Since ancient times, people have tried to predict earthquakes using simple perceptions such as animal behavior. The prediction of the time and strength an earthquake is primary concern. In this study chaotic signal modeling used based on noise detecting anomalies before artificial neural networks (ANNs). Artificial are efficient tools for solving complex problems identification. study, effectiv...

After an earthquake, disaster sites pose a multitude of health and safety concerns. A rescue operation of people trapped in the ruins after an earthquake disaster requires a series of intelligent behavior, including planning. For a successful rescue operation, given a limited number of available actions and regulations, the role of planning in rescue operations is crucial. Fortunately, recent d...

We present a velocity model inversion approach using artificial neural networks (NN). We selected four aftershocks from the 2000 Tottori, Japan, earthquake located around station SMNH01 in order to determine a 1D nearby underground velocity model. An NN was trained independently for each earthquake-station profile. We generated many velocity models and computed their corresponding synthetic wav...

Fault slip distributions provide important insight into the earthquake process. We analyze high-resolution along-strike co-seismic slip profiles of the 1992 Mw = 7.3 Landers and 1999 Mw = 7.1 Hector Mine earthquakes, finding a spatial correlation between fluctuations of the slip distribution and geometrical fault structure. Using a spectral analysis, we demonstrate that the observed variation o...

Several studies have been oriented to develop methodologies for estimating inelastic response of structures; however, the estimation of inelastic seismic response spectra requires complex analyses, in such a way that traditional methods can hardly get an acceptable error. In this paper, an Artificial Neural Network ANN model is presented as an alternative to estimate inelastic response spectra ...

The differences in b values between foreshock and aftershock sequences can be shown to be a statistically significant property of real earthquake sequences if a sufficiently large number of cases is considered, i.e., if the catalogs are long enough. These differences depend on the particulars of the data processing procedures used to define the sequences, such as space-time windowing and defini...

Liquefaction of soil is one of the major causes for the significant damages to the buildings, lifeline systems and harbor facilities caused by the earthquakes. At present artificial intelligence techniques such as artificial neural network (ANN) and support vector machine (SVM) based models are found to be more efficient compared to statistical methods. The present study discusses about the eva...

We propose a new algorithm to rapidly determine earthquake source and ground-motion parameters for earthquake early warning (EEW). This algorithm uses the acceleration, velocity, and displacement waveforms of a single three-component broadband (BB) or strong-motion (SM) sensor to perform real-time earthquake/noise discrimination and near/far source classification. When an earthquake is detected...

Through the last three decades different seismological and engineering approaches for the generation of artificial earthquakes have been proposed. Selection of an appropriate method for the generation of applicable artificial earthquake accelerograms (AEAs) has been a challenging subject in the time history analysis of the structures in the case of the absence of sufficient recorded accelerogra...