Literatura científica selecionada sobre o tema "Periodic prediction"
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Artigos de revistas sobre o assunto "Periodic prediction"
Niu, Xiaoxu, Junwei Ma, Yankun Wang, Junrong Zhang, Hongjie Chen e Huiming Tang. "A Novel Decomposition-Ensemble Learning Model Based on Ensemble Empirical Mode Decomposition and Recurrent Neural Network for Landslide Displacement Prediction". Applied Sciences 11, n.º 10 (20 de maio de 2021): 4684. http://dx.doi.org/10.3390/app11104684.
Texto completo da fonteYang, Xiaoxue, Yajie Zou, Jinjun Tang, Jian Liang e Muhammad Ijaz. "Evaluation of Short-Term Freeway Speed Prediction Based on Periodic Analysis Using Statistical Models and Machine Learning Models". Journal of Advanced Transportation 2020 (20 de janeiro de 2020): 1–16. http://dx.doi.org/10.1155/2020/9628957.
Texto completo da fonteRen, Liang, Feng Yang, Yuanhe Gao e Yongcong He. "Predicting Spacecraft Telemetry Data by Using Grey–Markov Model with Sliding Window and Particle Swarm Optimization". Journal of Mathematics 2023 (3 de fevereiro de 2023): 1–14. http://dx.doi.org/10.1155/2023/9693047.
Texto completo da fonteSugimoto, Masashi, Naoya Iwamoto, Robert W. Johnston, Keizo Kanazawa, Yukinori Misaki e Kentarou Kurashige. "A Study of Predicting Ability in State-Action Pair Prediction". International Journal of Artificial Life Research 7, n.º 1 (janeiro de 2017): 52–66. http://dx.doi.org/10.4018/ijalr.2017010104.
Texto completo da fonteShen, Yueqian, Xiaoxia Ma, Yajing Sun e Sheng Du. "Prediction of university fund revenue and expenditure based on fuzzy time series with a periodic factor". PLOS ONE 18, n.º 5 (25 de maio de 2023): e0286325. http://dx.doi.org/10.1371/journal.pone.0286325.
Texto completo da fonteCheng, Weiwei, Guigen Nie e Jian Zhu. "Characterizing Periodic Variations of Atomic Frequency Standards via Their Frequency Stability Estimates". Sensors 23, n.º 11 (5 de junho de 2023): 5356. http://dx.doi.org/10.3390/s23115356.
Texto completo da fonteScerri, Eric R., e John Worrall. "Prediction and the periodic table". Studies in History and Philosophy of Science Part A 32, n.º 3 (setembro de 2001): 407–52. http://dx.doi.org/10.1016/s0039-3681(01)00023-1.
Texto completo da fontePawelzik, K., e H. G. Schuster. "Unstable periodic orbits and prediction". Physical Review A 43, n.º 4 (1 de fevereiro de 1991): 1808–12. http://dx.doi.org/10.1103/physreva.43.1808.
Texto completo da fonteMiao, Xu, Bing Wu, Yajie Zou e Lingtao Wu. "Examining the Impact of Different Periodic Functions on Short-Term Freeway Travel Time Prediction Approaches". Journal of Advanced Transportation 2020 (1 de agosto de 2020): 1–15. http://dx.doi.org/10.1155/2020/3463287.
Texto completo da fonteZhao, Lin, Nan Li, Hui Li, Renlong Wang e Menghao Li. "BDS Satellite Clock Prediction Considering Periodic Variations". Remote Sensing 13, n.º 20 (11 de outubro de 2021): 4058. http://dx.doi.org/10.3390/rs13204058.
Texto completo da fonteTeses / dissertações sobre o assunto "Periodic prediction"
Chen, Jin-Jae. "Prediction of periodic forced response of frictionally constrained turbine blades /". The Ohio State University, 1999. http://rave.ohiolink.edu/etdc/view?acc_num=osu1488187763847997.
Texto completo da fonteSadat, Hosseini Seyed Hamid Stern Frederick Carrica Pablo M. "CFD prediction of ship capsize parametric rolling, broaching, surf-riding, and periodic motions /". [Iowa City, Iowa] : University of Iowa, 2009. http://ir.uiowa.edu/etd/427.
Texto completo da fonteDate, James Charles. "Performance prediction of high lift rudders operating under steady and periodic flow conditions". Thesis, University of Southampton, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.390722.
