Incremental tensor-train decomposition for real-time analysis of high-dimensional infrastructure data

Hadi Salehi; Md Shah Jalal Mazumder

doi:10.1016/j.knosys.2026.116738

Incremental tensor-train decomposition for real-time analysis of high-dimensional infrastructure data

Hadi Salehi
, Md Shah Jalal Mazumder

Louisiana Tech University

Research output: Contribution to journal › Article › peer-review

Original language	English
Article number	116738
Journal	Knowledge-Based Systems
Volume	351
DOIs	https://doi.org/10.1016/j.knosys.2026.116738
State	Published - Oct 9 2026
Externally published	Yes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 11 Sustainable Cities and Communities

ASJC Scopus Subject Areas

Management Information Systems
Software
Information Systems and Management
Artificial Intelligence

Keywords

Anomaly detection
CANDECOMP/PARAFAC (CP)
Forecasting
High-order tensors
Intelligent transportation systems
Multi-modal datasets
Online tensor-train (OTT)
Performance scaling
Real-time analytics
Spatiotemporal data
Structural health monitoring
Tensor decomposition
Tucker decomposition

Access to Document

10.1016/j.knosys.2026.116738

Cite this

@article{ba2959bcd6114b6092dba8089df05426,

title = "Incremental tensor-train decomposition for real-time analysis of high-dimensional infrastructure data",

keywords = "Anomaly detection, CANDECOMP/PARAFAC (CP), Forecasting, High-order tensors, Intelligent transportation systems, Multi-modal datasets, Online tensor-train (OTT), Performance scaling, Real-time analytics, Spatiotemporal data, Structural health monitoring, Tensor decomposition, Tucker decomposition",

author = "Hadi Salehi and Mazumder, \{Md Shah Jalal\}",

note = "Publisher Copyright: {\textcopyright} 2026 Elsevier B.V.",

year = "2026",

month = oct,

day = "9",

doi = "10.1016/j.knosys.2026.116738",

language = "English",

volume = "351",

journal = "Knowledge-Based Systems",

issn = "0950-7051",

}

TY - JOUR

T1 - Incremental tensor-train decomposition for real-time analysis of high-dimensional infrastructure data

AU - Salehi, Hadi

AU - Mazumder, Md Shah Jalal

PY - 2026/10/9

Y1 - 2026/10/9

KW - Anomaly detection

KW - CANDECOMP/PARAFAC (CP)

KW - Forecasting

KW - High-order tensors

KW - Intelligent transportation systems

KW - Multi-modal datasets

KW - Online tensor-train (OTT)

KW - Performance scaling

KW - Real-time analytics

KW - Spatiotemporal data

KW - Structural health monitoring

KW - Tensor decomposition

KW - Tucker decomposition

UR - https://www.scopus.com/pages/publications/105046855963

UR - https://www.scopus.com/pages/publications/105046855963#tab=citedBy

U2 - 10.1016/j.knosys.2026.116738

DO - 10.1016/j.knosys.2026.116738

M3 - Article

AN - SCOPUS:105046855963

SN - 0950-7051

VL - 351

JO - Knowledge-Based Systems

JF - Knowledge-Based Systems

M1 - 116738

ER -

Incremental tensor-train decomposition for real-time analysis of high-dimensional infrastructure data

UN SDGs

ASJC Scopus Subject Areas

Keywords

Access to Document

Other files and links

Fingerprint

Cite this