Results 31 to 40 of about 879,596 (317)

Estimation of prediction error variances via Monte Carlo sampling methods using different formulations of the prediction error variance [PDF]

, 2009
peer-reviewedCalculation of the exact prediction error variance covariance matrix is often computationally too demanding, which limits its application in REML algorithms, the calculation of accuracies of estimated breeding values and the control of ...
Veerkamp Roel F, Calus, M.P., Hickey, John M, Veerkamp, Roel F., Calus Mario PL, Thompson, Robin, Mulder, Han A, Mulder Han A, Calus, M. P. L., Thompson, R., Calus, M.P.L., Veerkamp, R.F., Mulder, H.A., Thompson Robin, Hickey John M, Hickey, J.M.   +15 more
core   +1 more source

Scope 3 emissions: Data quality and machine learning prediction accuracy [PDF]

, 2023
Investors’ sophistication on climate risk is increasing and as part of this they require high-quality and comprehensive Scope 3 emissions data. Accordingly, we investigate Scope 3 emissions data divergence (across different providers), composition (which
Kitto, Adam, McNeil, Ben I, Nguyen, Quyen, Zhang, Renzhu, Pittman, Nicholas A, Diaz-Rainey, Ivan   +5 more
core   +1 more source

The Accuracy of Tide-predicting Machines [PDF]

Nature, 1922
IT seemed to me that Mr. Marmer's first letter left the impression that the U.S.A. machine is one that is free from serious errors of the order of magnitude of those of the British machines, and I raised the question of proof. I said that I should be very glad to know that this machine could produce hourly heights to within 0.05 ft. with a spring range
openaire   +2 more sources

The Effect of Resampling Techniques on Model Performance Classification of Maternal Health Risks

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
Indonesia's maternal mortality rate was the second highest in ASEAN, reflecting the problem of class imbalance in maternal health data. This research aimed to improve prediction accuracy in the classification of pregnant women's diseases through the ...
Nia Mauliza, Aisha Shakila Iedwan, Yoga Pristyanto, Anggit Dwi Hartanto, Arif Nur Rohman   +4 more
doaj   +1 more source

Hybrid Real-Value-Genetic-Algorithm and Extended-Nelder- Mead Algorithm for Short Term Energy Demand Prediction

Journal of ICT
Energy consumption planning of an area is very important. It is essential to accurately predict the amount of short-term power required by an area using a highly effective prediction technique.
Wahab Musa, Ku Ruhana Ku-Mahamud, Sardi Salim, Agung Sediyono   +3 more
doaj   +1 more source

Accuracy of Ultrasonography in Predicting Celiac Disease [PDF]

Archives of Internal Medicine, 2004
Various ultrasonographic (US) signs have been reported in overt celiac disease (CD). The aim of this study was to investigate the diagnostic accuracy of 6 US parameters in predicting CD.One hundred sixty-two consecutive patients with chronic diarrhea (n=105), iron deficiency anemia (n=25), or dyspepsia (n=32) underwent anti-endomysial IgA antibody ...
M. Fraquelli, A. Colli, COLUCCI, ALICE, M.T. Bardella, C. Trovato, R. Pometta, M. Pagliarulo, D. Conte   +7 more
openaire   +2 more sources

Accuracy of circulating adiponectin for predicting gestational diabetes : a systematic review and meta-analysis [PDF]

, 2016
Aims/hypothesis Universal screening for gestational diabetes mellitus (GDM) has not been implemented, and this has had substantial clinical implications. Biomarker-directed targeted screening might be feasible.
Kelsey, Tom, Stamatina Iliodromiti, Nelson, Scott M., Iliodromiti, S, Sattar, N, Thomas W. Kelsey, Sattar, Naveed, Kelsey, TW, Robert S. Lindsay, Sassarini, J, Scott M. Nelson, Jennifer Sassarini, Sassarini, Jennifer, Naveed Sattar, Lindsay, Robert S., Nelson, SM, Iliodromiti, Stamatina, Kelsey, Thomas W., Lindsay, R, Nelson, S, Lindsay, RS   +20 more
core   +1 more source

Genomic Selection at Preliminary Yield Trial Stage: Training Population Design to Predict Untested Lines

Agronomy, 2020
Genomic selection (GS) is being applied routinely in wheat breeding programs. For the evaluation of preliminary lines, this tool is becoming important because preliminary lines are generally evaluated in few environments with no replications due to the ...
Virginia L. Verges, David A. Van Sanford   +1 more
doaj   +1 more source

Prediction Accuracy of Dynamic Mode Decomposition

SIAM Journal on Scientific Computing, 2020
Dynamic mode decomposition (DMD), which the family of singular-value decompositions (SVD), is a popular tool of data-driven regression. While multiple numerical tests demonstrated the power and efficiency of DMD in representing data (i.e., in the interpolation mode), applications of DMD as a predictive tool (i.e., in the extrapolation mode) are scarce.
Hannah Lu, Daniel M. Tartakovsky
openaire   +3 more sources

Artificial neural network algorithm for online glucose prediction from continuous glucose monitoring. [PDF]

, 2010
Background and Aims: Continuous glucose monitoring (CGM) devices could be useful for real-time management of diabetes therapy. In particular, CGM information could be used in real time to predict future glucose levels in order to prevent hypo ...
Pérez Gandía, Carmen, DE LEIVA A, Hernando Pérez, María Elena, Gómez Aguilera, Enrique J., SPARACINO, GIOVANNI, Rigla Cros, Mercedes, RIGLA M, GOMEZ EJ, HERNANDO ME, Leiva, Alberto de, Sparacino, G., PEREZ GANDIA C, COBELLI, CLAUDIO, Facchinetti, A., Cobelli, C., FACCHINETTI, ANDREA   +15 more
core   +2 more sources