An effective density based approach to detect complex data clusters using notion of neighborhood difference

Nagaraju, Samudrala; Kashyap, Manish; Bhattachraya, Mahua

doi:10.1007/s11633-016-1038-7

Cited by 8 publications

(2 citation statements)

References 24 publications

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“…Density-based clustering algorithms include density-based spatial clustering of applications with noise (DBSCAN). Created in 1996, this was the first algorithm to use data density [89].…”

Section: Density-based Clusteringmentioning

confidence: 99%

Review of Fault Diagnosis Methods for Induction Machines in Railway Traction Applications

Issa,

Clerc,

Hologne-Carpentier

et al. 2024

Energies

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Induction motors make up approximately 80% of the electric motors in the railway sector due to their robustness, high efficiency, and low maintenance cost. Nevertheless, these motors are subject to failures which can lead to costly downtime and service interruptions. In recent years, there has been a growing interest in developing fault diagnosis systems for railway traction motors using advanced non-invasive detection and data analysis techniques. Implementing these methods in railway applications can prove challenging due to variable speed and low-load operating conditions, as well as the use of inverter-fed motor drives. This comprehensive review paper summarizes general methods of fault diagnosis for induction machines. It details the faults seen in induction motors, the most relevant signals measured for fault detection, the signal processing techniques for fault extraction as well as some classification algorithms for diagnosis purposes. By giving the advantages and drawbacks of each technique, it helps select the appropriate method that could address the challenges of railway applications.

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“…Density-based clustering algorithms include density-based spatial clustering of applications with noise (DBSCAN). Created in 1996, this was the first algorithm to use data density [89].…”

Section: Density-based Clusteringmentioning

confidence: 99%

Review of Fault Diagnosis Methods for Induction Machines in Railway Traction Applications

Issa,

Clerc,

Hologne-Carpentier

et al. 2024

Energies

View full text Add to dashboard Cite

show abstract

“…The significance is that the developer can pre-determine a desired performance through the model and can determine the proportion of developers in each development project, so that the total development risk is minimized. Different expectation performance has different minimum variance combinations, which constitutes the minimum variance set [4]. It provides a good means to accurately measure the risk and performance of securities development projects, but this model involves calculating the covariance matrix of all assets.…”

Section: Grey Clustering Extraction and Analysis Algorithmmentioning

confidence: 99%

Optimization of software project evaluation system

Ding¹

2020

SSURJ

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Starting from the problems of imperfect evaluation index system, non-standard evaluation method and single factor of performance evaluation model, this paper applies the unified grey clustering analysis algorithm to establish the index system of software organization status and software project characteristics, and defines the connotation of software project performance. A new network topology design method is proposed, and a software project performance evaluation model based on fuzzy neural network is established. An improved particle swarm optimization algorithm is introduced to solve the problem of determining the connection weight coefficient of the evaluation model accurately and efficiently. This paper introduces the basic concept of project performance evaluation, and explains the necessity and importance of performance evaluation in the project.

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An improved frequent pattern tree: the child structured frequent pattern tree CSFP-tree

Jamsheela¹,

Raju

2022

Pattern Anal Applic

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An effective density based approach to detect complex data clusters using notion of neighborhood difference

Cited by 8 publications

References 24 publications

Review of Fault Diagnosis Methods for Induction Machines in Railway Traction Applications

Review of Fault Diagnosis Methods for Induction Machines in Railway Traction Applications

Optimization of software project evaluation system

An improved frequent pattern tree: the child structured frequent pattern tree CSFP-tree

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