Reconstruction of the distribution of ground motion due to an earthquake is one of the key
technologies for the prediction of seismic damage to infrastructure. Particularly, the …

Objective functions for sensor selection are investigated in linear time-invariant systems with
a large number of sensor candidates. This study compared the performance of sensor sets …

In this paper, we overview, evaluate, and demonstrate the sparse processing particle image
velocimetry (SPPIV) as a real-time flow field estimation method using the particle image …

Optimization approaches that determine sensitive sensor nodes in a large-scale, linear time-
invariant, and discrete-time dynamical system are examined under the assumption of …

This study proposes a method for predicting the wind direction against the simple
automobile model (Ahmed model) and the surface pressure distributions on it by using data …

In this study, a nondominated-solution-based multi-objective greedy method is proposed
and applied to a sensor selection problem based on the multiple indices of the optimal …

The randomized group-greedy (RGG) method and its customized method for large-scale
sensor selection problems are proposed. The randomized greedy sensor selection …

A novel measurement method is developed for a simultaneous measurement of pressure
and temperature on an airfoil by sensitive paints. The proposed method requires two sets of …

Optimization of sensor selection has been studied to monitor complex and large-scale
systems with data-driven linear reduced-order modeling. An algorithm for greedy sensor …

ABSTRACT A vector-measurement-sensor-selection problem in the undersampled and
oversampled cases is considered by extending the previous novel approaches: a greedy …