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Results 1 to 25 of 16539

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Forecasting and recombining time-series components by using neural networksHANSEN, J. V; NELSON, R. D.The Journal of the Operational Research Society. 2003, Vol 54, Num 3, pp 307-317, issn 0160-5682, 11 p.Article

Interrupted time series analysis in clinical researchMATOWE, Lloyd K; LEISTER, Cathie A; CRIVERA, Concetta et al.The Annals of pharmacotherapy. 2003, Vol 37, Num 7-8, pp 1110-1116, issn 1060-0280, 7 p.Article

A method for determinism in short time series, and its application to stationary EEGJEONG, Jaeseung; GORE, John C; PETERSON, Bradley S et al.IEEE transactions on biomedical engineering. 2002, Vol 49, Num 11, pp 1374-1379, issn 0018-9294, 6 p.Article

Synthetic generation of standard sky types series using Markov Transition MatricesTORRES, J. L; DE BIAS, M; TORRES, L. M et al.Renewable energy. 2014, Vol 62, pp 731-736, issn 0960-1481, 6 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

A note on tests for nonlinearity in a vector time seriesHARVILL, J. L; RAY, B. K.Biometrika. 1999, Vol 86, Num 3, pp 728-734, issn 0006-3444Article

What drives the change in UK household energy expenditure and associated CO2 emissions? Implication and forecast to 2020CHITNIS, Mona; HUNT, Lester C.Applied energy. 2012, Vol 94, pp 202-214, issn 0306-2619, 13 p.Article

Methods for comparison of parameters from longitudinal rhythmometric models with multiple componentsFERNANDEZ, José R; MOJON, Artemio; HERMIDA, Ramon C et al.Chronobiology international. 2003, Vol 20, Num 3, pp 495-513, issn 0742-0528, 19 p.Article

Comparison of predictability of epileptic seizures by a linear and a nonlinear methodMCSHARRY, Patrick E; SMITH, Leonard A; TARASSENKO, Lionel et al.IEEE transactions on biomedical engineering. 2003, Vol 50, Num 5, pp 628-633, issn 0018-9294, 6 p.Article

Discerning nonstationarity from nonlinearity in seizure-free and preseizure EEG recordings from epilepsy patientsRIEKE, Christoph; MORMANN, Florian; ANDRZEJAK, Ralph G et al.IEEE transactions on biomedical engineering. 2003, Vol 50, Num 5, pp 634-639, issn 0018-9294, 6 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

Linearity analysis on stationary segments of hydrologic time seriesCHEN, Huey-Long; RAMACHANDRA RAO, A.Journal of hydrology (Amsterdam). 2003, Vol 277, Num 1-2, pp 89-99, issn 0022-1694, 11 p.Article

Trend assessment in a long memory dependence model using the discrete wavelet transformCRAIGMILE, Peter F; GUTTORP, Peter; PERCIVAL, Donald B et al.EnvironMetrics (London, Ont.). 2004, Vol 15, Num 4, pp 313-335, issn 1180-4009, 23 p.Article

A new wind speed forecasting strategy based on the chaotic time series modelling technique and the Apriori algorithmZHENHAI GUO; DEZHONG CHI; JIE WU et al.Energy conversion and management. 2014, Vol 84, pp 140-151, issn 0196-8904, 12 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

Imperialist competitive algorithm combined with refined high-order weighted fuzzy time series (RHWFTS-ICA) for short term load forecastingENAYATIFAR, Rasul; HOSSEIN JAVEDANI SADAEI; ABDUL HANAN ABDULLAH et al.Energy conversion and management. 2013, Vol 76, pp 1104-1116, issn 0196-8904, 13 p.Article

ESTIMABILITY OF DENSITY DEPENDENCE IN MODELS OF TIME SERIES DATAKNAPE, Jonas.Ecology (Durham). 2008, Vol 89, Num 11, pp 2994-3000, issn 0012-9658, 7 p.Article

Time Series of ac Conductivity in Praseodymium Nitrate CrystalKAWASHIMA, Riki; MIURA, Toshiomi; ISODA, Hiroshi et al.Journal of the Physical Society of Japan. 2007, Vol 76, Num 12, issn 0031-9015, 124002.1-124002.4Article

The effects of exchange rate volatility on U.S. forest commodities exportsCHANGYOU SUN; DAOWEI ZHANG.Forest science. 2003, Vol 49, Num 5, pp 807-814, issn 0015-749X, 8 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

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