Texto completo da fonteSadat, Hosseini Seyed Hamid. "CFD prediction of ship capsize: parametric rolling, broaching, surf-riding, and periodic motions". Diss., University of Iowa, 2009. https://ir.uiowa.edu/etd/427.
Texto completo da fontePerreira, Das Chagas Thiago. "Stabilization of periodic orbits in discrete and continuous-time systems". Phd thesis, Université Paris Sud - Paris XI, 2013. http://tel.archives-ouvertes.fr/tel-00852424.
Texto completo da fonteLindsey, Justin. "Fatigue Behavior in the Presence of Periodic Overloads Including the Effects of Mean Stress and Inclusions". University of Toledo / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1319554971.
Texto completo da fonteBorda, Jorge Victor Quiñones. "Log periodic analysis of critical crashes in the portuguese stock market". Master's thesis, Instituto Superior de Economia e Gestão, 2015. http://hdl.handle.net/10400.5/11082.
Texto completo da fonteO estudo de fenómenos críticos que se originaram nas ciências naturais e encontraram muitos campos de aplicação foi estendido nos últimos anos aos campos da economia de finanças, fornecendo aos investigadores novas abordagens para problemas conhecidos, nomeadamente aos que estão relacionados com a gestão de risco, a previsão, o estudo de bolhas financeiras e crashes, e muitos outros tipos de problemas que envolvem sistemas com criticalidade auto-organizada. A teoria de singularidades de tempo oscilatório auto-similares é apresentada, uma metodologia prática é exposta, juntamente com alguns resultados de análises semelhantes de diferentes mercados em todo o mundo, como uma maneira de obter de alguns exemplos da forma como a função "linear" log-periódica de potências funciona. Apresento alguns contextos onde o tempo de crise é apresentado aos mercados internacionais - como uma maneira de demonstração de antecedentes -, assim como apresento também três aplicações práticas do mercado de acções português (1997, 2008 e 2015). A sensibilidade dos resultados e do significado das oscilações log-periódicas são avaliadas. Concluo com algumas recomendações e futuras propostas de investigação.
The study of critical phenomena that originated in the natural sciences and found many fields of applications has been extended in the last years to the financial economics? field, giving researchers new approaches to known problems, namely those related to risk management, forecasting, the study of bubbles and crashes, and many kind of problems involving complex systems with self-organized criticality. The theory of self-similar oscillatory time singularities is presented. A practical methodology is exposed along with some results from similar analysis from different markets around the world, as a way to get some examples of the way the ´Linear´ Log-Periodic Power Law formula works. Some context presenting the international markets at the time of crisis is given as a way of having some background, and three practical applications for the Portuguese stock market are made (1997, 2008 and 2015). The sensitivity of the results and the significance from the log-periodic oscillations is assessed. It concludes with some recommendations and future proposed research.
Devarasetty, Ravi Kiran. "Heuristic Algorithms for Adaptive Resource Management of Periodic Tasks in Soft Real-Time Distributed Systems". Thesis, Virginia Tech, 2001. http://hdl.handle.net/10919/31219.
Texto completo da fonteMaster of Science
Kamisetty, Jananni Narasimha Shiva Sai Sri Harsha Vardhan. "Forecasting Trajectory Data : A study by Experimentation". Thesis, Blekinge Tekniska Högskola, Institutionen för kommunikationssystem, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-13976.
Texto completo da fonteLevin, Ori. "Numerical studies of transtion in wall-bounded flows". Doctoral thesis, KTH, Mechanics, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-546.
