Relevant bibliographies by topics / Predictive schemes

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Predictive schemes'

Author: Grafiati
Published: 3 June 2025
Last updated: 1 August 2025

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Journal articles on the topic "Predictive schemes"

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Peng, Jingyao, and Ming Yao. "Overview of Predictive Control Technology for Permanent Magnet Synchronous Motor Systems." Applied Sciences 13, no. 10 (2023): 6255. http://dx.doi.org/10.3390/app13106255.

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Permanent magnet synchronous motors (PMSMs) are commonly used in the automation industry. With the speedy development of digital system processors, predictive control as a modern control scheme has been applied to improve the dynamic performance and work efficiency of PMSMs. This paper provides an overview of the research status of PMSM-based predictive control strategies. The deficiencies of the three most popular predictive schemes, deadbeat predictive control, finite-control-set model predictive control, and continuous-control-set model predictive control, and existing improvement strategie
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Haj Ahmad, Hanan. "Best Prediction Method for Progressive Type-II Censored Samples under New Pareto Model with Applications." Journal of Mathematics 2021 (July 15, 2021): 1–11. http://dx.doi.org/10.1155/2021/1355990.

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This paper describes two prediction methods for predicting the non-observed (censored) units under progressive Type-II censored samples. The lifetimes under consideration are following a new two-parameter Pareto distribution. Furthermore, point and interval estimation of the unknown parameters of the new Pareto model is obtained. Maximum likelihood and Bayesian estimation methods are considered for that purpose. Since Bayes estimators cannot be expressed explicitly, Gibbs and the Markov Chain Monte Carlo techniques are utilized for Bayesian calculation. We use the posterior predictive density
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Emam, M., and M. Gerdts. "Sensitivity updates for linear-quadratic optimization problems in multi-step model predictive control." Journal of Physics: Conference Series 2514, no. 1 (2023): 012008. http://dx.doi.org/10.1088/1742-6596/2514/1/012008.

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Abstract The paper discusses how parametric sensitivity analysis can be used in certain model predictive control (MPC) schemes. The sensitivity analysis will be performed with regard to the initial state measurement and update schemes will be derived that speed-up the computations. Throughout we restrict the discussion to linear-quadratic optimal control problems in discrete time, which frequently arise in tracking tasks with MPC. The derived tools from sensitivity analysis can be embedded into MPC schemes with a prediction step and multi-step MPC schemes with re-optimization and prediction st
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Hu, Yu-Chen. "Predictive Grayscale Image Coding Scheme Using VQ and BTC." Fundamenta Informaticae 78, no. 2 (2007): 239–55. https://doi.org/10.3233/fun-2007-78203.

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A predictive image compression scheme that combines the advantages of vector quantization and moment preserving block truncation coding is introduced in this paper. To exploit the similarities among neighboring image blocks, the block prediction technique is employed in this scheme. If a similar compressed image block can be found in the neighborhood of current processing block, it is taken to encode this block. Otherwise, this image block is encoded either by vector quantization or moment preserving block truncation coding. A bit-rate reduced version of the proposed scheme is also introduced.
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Wu, Yuzhan, Chenlong Li, Changshun Yuan, Meng Li, and Hao Li. "Predictive Control for Small Unmanned Ground Vehicles via a Multi-Dimensional Taylor Network." Applied Sciences 12, no. 2 (2022): 682. http://dx.doi.org/10.3390/app12020682.

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Tracking control of Small Unmanned Ground Vehicles (SUGVs) is easily affected by the nonlinearity and time-varying characteristics. An improved predictive control scheme based on the multi-dimensional Taylor network (MTN) is proposed for tracking control of SUGVs. First, a MTN model is used as a predictive model to construct a SUGV model and back propagation (BP) is taken as its learning algorithm. Second, the predictive control law is designed and the traditional objective function is improved to obtain a predictive objective function with a differential term. The optimal control quantity is
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Alhasheem, Mohammed, Ahmed Abdelhakim, Frede Blaabjerg, Paolo Mattavelli, and Pooya Davari. "Model Predictive Control of Grid Forming Converters with Enhanced Power Quality." Applied Sciences 10, no. 18 (2020): 6390. http://dx.doi.org/10.3390/app10186390.

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This paper proposes an enhanced finite control set model predictive control (FCS-MPC) strategy for voltage source converter (VSC) with a LC output filter. The proposed control scheme is based on tracking the voltage reference trajectory by using only a single-step prediction within the controller horizon. Besides, the suitability of different frequency control schemes with the proposed scheme to prevent from inherent variable switching behaviour of conventional FCS-MPC is investigated. Based on that, the proposed method targets two major factors influencing power quality in grid forming applic
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Babu, K. S., and R. N. Mohapatra. "Predictive schemes for bimaximal neutrino mixings." Physics Letters B 532, no. 1-2 (2002): 77–86. http://dx.doi.org/10.1016/s0370-2693(02)01434-x.

