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Artykuły w czasopismach na temat "Predictive programming"
de Madrid, A. P., S. Dormido, F. Morilla i L. Grau. "Dynamic Programming Predictive Control". IFAC Proceedings Volumes 29, nr 1 (czerwiec 1996): 1721–26. http://dx.doi.org/10.1016/s1474-6670(17)57917-3.
Pełny tekst źródłaKulcsár, Zsuzsanna, János Nagy i Mária Nábrády. "Hemisphericity and predictive motor programming". International Journal of Psychophysiology 11, nr 1 (lipiec 1991): 49. http://dx.doi.org/10.1016/0167-8760(91)90209-g.
Pełny tekst źródłaXie, Haotian, Jianming Du, Dongliang Ke, Yingjie He, Fengxiang Wang, Christoph Hackl, José Rodríguez i Ralph Kennel. "Multistep Model Predictive Control for Electrical Drives—A Fast Quadratic Programming Solution". Symmetry 14, nr 3 (21.03.2022): 626. http://dx.doi.org/10.3390/sym14030626.
Pełny tekst źródłaRao, Christopher V., i James B. Rawlings. "Linear programming and model predictive control". Journal of Process Control 10, nr 2-3 (kwiecień 2000): 283–89. http://dx.doi.org/10.1016/s0959-1524(99)00034-7.
Pełny tekst źródłaRodríguez, Arturo, i Joaquín Trigueros. "Forecasting and forecast-combining of quarterly earnings-per-share via genetic programming". Estudios de Administración 15, nr 2 (4.02.2020): 47. http://dx.doi.org/10.5354/0719-0816.2008.56413.
Pełny tekst źródłaBabu, Mr M. Jeevan. "Mental Health Prediction Using Catboost Algorithm". International Journal for Research in Applied Science and Engineering Technology 12, nr 3 (31.03.2024): 3449–53. http://dx.doi.org/10.22214/ijraset.2024.59219.
Pełny tekst źródłaJianhong, Wang. "Dynamic Programming in Data Driven Model Predictive Control?" WSEAS TRANSACTIONS ON SYSTEMS 20 (21.07.2021): 170–77. http://dx.doi.org/10.37394/23202.2021.20.19.
Pełny tekst źródłaDixon, Kevin R., John M. Dolan i Pradeep K. Khosla. "Predictive Robot Programming: Theoretical and Experimental Analysis". International Journal of Robotics Research 23, nr 9 (wrzesień 2004): 955–73. http://dx.doi.org/10.1177/0278364904044401.
Pełny tekst źródłaDavidson, Curt, i Alan Ewert. "College Student Commitment and Outdoor Orientation Programming". Journal of Experiential Education 43, nr 3 (1.06.2020): 299–316. http://dx.doi.org/10.1177/1053825920923709.
Pełny tekst źródłaOhmori, Shunichi. "A Predictive Prescription Using Minimum Volume k-Nearest Neighbor Enclosing Ellipsoid and Robust Optimization". Mathematics 9, nr 2 (7.01.2021): 119. http://dx.doi.org/10.3390/math9020119.
Pełny tekst źródłaRozprawy doktorskie na temat "Predictive programming"
König, Rikard. "Enhancing genetic programming for predictive modeling". Doctoral thesis, Högskolan i Borås, Institutionen Handels- och IT-högskolan, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:hb:diva-3689.
Pełny tekst źródłaAvhandling för teknologie doktorsexamen i datavetenskap, som kommer att försvaras offentligt tisdagen den 11 mars 2014 kl. 13.15, M404, Högskolan i Borås. Opponent: docent Niklas Lavesson, Blekinge Tekniska Högskola, Karlskrona.
Buerger, Johannes Albert. "Fast model predictive control". Thesis, University of Oxford, 2013. http://ora.ox.ac.uk/objects/uuid:6e296415-f02c-4bc2-b171-3bee80fc081a.
Pełny tekst źródłaFreiwat, Sami, i Lukas Öhlund. "Fuel-Efficient Platooning Using Road Grade Preview Information". Thesis, Uppsala universitet, Avdelningen för systemteknik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-270263.
Pełny tekst źródłaFelipe, Dominguez Luis Felipe Dominguez. "Advances in multiparametric nonlinear programming & explicit model predictive control". Thesis, Imperial College London, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.536023.
