Clustering-Based Model Order Reduction for Nonlinear Network Systems

Benner, Peter; Grundel, Sara; Mlinarić, Petar

doi:10.1007/978-3-030-72983-7_4

Cited by 4 publications

(3 citation statements)

References 23 publications

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“…Model abstraction mechanisms & strategies such as projection and partition are applied to reduce quantity or diversity of elements and their interrelations [9]. Partition focuses on breaking down the entity into pieces [31] while projection focuses on compacting the entity [51] and still preserves the physical properties after reduction.…”

Section: Methodsmentioning

confidence: 99%

Developing a GIS Audit Framework in the Context of Information Technology though a Reductive Model Approach

Njiru¹,

Siriba²,

Karanja³

2023

JGIS

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A GIS audit framework is necessary considering the diverse nature of GIS with regard to components, applications and industry. In practice, checklists are generated during the audit process based on specific objectives. There is no standardized list of items that can be used as a reference. The purpose of this study was to develop a GIS audit framework as a foundation for GIS audits. The framework provides that comprehensive approach to various GIS aspects during the audit process. The design builds on a developed conceptual framework where most significant categories of GIS audit parameters namely data quality, software utilization, GIS competency and procedures (work flows) were identified. The study adopted a reductive model approach to simplify the complexity associated with each category of GIS audit parameter. The resultant audit elements for each category are organized in a matrix that forms an integral part of the framework. The columns comprise audit goal, audit questions and audit subjects as indicators which are qualitatively measured.The rows comprise the parameters (data quality, software utilization, personnel competency and procedure (workflows)). To use the framework, an auditor only needs to create an audit checklist that consists of particular parameters and indicators from the framework depending on audit objective. As part of an on-going research, the next step will involve validating the framework through a mock testing process.

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Section: Methodsmentioning

confidence: 99%

Developing a GIS Audit Framework in the Context of Information Technology though a Reductive Model Approach

Njiru¹,

Siriba²,

Karanja³

2023

JGIS

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“…We briefly review some of the recent developments and recommend [34] for further reading. Methods based on reducing the dimension of individual subsystems in a network were described in [35,36], where as methods based on reducing the number of nodes in a network using clustering and projection were described in [37][38][39][40]. Specifically, the latter methods typically rely on Petrov-Galerkin approximation, where projection matrices are constructed to retain certain structural aspects (e.g., clusters) in the reduced network.…”

Section: Mor For Complex Networkmentioning

confidence: 99%

“…where (a) is due to the identity E A 2 ii = P i QP1 n = P i Qd. By merging (37), (38) and putting them in a matrix form, and by defining η as…”

Section: A2 Lemma and Proof: Error Between The Gramians Of Random And...mentioning

confidence: 99%

Controllability of Coarsely Measured Networked Linear Dynamical Systems (Extended Version)

Ghoroghchian¹,

Anguluri²,

Dasarathy³

et al. 2022

Preprint

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We consider the controllability of large-scale linear networked dynamical systems when complete knowledge of network structure is unavailable and knowledge is limited to coarse summaries. We provide conditions under which average controllability of the fine-scale system can be well approximated by average controllability of the (synthesized, reduced-order) coarse-scale system. To this end, we require knowledge of some inherent parametric structure of the fine-scale network that makes this type of approximation possible. Therefore, we assume that the underlying fine-scale network is generated by the stochastic block model (SBM)-often studied in community detection. We then provide an algorithm that directly estimates the average controllability of the fine-scale system using a coarse summary of SBM. Our analysis indicates the necessity of underlying structure (e.g., in-built communities) to be able to quantify accurately the controllability from coarsely characterized networked dynamics. We also compare our method to that of the reduced-order method and highlight the regimes where both can outperform each other. Finally, we provide simulations to confirm our theoretical results for different scalings of network size and density, and the parameter that captures how much community-structure is retained in the coarse summary.

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Order Reduction of Single-Machine-Infinite-Bus System by Utilizing Markov Parameters, Time Moments and Routh Array

Singh,

Meena,

Yadav

et al. 2023

J Control Autom Electr Syst

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Clustering-Based Model Order Reduction for Nonlinear Network Systems

Cited by 4 publications

References 23 publications

Developing a GIS Audit Framework in the Context of Information Technology though a Reductive Model Approach

Developing a GIS Audit Framework in the Context of Information Technology though a Reductive Model Approach

Controllability of Coarsely Measured Networked Linear Dynamical Systems (Extended Version)

Order Reduction of Single-Machine-Infinite-Bus System by Utilizing Markov Parameters, Time Moments and Routh Array

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