Data analytic engine towards the self-management of complex physical systems
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a data analysis and data engine technology, applied in the field of complex systems, can solve problems such as system scale and complexity, methods that require extensive human involvement, and difficult to obtain complete domain knowledg
Inactive Publication Date: 2014-04-17
NEC LAB AMERICA
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[0008]A method for modeling system dynamics, comprising extracting features representative of a temporal evolution of a dynamical system, further comprising; deriving one or more vector trajectories by performing sliding window segmentation of one or more time series, applying a linear test to determine whether the one or more
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Such methods require extensive human involvement and are domain specific.
Also, it may be difficult to obtain complete domain knowledge with the increasing of system scale and compl
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[0018]The process statuses of complex physical systems may be monitored by a large number of sensors. The processes in a complex physical system usually develop some temporal patterns which are inherently governed by the underlying dynamical system and can be captured by the analysis of the time series observations from the sensors. Indeed, the modeling of the system dynamics for temporal patterns can be beneficial to a wide range of applications. However, given the noisy, nonlinear and heterogeneous time series data, it is a critical challenge to model the system dynamics without an a priori knowledge of the system. In one embodiment according to the present principles, a method to model time series dynamics without much a priori knowledge about the system is illustratively provided.
[0019]The above-mentioned method may be based on the fact that an underlying dynamical system of a complex physical system is deterministic and that the state trajectory demonstrates a self-similar beha...
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Abstract
Systems and method for modeling system dynamics, including extracting features representative of a temporal evolution of a dynamical system, further including deriving one or more vector trajectories by performing sliding window segmentation of one or more time series; applying a linear test to determine whether the one or more vector trajectories are linear or nonlinear; and performing linear or nonlinear subspace decomposition on the vector trajectory based on the linear test. The system and method may generate a system evolution model from the extracted features of the dynamical system and determine a fitness score of the system evolution model.
Description
RELATED APPLICATION INFORMATION[0001]This application claims priority to provisional application Ser. No. 61 / 713,006, filed on Oct. 12, 2012, and provisional application Ser. No. 61 / 719,425, filed on Oct. 28, 2012, each incorporated herein by reference.BACKGROUND[0002]1. Technical Field[0003]The present invention relates to complex systems, and, in particular, to modeling, analyzing, and managing time series dynamics in complex physical systems.[0004]2. Description of the Related Art[0005]Recently, cyber-physical systems (CPS) have risen to prominence with examples including automobile and intelligent transportation systems, medical devices and healthcare systems, smart grid, industrial monitoring, etc. Since CPS integrates computing, communication, and storage capabilities in the monitoring entities, a significant amount of measurement data can now be collected, which contains useful knowledge to provide an opportunity for system self-management. Modern industries, such as power pl...
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