Pełny tekst źródłaRivotti, Pedro. "Multi-parametric programming and explicit model predictive control of hybrid systems". Thesis, Imperial College London, 2013. http://hdl.handle.net/10044/1/24432.
Pełny tekst źródłaBennett, Andrew David. "Using genetic programming to learn predictive models from spatio-temporal data". Thesis, University of Leeds, 2010. http://etheses.whiterose.ac.uk/1376/.
Pełny tekst źródłaJonsson, Johan. "Fuel Optimized Predictive Following in Low Speed Conditions". Thesis, Linköping University, Department of Electrical Engineering, 2003. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-1937.
Pełny tekst źródłaThe situation when driving in dense traffic and at low speeds is called Stop and Go. A controller for automatic following of the car in front could under these conditions reduce the driver's workload and keep a safety distance to the preceding vehicle through different choices of gear and engine torque. The aim of this thesis is to develop such a controller, with an additional focus on lowering the fuel consumption. With help of GPS, 3D-maps and sensors information about the slope of the road and the preceding vehicle can be obtained. Using this information the controller is able to predict future possible control actions and an optimization algorithm can then find the best inputs with respect to some criteria. The control method used is Model Predictive Control (MPC) and as the name indicate a model of the control object is required for the prediction. To find the optimal sequence of inputs, the optimization method Dynamic Programming choose the one which lead to the lowest fuel consumption and satisfactory following. Simulations have been made using a reference trajectory which was measured in a real traffic jam. The simulations show that it is possible to follow the preceding vehicle in a good way and at the same time reduce the fuel consumption with approximately 3 %.
Andersson, Emma. "Intuitive Mission Handling with Automatic Route Re-planning using Model Predictive Control". Thesis, Linköpings universitet, Reglerteknik, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-80638.
Pełny tekst źródłaSystemet för uppdragshantering i stridsflygplanet Gripen, och i dess markstödsystem, består bland annat av uppdragsplanering, skapande av uppdragspunkter och möjligheter att validera utförda uppdrag. Systemet är komplext och exempelvis växer antalet uppdragspunkter med omvärldens ökande krav och behov. Detta examensarbete presenterar förslag till förenklingar och förbättringar i uppdragshanteringssystemet, för att göra det mer intuitivt och användarvänligt. Som grund för förslagen har intervjuer med piloter från Saab, TUJAS och FMV gjorts, för att samla in åsikter och idéer från de som använder systemet och har bred kunskap om det. En förbättring är en möjlighet till online automatisk omplanering av uppdragsrutten vid hinder. MPC (modellbaserad prediktionsreglering) har använts för att estimera den dynamiska fiendens flygväg, och beräkna en ny rutt till nästa uppdragspunkt som inte ligger i konflikt med den estimerade vägen för hindret. Detta system har implementerats i Matlab och konceptet demonstreras med olika testscenarion där prestandaparametrar (prediktionshorisont och straff i kostnadsfunktionen) för regulatorn varieras, och stationära och rörliga hinder induceras.
AL_Sheakh, Ameen Nael [Verfasser]. "Programming and Industrial Control, Model-Based Predictive Control of 3-Level Inverters / Nael AL_Sheakh Ameen". Wuppertal : Universitätsbibliothek Wuppertal, 2012. http://d-nb.info/1022901303/34.
Pełny tekst źródłaJonsson, Holm Erik. "Predictive Energy Management of Long-Haul Hybrid Trucks : Using Quadratic Programming and Branch-and-Bound". Thesis, Linköpings universitet, Fordonssystem, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-178224.
Pełny tekst źródłaKsiążki na temat "Predictive programming"
author, Mayor Eric, i Forte Rui Miguel author, red. R: Predictive analysis : master the art of predictive modeling. Birmingham, UK: Packt Publishing, 2017.
Znajdź pełny tekst źródłaNitin, Indurkhya, i Zhang Tong 1971-, red. Fundamentals of predictive text mining. London: Springer-Verlag, 2010.
Znajdź pełny tekst źródłaLearning data mining with Python: Harness the power of Python to analyze data and create insightful predictive models. Birmingham, UK: Packt Publishing, 2015.
Znajdź pełny tekst źródłaC, Georgiadis Michael, Pistikopoulos Efstratios N i Dua Vivek, red. Multi-parametric model-based control: Theory and applications. Weinheim: Wiley-VCH, 2007.
