Traditional tsunami forecasting methods are based on seismic observations. The
development of offshore observational devices makes it possible to utilize offshore tsunami …

The problem of optimally placing sensors under a cost constraint arises naturally in the
design of industrial and commercial products, as well as in scientific experiments. We …

We develop greedy algorithms to approximate the optimal solution to the multi-fidelity sensor
selection problem, which is a cost constrained optimization problem prescribing the …

In this work, we propose a new Gaussian process regression (GPR) method:
physicsinformed Kriging (PhIK). In the standard data-driven Kriging, the unknown function of …

We consider cost-constrained sparse sensor selection for full-state reconstruction, applying
a well-known greedy algorithm to dynamical systems for which the usual singular value …

Observing system simulation experiments (OSSEs) were performed in Massachusetts Bay
for the design of optimal monitoring sites for dissolved oxygen (DO) measurements …

Recently, there are numerous tsunami observation networks deployed in several major
tsunamigenic regions. However, guidance on where to optimally place the measurement …

A well-performing data-driven sparse sensor deployment strategy is critical for marine
monitoring systems, as it enables the optimal reconstruction of marine physical quantities …

Estimation of unsteady flowfields around flight vehicles may improve flow interactions and
lead to enhanced vehicle performance. Although flowfield representations can be very high …

Physical and data-based approach for wind forecast has been under rapid development
recently. Yet challenges remain when high spatial resolutions of the velocity distributions are …