Results 271 to 280 of about 11,351,001 (331)

Non-intrusive appliance recognition

2012 3rd IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe), 2012
Energy conservation becomes more important nowadays. The use of smart meters and, in the near future, smart appliances, are the key to achieve reduction in energy consumption. This research proposes a non-intrusive appliance monitor and recognition system for implementation on an embedded system. The research focuses on computational efficiency of such
Hoogsteen, Gerwin, Krist, J.O., Bakker, Vincent, Smit, Gerardus Johannes Maria   +3 more
openaire   +2 more sources

A non-intrusive model-order reduction of geometrically nonlinear structural dynamics using modal derivatives

Mechanical Systems and Signal Processing, 2021
Non-intrusive model-order reduction methods are beneficial for reducing the computational costs of dynamic analysis of nonlinear finite element models, developed in programs that do not release nonlinear element forces and Jacobians (e.g., commercial ...
Daniel J Rixen, Paolo Tiso, Antoine Brandt   +2 more
exaly   +2 more sources

Deep Domain Adaptation for Non-Intrusive Load Monitoring Based on a Knowledge Transfer Learning Network

IEEE Transactions on Smart Grid, 2022
Understanding customers’ energy consumption at the individual appliances level is crucial for the planning and implementation of demand response (DR) programs.
Jun Lin, Jin Ma, Jianguo Zhu, Huishi Liang   +3 more
semanticscholar   +1 more source

SAMNet: Toward Latency-Free Non-Intrusive Load Monitoring via Multi-Task Deep Learning

IEEE Transactions on Smart Grid, 2022
Non-intrusive load monitoring (NILM), including state detection and energy disaggregation, aims to identify the on/off state and energy consumption from the aggregate load of a building.
Yinyan Liu, Jing Qiu, Jin Ma
semanticscholar   +1 more source

Real-time non-intrusive load monitoring: A light-weight and scalable approach

Energy and Buildings, 2021
Non-intrusive load monitoring (NILM) is a topic that lately attracts both the academic and the industrial interest. NILM is used to reveal useful information regarding the consumption breakdown on appliance or activity level, thus can be a key solution ...
C. Athanasiadis, T. Papadopoulos, D. Doukas   +2 more
semanticscholar   +1 more source

Generalizability Improvement of Deep Learning-Based Non-Intrusive Load Monitoring System Using Data Augmentation

IEEE Transactions on Smart Grid, 2021
Practical application of deep learning based non-intrusive load monitoring (NILM) system requires the deep neural network model to generalize on new unseen data.
Hasan Rafiq, Xiaohan Shi, Hengxu Zhang, Huimin Li, Manesh Kumar Ochani, A. Shah   +5 more
semanticscholar   +1 more source

Adaptive Non-Intrusive Load Monitoring Based on Feature Fusion

IEEE Sensors Journal, 2022
Intelligent power management system is an important part of the smart grid, in which the non-intrusive load monitoring technology is one of the key technologies.
Junhyuk Kang, Miao Yu, Lingxia Lu, Bingnan Wang, Z. Bao   +4 more
semanticscholar   +1 more source

Non‐intrusive object introspection in C++

Software: Practice and Experience, 2001
AbstractWe describe the design and implementation of system architecture to support object introspection in C++. In this system, information is collected by parsing class declarations, and is used to build a supporting environment for object introspection.
Chuang, Tyng-Ruey, Kuo, Y. S., Wang, Chien-Min   +2 more
openaire   +2 more sources

A Comprehensive Review of Latent Space Dynamics Identification Algorithms for Intrusive and Non-Intrusive Reduced-Order-Modeling

arXiv.org
Numerical solvers of partial differential equations (PDEs) have been widely employed for simulating physical systems. However, the computational cost remains a major bottleneck in various scientific and engineering applications, which has motivated the ...
C. Bonneville, Xiaolong He, April Tran, Jun Sur Richard Park, William D. Fries, D. Messenger, S. W. Cheung, Yeonjong Shin, D. Bortz, Debojyoti Ghosh, Jiun-Shyan Chen, J. Belof, Youngsoo Choi   +12 more
semanticscholar   +1 more source

Non-intrusive Methods

2010
In this chapter, we focus our attention on non-intrusive methods for the approximation of an output of a model involving random data, parametrized by a finite set of independent random parameters defined on a suitable probability space. As discussed Chap. 2, we are concerned with models having a unique solution for almost all realizations of the random
O. P. Le Maître, O. M. Knio
openaire   +1 more source