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Yuan, Jie, Dingdou Wen, and Yang Zhang. "Model Predictive Current Control Strategy with Reduced Computation Burden." Mathematical Problems in Engineering 2021 (February 4, 2021): 1–10. http://dx.doi.org/10.1155/2021/6677543.

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In this paper, three model predictive current control (MPCC) schemes for permanent magnet synchronous motors (PMSM) are studied. The first control scheme is the traditional optimal duty cycle model predictive current control (ODC-MPCC). In this scheme, according to the principle of minimizing the cost function, the optimal voltage vector is selected from the six basic voltage vectors which are optimized simultaneously with the duty, and then, the optimal voltage vector and its duty are applied to the inverter. In order to reduce the computational burden of ODC-MPCC, a second control scheme is
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Rabie, Abdalla, Abd EL-Baset A. Ahmad, Mohamad A. Fawzy, and Tahani A. Aloafi. "Bayesian Prediction Intervals Based on Type-I Hybrid Censored Data from the Lomax Distribution under Step-Stress Model." Journal of Mathematics 2022 (December 23, 2022): 1–10. http://dx.doi.org/10.1155/2022/2801582.

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The Bayesian prediction of future failures from Lomax distribution is the subject of this research. The observed data is censored using a Type-I hybrid censoring scheme under a step-stress partially accelerated life test. There are two types of sampling schemes considered: one-sample and two-sample. We create predictive intervals for failure observations in the future. Bayesian prediction intervals are constructed using MCMC algorithms. After all, two numerical examples, simulation study and a real-life example are provided for both one-sample and two-sample methods for the purpose of illustra
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Singh, Amit Kumar, Barjeev Tyagi, and Vishal Kumar. "Classical and Neural Network–Based Approach of Model Predictive Control for Binary Continuous Distillation Column." Chemical Product and Process Modeling 9, no. 1 (2014): 71–87. http://dx.doi.org/10.1515/cppm-2013-0013.

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Abstract The objective of present research work is to develop a neural network–based model predictive control scheme (NN-MPC) for distillation column. To fulfill this objective, an existing laboratory setup of continuous binary-type distillation column (BDC) is used. An equation-based model that uses the fundamental physical and chemical laws along with valid normal assumptions is validated for this experimental setup. Model predictive control (MPC) is one of the main process control techniques explored in the recent past for various chemical engineering applications; therefore, the convention
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Dissertations / Theses on the topic "Predictive schemes"

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Karimi, Pour Fatemeh. "Health-aware predictive control schemes based on industrial processes." Doctoral thesis, TDX (Tesis Doctorals en Xarxa), 2020. http://hdl.handle.net/10803/673045.

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The research is motivated by real applications, such as pasteurization plant, water networks and autonomous system, which each of them require a specific control system to provide proper management able to take into account their particular features and operating limits in presence of uncertainties related to their operation and failures from component breakdowns. According to that most of the real systems have nonlinear behaviors, it can be approximated them by polytopic linear uncertain models such as Linear Parameter Varying (LPV) and Takagi-Sugeno (TS) models. Therefore, a new economic Mod
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Stieler, Marleen [Verfasser], and Lars [Akademischer Betreuer] Grüne. "Performance Estimates for Scalar and Multiobjective Model Predictive Control Schemes / Marleen Stieler ; Betreuer: Lars Grüne." Bayreuth : Universität Bayreuth, 2018. http://d-nb.info/1163319147/34.

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Ananduta, Wayan Wicak. "Non-centralized optimization-based control schemes for large-scale energy systems." Doctoral thesis, TDX (Tesis Doctorals en Xarxa), 2019. http://hdl.handle.net/10803/669263.

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Non-centralized control schemes for large-scale systems, including energy networks, are more flexible, scalable, and reliable than the centralized counterpart. These benefrts are obtained by having a set of local control!ers, each of which is responsible for a partition of the system, instead of one central entity that controls the whole system. Furthermore,in sorne cases, employing a non­ centralized control structure might be necessary due to the intractability problem of the centralized method.Thus, this thesis is devoted to the study of non-centralized optimization-based control approaches
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Wirsching, Leonard [Verfasser], and Hans Georg [Akademischer Betreuer] Bock. "Multi-Level Iteration Schemes with Adaptive Level Choice for Nonlinear Model Predictive Control / Leonard Wirsching ; Betreuer: Hans Georg Bock." Heidelberg : Universitätsbibliothek Heidelberg, 2018. http://d-nb.info/1177251639/34.