Znajdź pełny tekst źródłaFahringer, Thomas. Automatic performance prediction of parallel programs. Boston: Kluwer Academic Publishers, 1996.
Znajdź pełny tekst źródłaHyslop, William F. Performance prediction of relational database management systems. Toronto: Computer Systems Research Institute, University of Toronto, 1991.
Znajdź pełny tekst źródłaFahringer, Thomas. Automatic Performance Prediction of Parallel Programs. Boston, MA: Springer US, 1996.
Znajdź pełny tekst źródłaR, Horn J., i United States. National Aeronautics and Space Administration. Scientific and Technical Information Division., red. Geometric programming prediction of design trends for OMV protective structures. [Washington, D.C.]: National Aeronautics and Space Administration, Office of Management, Scientific and Technical Information Division, 1990.
Znajdź pełny tekst źródłaRauscher, Harold M. The microcomputer scientific software series 4: Testing prediction accuracy. St. Paul, Minn: U.S. Dept. of Agriculture, Forest Service, North Central Forest Experiment Station, 1986.
Znajdź pełny tekst źródłaBrown, Robert Goodell. Smoothing, forecasting and prediction of discrete time series. Mineola, NY: Dover Publications, 2004.
Znajdź pełny tekst źródłaCzęści książek na temat "Predictive programming"
Grancharova, Alexandra, i Tor Arne Johansen. "Multi-parametric Programming". W Explicit Nonlinear Model Predictive Control, 1–37. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28780-0_1.
Pełny tekst źródłaMathavaraj, S., i Radhakant Padhi. "Model Predictive Static Programming". W Satellite Formation Flying, 111–38. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-9631-5_7.
Pełny tekst źródłaFerreira, Carlos Abreu, João Gama i Vítor Santos Costa. "Predictive Sequence Miner in ILP Learning". W Inductive Logic Programming, 130–44. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31951-8_15.
Pełny tekst źródłaSaerens, Bart, Moritz Diehl i Eric Van den Bulck. "Optimal Control Using Pontryagin’s Maximum Principle and Dynamic Programming". W Automotive Model Predictive Control, 119–38. London: Springer London, 2010. http://dx.doi.org/10.1007/978-1-84996-071-7_8.
Pełny tekst źródłaMarathe, Madhav V. "Towards a Predictive Computational Complexity Theory". W Automata, Languages and Programming, 22–31. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-45465-9_2.
Pełny tekst źródłaKirches, Christian. "Constrained Nonlinear Programming". W Fast Numerical Methods for Mixed-Integer Nonlinear Model-Predictive Control, 61–87. Wiesbaden: Vieweg+Teubner Verlag, 2011. http://dx.doi.org/10.1007/978-3-8348-8202-8_4.
Pełny tekst źródłaZavala, Victor M., i Lorenz T. Biegler. "Nonlinear Programming Strategies for State Estimation and Model Predictive Control". W Nonlinear Model Predictive Control, 419–32. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01094-1_33.
Pełny tekst źródłaŠourek, Gustav, Suresh Manandhar, Filip Železný, Steven Schockaert i Ondřej Kuželka. "Learning Predictive Categories Using Lifted Relational Neural Networks". W Inductive Logic Programming, 108–19. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-63342-8_9.
Pełny tekst źródłaGrüne, Lars. "Dynamic Programming, Optimal Control and Model Predictive Control". W Handbook of Model Predictive Control, 29–52. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-77489-3_2.
Pełny tekst źródłaTamaddoni-Nezhad, Alireza, David Bohan, Alan Raybould i Stephen Muggleton. "Towards Machine Learning of Predictive Models from Ecological Data". W Inductive Logic Programming, 154–67. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-23708-4_11.
Pełny tekst źródłaStreszczenia konferencji na temat "Predictive programming"
Dantas, Danilo Medeiros, Jucelio Soares dos Santos, Kézia de Vasconcelos Oliveira Dantas, Wilkerson L. Andrade, João Brunet i Monilly Ramos Araujo Melo. "Screening Programming’s Reliability to Measure Predictive Programming Skills". W Simpósio Brasileiro de Informática na Educação. Sociedade Brasileira de Computação - SBC, 2023. http://dx.doi.org/10.5753/sbie.2023.235112.