Texto completo da fonteDisturbances introduced in wall-bounded flows can grow and lead to transition from laminar to turbulent flow. In order to reduce losses or enhance mixing in energy systems, a fundamental understanding of the flow stability and transition mechanism is important. In the present thesis, the stability, transition mechanism and early turbulent evolution of wall-bounded flows are studied. The stability is investigated by means of linear stability equations and the transition mechanism and turbulence are studied using direct numerical simulations. Three base flows are considered, the Falkner-Skan boundary layer, boundary layers subjected to wall suction and the Blasius wall jet. The stability with respect to the exponential growth of waves and the algebraic growth of optimal streaks is studied for the Falkner-Skan boundary layer. For the algebraic growth, the optimal initial location, where the optimal disturbance is introduced in the boundary layer, is found to move downstream with decreased pressure gradient. A unified transition prediction method incorporating the influences of pressure gradient and free-stream turbulence is suggested. The algebraic growth of streaks in boundary layers subjected to wall suction is calculated. It is found that the spatial analysis gives larger optimal growth than temporal theory. Furthermore, it is found that the optimal growth is larger if the suction begins a distance downstream of the leading edge. Thresholds for transition of periodic and localized disturbances as well as the spreading of turbulent spots in the asymptotic suction boundary layer are investigated for Reynolds number Re=500, 800 and 1200 based on the displacement thickness and the free-stream velocity. It is found that the threshold amplitude scales like Re^-1.05 for transition initiated by streamwise vortices and random noise, like Re^-1.3 for oblique transition and like Re^-1.5 for the localized disturbance. The turbulent spot is found to take a bullet-shaped form that becomes more distinct and increases its spreading rate for higher Reynolds number. The Blasius wall jet is matched to the measured flow in an experimental wall-jet facility. Both the linear and nonlinear regime of introduced waves and streaks are investigated and compared to measurements. It is demonstrated that the streaks play an important role in the breakdown process where they suppress pairing and enhance breakdown to turbulence. Furthermore, statistics from the early turbulent regime are analyzed and reveal a reasonable self-similar behavior, which is most pronounced with inner scaling in the near-wall region.
Livros sobre o assunto "Periodic prediction"
Dolph, K. Leroy. Prediction of periodic basal area increment for young-growth mixed conifers in the Sierra Nevada. Berkeley, Calif: U.S. Dept. of Agriculture, Forest Service, Pacific Southwest Forest and Range Experiment Station, 1988.
Encontre o texto completo da fonteEl paisaje del valle del Asón (Cantabria) a finales del Tardiglaciar: Un modelo predictivo de vegetación arbórea mediante SIG = Landscape in the Ason River Valley (Spain) during the Final Late Glacial : a predictive vegetation model using GIS. Oxford: Archaeopress, 2015.
Encontre o texto completo da fonteBEREZhNOY, Aleksandr, Svetlana DUNAEVSKAYa e Yuriy VINNIK. Prognosis of postoperative course of urolithiasis. ru: INFRA-M Academic Publishing LLC., 2022. http://dx.doi.org/10.12737/1863093.
Texto completo da fonteTerehin, Valeriy, e Viktor Chernyshov. Efficiency and effectiveness of the penitentiary system: assessment and planning. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1079434.
Texto completo da fonteWang, Bin. Intraseasonal Modulation of the Indian Summer Monsoon. Oxford University Press, 2018. http://dx.doi.org/10.1093/acrefore/9780190228620.013.616.
Texto completo da fonteKalitzin, Stiliyan, e Fernando Lopes da Silva. EEG-Based Anticipation and Control of Seizures. Editado por Donald L. Schomer e Fernando H. Lopes da Silva. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190228484.003.0023.
Texto completo da fonteNational Aeronautics and Space Administration (NASA) Staff. Predictions of Control Inputs, Periodic Responses and Damping Levels of an Isolated Experimental Rotor in Trimmed Flight. Independently Published, 2018.
Encontre o texto completo da fontePeriodic Tables Unifying Living Organisms at the Molecular Level: The Predictive Power of the Law of Periodicity. World Scientific Publishing Co Pte Ltd, 2018.
Encontre o texto completo da fonteBarbaree, Howard E., e Robert A. Prentky. Risk assessment of sex offenders. Editado por Teela Sanders. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780190213633.013.21.
Texto completo da fonteDawid, A. Philip, Julia Mortera e Paola Vicard. Volatility in prediction markets: A measure of information flow in political campaigns. Editado por Anthony O'Hagan e Mike West. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780198703174.013.21.
Texto completo da fonteCapítulos de livros sobre o assunto "Periodic prediction"
McCormick, Andrew C., e Asoke K. Nandi. "Condition Monitoring Using Periodic Time-Varying AR Models". In Signal Analysis and Prediction, 197–204. Boston, MA: Birkhäuser Boston, 1998. http://dx.doi.org/10.1007/978-1-4612-1768-8_14.
