Letteratura scientifica selezionata sul tema "Periodic prediction"
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Articoli di riviste sul tema "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. 10 (20 maggio 2021): 4684. http://dx.doi.org/10.3390/app11104684.
Yang, 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 gennaio 2020): 1–16. http://dx.doi.org/10.1155/2020/9628957.
Ren, 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 febbraio 2023): 1–14. http://dx.doi.org/10.1155/2023/9693047.
Sugimoto, 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. 1 (gennaio 2017): 52–66. http://dx.doi.org/10.4018/ijalr.2017010104.
Shen, 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. 5 (25 maggio 2023): e0286325. http://dx.doi.org/10.1371/journal.pone.0286325.
Cheng, Weiwei, Guigen Nie e Jian Zhu. "Characterizing Periodic Variations of Atomic Frequency Standards via Their Frequency Stability Estimates". Sensors 23, n. 11 (5 giugno 2023): 5356. http://dx.doi.org/10.3390/s23115356.
Scerri, Eric R., e John Worrall. "Prediction and the periodic table". Studies in History and Philosophy of Science Part A 32, n. 3 (settembre 2001): 407–52. http://dx.doi.org/10.1016/s0039-3681(01)00023-1.
Pawelzik, K., e H. G. Schuster. "Unstable periodic orbits and prediction". Physical Review A 43, n. 4 (1 febbraio 1991): 1808–12. http://dx.doi.org/10.1103/physreva.43.1808.
Miao, 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 agosto 2020): 1–15. http://dx.doi.org/10.1155/2020/3463287.
Zhao, Lin, Nan Li, Hui Li, Renlong Wang e Menghao Li. "BDS Satellite Clock Prediction Considering Periodic Variations". Remote Sensing 13, n. 20 (11 ottobre 2021): 4058. http://dx.doi.org/10.3390/rs13204058.
Tesi sul tema "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.
Sadat, 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.
Date, 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.
Sadat, 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.
Perreira, 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.
Lindsey, 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.
Borda, 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.
O 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.
Master 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.
Levin, 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.
Disturbances 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.
Libri sul tema "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.
Moreno, Alejandro García. El 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.
BEREZhNOY, 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.
Terehin, 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.
Wang, Bin. Intraseasonal Modulation of the Indian Summer Monsoon. Oxford University Press, 2018. http://dx.doi.org/10.1093/acrefore/9780190228620.013.616.
Kalitzin, Stiliyan, e Fernando Lopes da Silva. EEG-Based Anticipation and Control of Seizures. A cura di Donald L. Schomer e Fernando H. Lopes da Silva. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190228484.003.0023.
National 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.
Lima-de-Faria, A. Periodic Tables Unifying Living Organisms at the Molecular Level: The Predictive Power of the Law of Periodicity. World Scientific Publishing Co Pte Ltd, 2018.
Barbaree, Howard E., e Robert A. Prentky. Risk assessment of sex offenders. A cura di Teela Sanders. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780190213633.013.21.
Dawid, A. Philip, Julia Mortera e Paola Vicard. Volatility in prediction markets: A measure of information flow in political campaigns. A cura di Anthony O'Hagan e Mike West. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780198703174.013.21.
Capitoli di libri sul tema "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.
Bračič, 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.
Burgess, 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.
Michalak, 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.
Blatov, 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.
Cao, 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.
Zhao, 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.
Bittanti, 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.
Karimi, 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.
Bouzayane, 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.
Atti di convegni sul tema "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.
Sun 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.
Hu, 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.
Nakhjiri, 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.
Zonoozi, 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.
Wu, 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.
Luo, 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.
Guo, 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.
Xing, 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.
Ozcan 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.
Rapporti di organizzazioni sul tema "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.
Leis. L51865 Hydrotest Parameters to Help Control High-pH SCC on Gas Transmission Pipelines. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), settembre 1999. http://dx.doi.org/10.55274/r0010208.
Gómez 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, marzo 2024. http://dx.doi.org/10.53479/36137.
Соловйов, В. М., e В. В. Соловйова. Моделювання мультиплексних мереж. Видавець Ткачук О.В., 2016. http://dx.doi.org/10.31812/0564/1253.
Duffie, Darrell, e Ke Wang. Multi-Period Corporate Failure Prediction with Stochastic Covariates. Cambridge, MA: National Bureau of Economic Research, settembre 2004. http://dx.doi.org/10.3386/w10743.
Duffie, Darrell, Leandro Siata e Ke Wang. Multi-Period Corporate Default Prediction With Stochastic Covariates. Cambridge, MA: National Bureau of Economic Research, gennaio 2006. http://dx.doi.org/10.3386/w11962.
Dandekar, B. S., e J. Buchau. Improving foF2 Prediction for the Sunrise Transition Period. Fort Belvoir, VA: Defense Technical Information Center, gennaio 1986. http://dx.doi.org/10.21236/ada170457.
Si, 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, dicembre 2020. http://dx.doi.org/10.55461/lien3652.
Pompeu, Gustavo, e José Luiz Rossi. Real/Dollar Exchange Rate Prediction Combining Machine Learning and Fundamental Models. Inter-American Development Bank, settembre 2022. http://dx.doi.org/10.18235/0004491.
Gunay, 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, novembre 2020. http://dx.doi.org/10.55461/svks9397.