We investigate data-driven, simple-to-implement residential environmental models that can serve as the basis for energy saving algorithms in both retrofits and new designs of buildings. Despite nonlinearity underlying dynamics, using Koopman operator theory framework this study we show a linear second order model embedding, captures physics occur inside single or multi zone space does well when...

Data centers aim at provisioning on-demand processing, storage and networking capabilities in a reliable scalable way. In this context, proper maintenance of IT equipment within data center (DC) premises is crucial as it ensures prolonged lifetime servers uninterrupted availability resources. This paper focuses on the analysis how exact temperatures real big DC cluster 10 368 cores correspond t...

Condition monitoring of power transformers, which are key components electrical systems, is essential to identify incipient faults and avoid catastrophic failures. In this paper machine learning algorithms, i.e., nonlinear autoregressive neural networks support vector machines, proposed model the transformer thermal behavior for purpose monitoring. The models developed based on historical measu...

This study proposes, for the first time, an approach to remove thermal noise from wave coherency matrix, $\mathrm {C_{2}}$ , estimated single-look complex dual-polarization Interferometric Wide Swath mode Sentinel-1 synthetic aperture...