Texto completo da fonteBračič, Maja, e Aneta Stefanovska. "Lyapunov Exponents of Simulated and Measured Quasi-Periodic Flows". In Signal Analysis and Prediction, 479–88. Boston, MA: Birkhäuser Boston, 1998. http://dx.doi.org/10.1007/978-1-4612-1768-8_34.
Texto completo da fonteBurgess, Keith, Katie Burgess, Prajan Subedi, Phil Ainslie, Zbigniew Topor e William Whitelaw. "Prediction of Periodic Breathing at Altitude". In Integration in Respiratory Control, 442–46. New York, NY: Springer New York, 2008. http://dx.doi.org/10.1007/978-0-387-73693-8_77.
Texto completo da fonteMichalak, Marcin. "Time Series Prediction with Periodic Kernels". In Computer Recognition Systems 4, 137–46. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-20320-6_15.
Texto completo da fonteBlatov, Vladislav A., e Davide M. Proserpio. "Periodic-Graph Approaches in Crystal Structure Prediction". In Modern Methods of Crystal Structure Prediction, 1–28. Weinheim, Germany: Wiley-VCH Verlag GmbH & Co. KGaA, 2010. http://dx.doi.org/10.1002/9783527632831.ch1.
Texto completo da fonteCao, Yongzhong, He Zhou e Bin Li. "Rice Growth Prediction Based on Periodic Growth". In Studies in Computational Intelligence, 159–75. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-56178-9_13.
Texto completo da fonteZhao, Jijun, Hao Liu, Zhihua Li e Wei Li. "Periodic Data Prediction Algorithm in Wireless Sensor Networks". In Communications in Computer and Information Science, 695–701. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-36252-1_65.
Texto completo da fonteBittanti, Sergio. "The periodic prediction problem for cyclostationary processes — an introduction". In Modelling, Robustness and Sensitivity Reduction in Control Systems, 239–49. Berlin, Heidelberg: Springer Berlin Heidelberg, 1987. http://dx.doi.org/10.1007/978-3-642-87516-8_15.
Texto completo da fonteKarimi, M., P. Croaker e N. Kessissoglou. "Trailing-Edge Noise Prediction Using a Periodic BEM Technique". In Fluid-Structure-Sound Interactions and Control, 39–44. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-48868-3_6.
Texto completo da fonteBouzayane, Sarra, e Ines Saad. "Intelligent Multicriteria Decision Support System for a Periodic Prediction". In Decision Support Systems IX: Main Developments and Future Trends, 97–110. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-18819-1_8.
Texto completo da fonteTrabalhos de conferências sobre o assunto "Periodic prediction"
Gillan, Mark, R. Mitchell, S. Raghunathan, Jonathan Cole, Mark Gillan, R. Mitchell, S. Raghunathan e Jonathan Cole. "Prediction and control of periodic flows". In 35th Aerospace Sciences Meeting and Exhibit. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1997. http://dx.doi.org/10.2514/6.1997-832.
Texto completo da fonteSun Bo, Zhang Bingyi, Wang Erzhi e Sun Liang. "Periodic statistical prediction adaptive memory incremental control". In 2008 IEEE International Conference on Industrial Technology - (ICIT). IEEE, 2008. http://dx.doi.org/10.1109/icit.2008.4608382.
Texto completo da fonteHu, Xiaobo, e Gang Quan. "Fast performance prediction for periodic task systems". In the eighth international workshop. New York, New York, USA: ACM Press, 2000. http://dx.doi.org/10.1145/334012.334026.
Texto completo da fonteNakhjiri, Mehdi, e Peter F. Pelz. "Turbomachines Under Periodic Admission: Axiomatic Performance Prediction". In ASME Turbo Expo 2012: Turbine Technical Conference and Exposition. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/gt2012-68398.
Texto completo da fonteZonoozi, Ali, Jung-jae Kim, Xiao-Li Li e Gao Cong. "Periodic-CRN: A Convolutional Recurrent Model for Crowd Density Prediction with Recurring Periodic Patterns". In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/519.
Texto completo da fonteWu, Jiaqing, Yinzhi Wu e Cheng Chen. "Periodic Attention Networks for Air Quality Index Prediction". In ICMLCA 2023: 2023 4th International Conference on Machine Learning and Computer Application. New York, NY, USA: ACM, 2023. http://dx.doi.org/10.1145/3650215.3650271.
