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Autoregressive spectral analysis based on statistical autocorrelation

Hu, Minghui; Shao, Huihe - In: Physica A: Statistical Mechanics and its Applications 376 (2007) C, pp. 139-146

The autoregressive method of spectral analysis is widely used in diverse areas for its solid theoretical foundation. Various aspects of its statistical performance have been investigated. People assume the times series xn to be samples from a zero-mean distribution whose variance remains...

Persistent link: https://www.econbiz.de/10010872837

Three Phase Induction Motor's Stator Turns Fault Analysis Based on Artificial Intelligence

Hussein, H. A. Taha; Ammar, M. E.; Hassan, M. A. Moustafa - In: International Journal of System Dynamics Applications … 6 (2017) 3, pp. 1-19

This article presents a method for fault detection and diagnosis of stator inter-turn short circuit in three phase induction machines. The technique is based on modelling the motor in the dq frame for both health and fault cases to facilitate recognition of motor current. Using an Adaptive...

Persistent link: https://www.econbiz.de/10012047452

A Global Stability of Linearizing Control of Induction Motor for PV Water Pumping Application

Salima, Meziane; Loubna, Atarsia; Riad, Toufouti - In: International Journal of System Dynamics Applications … 7 (2018) 3, pp. 31-56

This article describes how a field oriented control can provide the same performance as it is achieved by a DC motor. However, this technique requires a mechanic sensor and is very sensitive to the variation of motor parameters which results in an undesirable coupling between the flux and the...

Persistent link: https://www.econbiz.de/10012047476

Machine learning and deep learning based methods toward industry 4.0 predictive maintenance in induction motors: State of the art survey

Drakaki, Maria; Karnavas, Yannis L.; Tziafettas, Ioannis A. - In: Journal of Industrial Engineering and Management (JIEM) 15 (2022) 1, pp. 31-57

Purpose: Developments in Industry 4.0 technologies and Artificial Intelligence (AI) have enabled data-driven manufacturing. Predictive maintenance (PdM) has therefore become the prominent approach for fault detection and diagnosis (FD/D) of induction motors (IMs). The maintenance and early FD/D...

Persistent link: https://www.econbiz.de/10013326270

Machine learning and deep learning based methods toward industry 4.0 predictive maintenance in induction motors : state of the art survey

Drakaki, Maria; Karnavas, Yannis L.; Tziafettas, Ioannis A. - In: Journal of industrial engineering and management : JIEM 15 (2022) 1, pp. 31-57

Persistent link: https://www.econbiz.de/10012815091

Using SVD for text classification

Nugumanova, Aliya; Baiburin, Yerzhan - International Institute of Social and Economic Sciences - 2014

Singular value decomposition (SVD) is a way to decompose a matrix into some successive approximation. This … then approximate it by SVD. Obtained matrix is very useful for creating new feature space. We prove our approach by …

Persistent link: https://www.econbiz.de/10011207173

Analyzing existing customers’ websites to improve the customer acquisition process as well as the profitability prediction in B-to-B marketing

THORLEUCHTER, D.; POEL, D. VAN DEN; PRINZIE, A. - Faculteit Economie en Bedrijfskunde, Universiteit Gent - 2011

We investigate the issue of predicting new customers as profitable based on information about existing customers in a business-to-business environment. In particular, we show how latent semantic concepts from textual information of existing customers’ websites can be used to uncover...

Persistent link: https://www.econbiz.de/10009392903

Website-oriented recommendation based on heat spreading and tag-aware collaborative filtering

Zhang, Zi-Ke; Yu, Lu; Fang, Kuan; You, Zhi-Qiang; Liu, … - In: Physica A: Statistical Mechanics and its Applications 399 (2014) C, pp. 82-88

Singular Value Decomposition (SVD) technique to model users features and propose the tag-aware k-nearest neighbor Collaborative …

Persistent link: https://www.econbiz.de/10010744292

Effect of noise filtering on predictions : on the routes of chaos

Guegan, Dominique - HAL - 2008

The detection of chaotic behaviors in commodities, stock markets and weather data is usually complicated by large noise perturbation inherent to the underlying system. It is well known, that predictions, from pure deterministic chaotic systems can be accurate mainly in the short term. Thus, it...

Persistent link: https://www.econbiz.de/10010750796

Sparse-smooth regularized singular value decomposition

Hong, Zhaoping; Lian, Heng - In: Journal of Multivariate Analysis 117 (2013) C, pp. 163-174

We consider penalized singular value decomposition (SVD) for a (noisy) data matrix when the left singular vector has a … contrast to the penalized SVD models proposed by Huang et al. (2009) [12] and by Lee et al. (2010) [14]. We carry out some …

Persistent link: https://www.econbiz.de/10011042044