Geochemical Mechanics And Deep Neural Network Modeling
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Geochemical Mechanics and Deep Neural Network Modeling
The recent understandings about global earth mechanics are widely based on huge amounts of monitoring data accumulated using global networks of precise seismic stations, satellite monitoring of gravity, very large baseline interferometry, and the Global Positioning System. New discoveries in materials sciences of rocks and minerals and of rock deformation with fluid water in the earth also provide essential information. This book presents recent work on natural geometry, spatial and temporal distribution patterns of various cracks sealed by minerals, and time scales of their crack sealing in the plate boundary. Furthermore, the book includes a challenging investigation of stochastic earthquake prediction testing by means of the updated deep machine learning of a convolutional neural network with multi-labeling of large earthquakes and of the generative autoencoder modeling of global correlated seismicity. Their manifestation in this book contributes to the development of human society resilient from natural hazards. Presented here are (1) mechanics of natural crack sealing and fluid flow in the plate boundary regions, (2) large-scale permeable convection of the plate boundary, (3) the rapid process of massive extrusion of plate boundary rocks, (4) synchronous satellite gravity and global correlated seismicity, (5) Gaussian network dynamics of global correlated seismicity, and (6) prediction testing of plate boundary earthquakes by machine learning and generative autoencoders.
Physics of Geochemical Mechanics and Deep Neural Network Modeling with Diffusion Augmentation
This book provides a new data augmentation method based on the local stochastic distribution patterns in natural time series data of global and regional seismicity rates and their correlated seismicity rates. The augmentation procedure is called the diffusion – denoising augmentation method from the local Gaussian distribution of segmented data of long time series. This method makes it possible to apply the deep machine learning necessary to neural network prediction of rare large earthquakes in the global and regional earth system. The book presents the physical background of the processes showing the development of characteristic features in the global and regional correlated seismicity dynamics, which are manifested by the successive time series of 1990–2023. Physical processes of the correlated global seismicity change and the earth’s rotation, fluctuation of plate motion, and the earth’s ellipsoid ratio (C20 of satellite gravity change) are proposed in this book. The equivalency between Gaussian seismicity network dynamics and the minimal nonlinear dynamics model of correlated seismicity rates is also provided. In addition, the book contains simulated models of the shear crack jog wave, precipitation of minerals in the jog, and jog accumulation inducing shear crack propagation which leads to earthquakes in the plate boundary rocks under permeable fluid flow.
Computational Science and Its Applications – ICCSA 2023 Workshops
This nine-volume set LNCS 14104 – 14112 constitutes the refereed workshop proceedings of the 23rd International Conference on Computational Science and Its Applications, ICCSA 2023, held at Athens, Greece, during July 3–6, 2023. The 350 full papers and 29 short papers and 2 PHD showcase papers included in this volume were carefully reviewed and selected from a total of 876 submissions. These nine-volumes includes the proceedings of the following workshops: Advances in Artificial Intelligence Learning Technologies: Blended Learning, STEM, Computational Thinking and Coding (AAILT 2023); Advanced Processes of Mathematics and Computing Models in Complex Computational Systems (ACMC 2023); Artificial Intelligence supported Medical data examination (AIM 2023); Advanced and Innovative web Apps (AIWA 2023); Assessing Urban Sustainability (ASUS 2023); Advanced Data Science Techniques with applications in Industry and Environmental Sustainability (ATELIERS 2023); Advances in Web Based Learning (AWBL 2023); Blockchain and Distributed Ledgers: Technologies and Applications (BDLTA 2023); Bio and Neuro inspired Computing and Applications (BIONCA 2023); Choices and Actions for Human Scale Cities: Decision Support Systems (CAHSC-DSS 2023); and Computational and Applied Mathematics (CAM 2023).