Texto completo da fonteLuo, Albert C. J. "Stability and Bifurcation for the Equispaced, Periodic Motion of a Horizontal Impact Damper". In ASME 2001 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2001. http://dx.doi.org/10.1115/detc2001/vib-21505.
Texto completo da fonteGuo, Xiaogang, Guangyue Li, Zhixing Chen, Huazu Zhang, Yulin Ding, Jinghan Wang, Zilong Zhao e Luliang Tang. "Large-Scale Human Mobility Prediction Based on Periodic Attenuation and Local Feature Match". In HuMob-Challenge '23: 1st International Workshop on the Human Mobility Prediction Challenge. New York, NY, USA: ACM, 2023. http://dx.doi.org/10.1145/3615894.3628505.
Texto completo da fonteXing, Siyuan, e Albert C. J. Luo. "Periodic Motions in a First-Order, Time-Delayed, Nonlinear System". In ASME 2018 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/imece2018-86824.
Texto completo da fonteOzcan Kini, Seldag, e Ayse Tosun. "[Research Paper] Periodic Developer Metrics in Software Defect Prediction". In 2018 IEEE 18th International Working Conference on Source Code Analysis and Manipulation (SCAM). IEEE, 2018. http://dx.doi.org/10.1109/scam.2018.00016.
Texto completo da fonteRelatórios de organizações sobre o assunto "Periodic prediction"
Dolph, Leroy K. Prediction of periodic basal area increment for young-growth mixed conifers in sierra Nevada. Berkeley, CA: U.S. Department of Agriculture, Forest Service, Pacific Southwest Forest and Range Experiment Station, 1988. http://dx.doi.org/10.2737/psw-rp-190.
Texto completo da fonteLeis. L51865 Hydrotest Parameters to Help Control High-pH SCC on Gas Transmission Pipelines. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), setembro de 1999. http://dx.doi.org/10.55274/r0010208.
Texto completo da fonteGómez Loscos, Ana, Miguel Ángel González Simón e Matías José Pacce. Short-term real-time forecasting model for spanish GDP (Spain-STING): new specification and reassessment of its predictive power. Madrid: Banco de España, março de 2024. http://dx.doi.org/10.53479/36137.
Texto completo da fonteСоловйов, В. М., e В. В. Соловйова. Моделювання мультиплексних мереж. Видавець Ткачук О.В., 2016. http://dx.doi.org/10.31812/0564/1253.
Texto completo da fonteDuffie, Darrell, e Ke Wang. Multi-Period Corporate Failure Prediction with Stochastic Covariates. Cambridge, MA: National Bureau of Economic Research, setembro de 2004. http://dx.doi.org/10.3386/w10743.
Texto completo da fonteDuffie, Darrell, Leandro Siata e Ke Wang. Multi-Period Corporate Default Prediction With Stochastic Covariates. Cambridge, MA: National Bureau of Economic Research, janeiro de 2006. http://dx.doi.org/10.3386/w11962.
Texto completo da fonteDandekar, B. S., e J. Buchau. Improving foF2 Prediction for the Sunrise Transition Period. Fort Belvoir, VA: Defense Technical Information Center, janeiro de 1986. http://dx.doi.org/10.21236/ada170457.
Texto completo da fonteSi, Hongjun, Saburoh Midorikawa e Tadahiro Kishida. Development of NGA-Sub Ground-Motion Model of 5%-Damped Pseudo-Spectral Acceleration Based on Database for Subduction Earthquakes in Japan. Pacific Earthquake Engineering Research Center, University of California, Berkeley, CA, dezembro de 2020. http://dx.doi.org/10.55461/lien3652.
Texto completo da fontePompeu, Gustavo, e José Luiz Rossi. Real/Dollar Exchange Rate Prediction Combining Machine Learning and Fundamental Models. Inter-American Development Bank, setembro de 2022. http://dx.doi.org/10.18235/0004491.
Texto completo da fonteGunay, Selim, Fan Hu, Khalid Mosalam, Arpit Nema, Jose Restrepo, Adam Zsarnoczay e Jack Baker. Blind Prediction of Shaking Table Tests of a New Bridge Bent Design. Pacific Earthquake Engineering Research Center, University of California, Berkeley, CA, novembro de 2020. http://dx.doi.org/10.55461/svks9397.
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