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Results 1 to 25 of 25007

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Nonlinear prediction of near-surface temperature via univariate and multivariate time series embeddingKOCAK, Kasim; SAYLAN, Levent; EITZINGER, Josef et al.Ecological modelling. 2004, Vol 173, Num 1, pp 1-7, issn 0304-3800, 7 p.Article

Ordinal time series analysisBANDT, Christoph.Ecological modelling. 2005, Vol 182, Num 3-4, pp 229-238, issn 0304-3800, 10 p.Conference Paper

A note on the Gamma test analysis of noisy input/output data and noisy time seriesJONES, Antonia J; EVANS, D; KEMP, S. E et al.Physica. D. 2007, Vol 229, Num 1, pp 1-8, issn 0167-2789, 8 p.Article

Influence of dynamical noise on time series generated by nonlinear mapsSTRUNFIK, Marek; MACEK, Wieslaw M.Physica. D. 2008, Vol 237, Num 5, pp 613-618, issn 0167-2789, 6 p.Article

Prospects of Long-Time-Series Observations from Dome C for Transit SearchRAUER, Heike; FRUTH, Thomas; ERIKSON, Anders et al.Publications of the Astronomical Society of the Pacific. 2008, Vol 120, Num 870, pp 852-859, issn 0004-6280, 8 p.Article

Origin of the usefulness of the natural-time representation of complex time seriesABE, Sumiyoshi; SARLIS, N. V; SKORDAS, E. S et al.Physical review letters. 2005, Vol 94, Num 17, pp 170601.1-170601.4, issn 0031-9007Article

A time series-based approach for renewable energy modelingFATIH ONUR HOCAOGLU; KARANFIL, Fatih.Renewable & sustainable energy review. 2013, Vol 28, pp 204-214, issn 1364-0321, 11 p.Article

Is the European Union Emissions Trading Scheme (EU ETS) informationally efficient? Evidence from momentum-based trading strategiesCROSSLAND, Jarrod; BIN LI; ROCA, Eduardo et al.Applied energy. 2013, Vol 109, pp 10-23, issn 0306-2619, 14 p.Article

Nitrogen and Phosphorus Flows in the Finnish Agricultural and Forest Sectors, 1910-2000ANTIKAINEN, Riina; HAAPANEN, Reija; LEMOLA, Riitta et al.Water, air and soil pollution. 2008, Vol 194, Num 1-4, pp 163-177, issn 0049-6979, 15 p.Article

Symbolic recurrence plots : A new quantitative framework for performance analysis of manufacturing networksDONNER, R; HINRICHS, U; SCHOLZ-REITER, B et al.The European physical journal. Special topics. 2008, Vol 164, pp 85-104, issn 1951-6355, 20 p.Article

A new similarity measure for histogram comparison and its application in time series analysisSTRELKOV, V. V.Pattern recognition letters. 2008, Vol 29, Num 13, pp 1768-1774, issn 0167-8655, 7 p.Article

Prediction of hourly solar radiation with multi-model frameworkJI WU; CHEE KEONG CHAN.Energy conversion and management. 2013, Vol 76, pp 347-355, issn 0196-8904, 9 p.Article

Cross-correlation time-frequency analysis for multiple EMG signals in Parkinson's disease: a wavelet approachDE MICHELE, Gennaro; SELLO, Stefano; CARBONCINI, Maria Chiara et al.Medical engineering & physics. 2003, Vol 25, Num 5, pp 361-369, issn 1350-4533, 9 p.Article

Time series analysis applied to construct US natural gas price functions for groups of statesKALASHNIKOV, V. V; MATIS, T. I; PEREZ-VALDES, G. A et al.Energy economics. 2010, Vol 32, Num 4, pp 887-900, issn 0140-9883, 14 p.Article

Benchmarking of economic time seriesHILLMER, S. C; ABDELWAHED TRABELSI.Journal of the American Statistical Association. 1987, Vol 82, Num 400, pp 1064-1071, issn 0162-1459Article

The Caterpillar-SSA method for analysis of time series with missing valuesGOLYANDINA, N; OSIPOV, E.Journal of statistical planning and inference. 2007, Vol 137, Num 8, pp 2642-2653, issn 0378-3758, 12 p.Conference Paper

A mode-fitting methodology optimized for very long helioseismic time seriesKORZENNIK, S. G.The Astrophysical journal. 2005, Vol 626, Num 1, pp 585-615, issn 0004-637X, 31 p., 1Article

Overview of the BlockNormal event trigger generatorMCNABB, J. W. C; ASHLEY, M; FINN, L. S et al.Classical and quantum gravity (Print). 2004, Vol 21, Num 20, pp S1705-S1710, issn 0264-9381Conference Paper

Permanent and temporary components of a time series in market analysis and forecastingCRAWFORD, R. G; GEURTS, M. D; RINNE, H. J et al.Journal of statistical computation and simulation (Print). 1988, Vol 29, Num 2, pp 157-177, issn 0094-9655Article

Hidden information within series of measurements. Four examples from atmospheric scienceHELMES, L; JAENICKE, R.Journal of atmospheric chemistry. 1985, Vol 3, Num 1, pp 171-185, issn 0167-7764Conference Paper

Testing for unit roots in seasonal time seriesDICKEY, D. A; HASZA, D. P; FULLER, W. A et al.Journal of the American Statistical Association. 1984, Vol 79, Num 386, pp 355-367, issn 0162-1459Article

A note on inverse autocorrelationsABRAHAM, B; LEDOLTER, J.Biometrika. 1984, Vol 71, Num 3, pp 609-614, issn 0006-3444Article

Chaotic electrical activity of living β-cells in the mouse pancreatic isletKANNO, Takahiro; MIYANO, Takaya; TOKUDA, Isao et al.Physica. D. 2007, Vol 226, Num 2, pp 107-116, issn 0167-2789, 10 p.Article

Predicting oil price movements: A dynamic Artificial Neural Network approachALI ABBASI GODARZI; ROHOLLAH MADADI AMIRI; TALAEI, Alireza et al.Energy policy. 2014, Vol 68, pp 371-382, issn 0301-4215, 12 p.Article

Nonlinear Analysis of Chaotic Time Series in a Natural Circulation Boiling LoopKARMAKAR, Amab; PARUYA, Swapan.Industrial & engineering chemistry research. 2012, Vol 51, Num 50, pp 16467-16481, issn 0888-5885, 15 p.Article

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