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Open Access research that improves the lives of children and families...

Strathprints makes available scholarly Open Access content by scholars in the School of Social Work & Social Policy, based within the Faculty of Humanities & Social Sciences (HaSS) .

Research at Social Work & Social Policy seeks to understand the social experiences of children, young people and families, in order to support evidence-informed policy. Issues of public health, health inequalities and health history within the context of social work are also important research themes. Research centres, such as CELCIS (Centre for Excellence for Children's Care & Protection) and the CYCJ (Centre for Youth & Criminal Justice) operate in furtherance of these research areas, supporting evidence-based solutions to improve child wellbeing and improvements in youth justice, and the lives of families and communities.

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Group by: Publication Date | Item type | No Grouping
Jump to: 2019 | 2018 | 2017
Number of items: 14.

2019

Pandit, Ravi Kumar and Infield, David (2019) Comparative analysis of Gaussian Process power curve models based on different stationary covariance functions for the purpose of improving model accuracy. Renewable Energy, 140. pp. 190-202. ISSN 0960-1481

Pandit, Ravi Kumar and Infield, David and Kolios, Athanasios (2019) Comparison of advanced non-parametric models for wind turbine power curves. IET Renewable Power Generation, 13 (9). pp. 1503-1510. ISSN 1752-1416

Pandit, Ravi Kumar and Infield, David (2019) SCADA based nonparametric models for condition monitoring of a wind turbine. The Journal of Engineering. pp. 1-5. ISSN 2051-3305

2018

Pandit, Ravi and Infield, David (2018) Comparative analysis of binning and support vector regression for wind turbine rotor speed based power curve use in condition monitoring. In: 2018 53rd International Universities Power Engineering Conference (UPEC). IEEE, Piscataway, NJ. ISBN 9781538629109

Pandit, Ravi Kumar and Infield, David and Carroll, James (2018) Incorporating air density into a Gaussian process wind turbine power curve model for improving fitting accuracy. Wind Energy. pp. 1-14. ISSN 1095-4244

Pandit, Ravi Kumar and Infield, David (2018) Comparative assessments of binned and support vector regression-based blade pitch curve of a wind turbine for the purpose of condition monitoring. International Journal of Energy and Environmental Engineering. pp. 1-8. ISSN 2008-9163

Pandit, Ravi Kumar and Infield, David (2018) Comparative analysis of binning and Gaussian Process based blade pitch angle curve of a wind turbine for the purpose of condition monitoring. Journal of Physics: Conference Series, 1102 (1). 012037. ISSN 1742-6588

Pandit, Ravi Kumar and Infield, David (2018) Comparison of binned and Gaussian Process based wind turbine power curves for condition monitoring purposes. Journal of Maintenance Engineering, 2.

Pandit, Ravi Kumar and Infield, David (2018) Comparative study of binning and gaussian process based rotor curves of a wind turbine for the purpose of condition monitoring. In: 3rd International Conference on Offshore Renewable Energy, 2018-08-29 - 2018-08-30.

Pandit, Ravi and Infield, David (2018) Gaussian process operational curves for wind turbine condition monitoring. Energies, 11 (7). ISSN 1996-1073

Pandit, Ravi Kumar and Infield, David (2018) Performance assessment of a wind turbine using SCADA based Gaussian Process model. International Journal of Prognostics and Health Management, 9 (1). 023. ISSN 2153-2648

Pandit, Ravi Kumar and Infield, David (2018) SCADA-based wind turbine anomaly detection using Gaussian Process (GP) models for wind turbine condition monitoring purposes. IET Renewable Power Generation. ISSN 1752-1416

Pandit, Ravi and Infield, David (2018) QQ plot for assessment of Gaussian Process wind turbine power curve error distribution function. In: 9th European Workshop on Structural Health Monitoring. British Institute of Non-Destructive Testing, Northampton. (In Press)

2017

Pandit, Ravi Kumar and Infield, David (2017) Using Gaussian process theory for wind turbine power curve analysis with emphasis on the confidence intervals. In: 2017 6th International Conference on Clean Electrical Power (ICCEP). IEEE, Piscataway, N.J., pp. 744-749. ISBN 978-1-5090-4683-6

This list was generated on Wed Nov 20 20:29:05 2019 GMT.