David Infield

Electrical and Electronic Engineering · 2003–2019

A researcher in the Science corpus: 5 papers; trusts 6 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Electrical and Electronic Engineering — 8 citations into it

Whom David Infield trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Radford M. Neal
2. Helmut Ltkepohl

Who trusts David Infield overall

1. Wei Qiao
2. Pramod Bangalore
3. Weizhong Yan

Papers from David Infield's perspective

Ordered by how strongly the researchers David Infield trusts endorse each paper. Same corpus, a different order for every researcher.

1. Standardizing the Performance Evaluation of Short-Term Wind Power Prediction Models
2. Powering Up With Space-Time Wind Forecasting
3. Pattern Recognition and Machine Learning
4. Modelling the UK residential energy sector under long-term decarbonisation scenarios: Comparison between energy systems and sectoral modelling approaches
5. Matrix Computations
6. New Introduction to Multiple Time Series Analysis
7. Complex-Valued Matrix Differentiation: Techniques and Key Results (IEEE Transactions on Signal Processing)
8. Estimating the Dimension of a Model
9. Physical Approach to Short-Term Wind Power Prediction
10. Learning and relearning in Boltzmann machines

Their papers

• Online wind turbine fault detection through automated SCADA data analysis (2009) — 479 citations
• The evolution of electricity demand and the role for demand side participation, in buildings and transport (2013) — 161 citations
• Short-term forecasting and uncertainty analysis of wind turbine power based on long short-term memory network and Gaussian mixture model (2019) — 356 citations
• Short-term spatio-temporal prediction of wind speed and direction (2014)
• Experimental study of variations of the solar spectrum of relevance to thin film solar cells (2003) — 135 citations