deep learning in aftershock prediction," The results show that the VMD-BP model has high prediction accuracy, it performs better than the single BP neural network, and it can effectively predict the earthquake magnitude. The VMD-BP model is then applied for seismic magnitude prediction in the Tibet and Yunnan regions. The features of the past three adjacent seismic events are used as the input of the VMD-BP model, and the magnitude of the next seismic event is considered as the output. For each entry in the chronological earthquake catalog, three features are taken into consideration: magnitude, latitude, and longitude. The proposed model is referred to as VMD-BP. This study builds a new model for seismic magnitude prediction, which uses a classic back propagation (BP) neural network combined with the variational mode decomposition (VMD) technique as a preprocessing for seismic dataset. Therefore, it is of great significance to develop relevant theories and methods of earthquake prediction. Earthquakes instantaneously occur and can cause huge disasters to cities, villages, and human beings.
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