Computational Mechanics of Building MaterialsOpen OpportunitiesThis project aims to develop advanced
earthquake forecasting models using
bio-inspired Spiking Neural Networks (SNNs).
By exploiting the inherent flexibility of SNNs,
the project will create sparse, multi-step
forecasting models capable of integrating
data from various sources. These models will
be built and tested using the NEST neural
simulator, emphasizing neuroplasticity,
neuromodulation, and neural Darwinism
principles. The goal is to enhance the
efficiency of earthquake predictions by
learning more effectively from limited and
lower-quality data, potentially leading to
significant improvements in forecasting
methods and ultimately reducing the risks
associated with seismic events. - Earthquake Seismology, Knowledge Representation and Machine Learning, Neural Networks, Genetic Alogrithms and Fuzzy Logic
- ETH Zurich (ETHZ), Master Thesis, Semester Project
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