Pełny tekst źródłaMeadows, E. S. "Dynamic programming and model predictive control". W Proceedings of 16th American CONTROL Conference. IEEE, 1997. http://dx.doi.org/10.1109/acc.1997.610861.
Pełny tekst źródłaBeeri, Catriel, i Tova Milo. "Functional and predictive programming in OODB's". W the eleventh ACM SIGACT-SIGMOD-SIGART symposium. New York, New York, USA: ACM Press, 1992. http://dx.doi.org/10.1145/137097.137863.
Pełny tekst źródłaNewsom, David K., Sardar F. Azari, Ahmad Anbar i Tarek El-Ghazawi. "Predictive energy management techniques for PGAS programming". W 2013 ACS International Conference on Computer Systems and Applications (AICCSA). IEEE, 2013. http://dx.doi.org/10.1109/aiccsa.2013.6616462.
Pełny tekst źródłaMorgenstern, Dimitri, Daniel Gorges i Andreas Wirsen. "Obtaining a Stabilizing Prediction Horizon in Quadratic Programming Model Predictive Control". W 2019 IEEE 58th Conference on Decision and Control (CDC). IEEE, 2019. http://dx.doi.org/10.1109/cdc40024.2019.9030254.
Pełny tekst źródłaChisci, L. "Stabilising predictive control: static vs dynamic programming approach". W UKACC International Conference on Control. Control '96. IEE, 1996. http://dx.doi.org/10.1049/cp:19960752.
Pełny tekst źródłaEggimann, Marc-Andre, Oscar D. Crisalle i Roland Longchamp. "A Linear-Programming Predictive Controller with Variable Horizon". W 1992 American Control Conference. IEEE, 1992. http://dx.doi.org/10.23919/acc.1992.4792372.
Pełny tekst źródłaCui, Hairong, Wei Wang i Xiangjie Liu. "Robust model predictive control based on linear programming". W 2011 2nd International Conference on Intelligent Control and Information Processing (ICICIP). IEEE, 2011. http://dx.doi.org/10.1109/icicip.2011.6008405.
Pełny tekst źródłaAmezquita-Brooks, Luis, i Jesus Liceaga-Castro. "A simple non-windup linear programming predictive controller". W Electronics, Robotics and Automotive Mechanics Conference (CERMA 2007). IEEE, 2007. http://dx.doi.org/10.1109/cerma.2007.4367668.
Pełny tekst źródłaCalafiore, G. C., i L. Fagiano. "Robust model predictive control via random convex programming". W 2011 50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC 2011). IEEE, 2011. http://dx.doi.org/10.1109/cdc.2011.6160548.
Pełny tekst źródłaRaporty organizacyjne na temat "Predictive programming"
Fogel, Lawrence J., i David Fogel. Artificial Intelligence through Evolutionary Programming: Prediction and Identification. Fort Belvoir, VA: Defense Technical Information Center, sierpień 1986. http://dx.doi.org/10.21236/ada171544.
Pełny tekst źródłaNeely, Christopher J., i Paul A. Weller. Predicting Exchange Rate Volatility: Genetic Programming vs. GARCH and Risk Metrics™. Federal Reserve Bank of St. Louis, 2001. http://dx.doi.org/10.20955/wp.2001.009.
Pełny tekst źródłaShaw, Alan C. Specifying, Predicting, and Verifying the Timing Properties of Hard- Real-Time Programming Languages and Systems. Fort Belvoir, VA: Defense Technical Information Center, czerwiec 1992. http://dx.doi.org/10.21236/ada257296.
Pełny tekst źródłaBednall, Timothy. A Gentle Introduction to Python. Instats Inc., 2023. http://dx.doi.org/10.61700/ywg7hgz3gf12y469.
Pełny tekst źródłaBednall, Timothy. A Gentle Introduction to Python. Instats Inc., 2023. http://dx.doi.org/10.61700/oma5ikdj8xru1469.
Pełny tekst źródłaBednall, Timothy. A Gentle Introduction to R. Instats Inc., 2022. http://dx.doi.org/10.61700/nkdwj37n3trpc469.
Pełny tekst źródłaBednall, Timothy. A Gentle Introduction to R. Instats Inc., 2022. http://dx.doi.org/10.61700/8851t6mqarw95469.
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