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Murali, madhavan rathai Karthik. "Synthesis and real-time implementation of parameterized NMPC schemes for automotive semi-active suspension systems." Thesis, Université Grenoble Alpes, 2020. http://www.theses.fr/2020GRALT052.

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Cette thèse traite de la synthèse et de la mise en œuvre en temps réel (RT) de schémas de contrôle prédictif non linéaire paramétré (pNMPC) pour les systèmes de suspension semi-active des automobiles. Le schéma pNMPC est basé sur une technique d'optimisation par simulation en boîte noire. Le point essentiel de la méthode est de paramétrer finement le profil d'entrée et de simuler le système pour chaque entrée paramétrée et d'obtenir la valeur approximative de l'objectif et de la violation des contraintes pour le problème pNMPC. Avec les résultats obtenus de la simulation, l'entrée admissible (
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Wolf, Ethan. "Statistical prediction schemes for the coiled-coil motif." Thesis, Massachusetts Institute of Technology, 1996. http://hdl.handle.net/1721.1/10678.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mathematics, 1996.<br>Includes bibliographical references (leaves 86-93).<br>This thesis proposes a new multi-dimensional scoring approach for identifying and distinguishing trimeric and dimeric coiled coils. Practical issues in the implementation of the two-stranded coiled coil prediction algorithm PairCoil suggested by Berger are discussed. This algorithm is naturally extended to the domain of three-stranded coiled coils in the implementation of the MultiCoil program. The computations are probabilistically justified and based u
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Ouyang, Hua. "Networked predictive control systems : control scheme and robust stability." Thesis, University of South Wales, 2007. https://pure.southwales.ac.uk/en/studentthesis/networked-predictive-control-systems(9c6178d7-e6a4-420b-b35f-2d62d35ff5b0).html.

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Networked predictive control is a new research method for Networked Control Systems (NCS), which is able to handle network-induced problems such as time-delay, data dropouts, packets disorders, etc. while stabilizing the closed-loop system. This work is an extension and complement of networked predictive control methodology. There is always present model uncertainties or physical nonlinearity in the process of NCS. Therefore, it makes the study of the robust control of NCS and that of networked nonlinear control system (NNCS) considerably important. This work studied the following three proble
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Yu, Lei. "Adaptive predictive handoff scheme with channel borrowing in cellular network." ScholarWorks@UNO, 2003. http://louisdl.louislibraries.org/u?/NOD,55.

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Thesis (M.S.)--University of New Orleans, 2003.<br>Title from electronic submission form. "A thesis ... in partial fulfillment of the requirements for the degree of Master of Science in the Department of Computer Science"--Thesis t.p. Vita. Includes bibliographical references.
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Herodotou, Nicos. "Spatial and temporal prediction schemes for object-based digital video." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape11/PQDD_0014/NQ41438.pdf.

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Loutos, Gerasimos. "Development of prediction schemes for real-time bus arrival information." Thesis, KTH, Transportvetenskap, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-145939.

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Intelligent Transport Systems (ITS) are increasingly used in public transport systems in order to provide real-time information (RTI) to passengers and operators. In particular, the RTI related to the prediction of remaining time until the arrival of the next vehicle is the most commonly provisioned information and the main focus of research. A number of predictions methods have been proposed without clear evidence of their real-world applicability, mainly because of their highly computational complexity. Moreover new sources of information, which could be used in RTI generators, become availa
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Books on the topic "Predictive schemes"

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Sigg, Stephan. Development of a novel context prediction algorithm and analysis of context prediction schemes. Kassel Univ. Press, 2008.

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Hawken, D. F. Prediction of two-dimensional time-dependent gasdynamic flows for hypersonic studies. Institute for Aerospace Studies, 1990.

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Naisbitt, John. Mind Set! HarperCollins, 2006.

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Naisbitt, John. Mind set!: Reset your mind and see the future. Collins, 2006.

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R, Kulkarni J., and Indian Institute of Tropical Meteorology., eds. Multimodel scheme for prediction of monthly rainfall over India. Indian Institute of Tropical Meteorology, 2003.

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1936-, Webster Christopher D., and University of Toronto. Centre of Criminology., eds. The Violence prediction scheme: Assessing dangerousness in high risk men. Centre of Criminology, University of Toronto, 1994.

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Lunn, G. D. Physiological control of hagberg falling number and sprouting in winter wheat and development of a prediction scheme. HGCA, 1998.

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Stewart, Paul C. Incorporation of a radiation parameterization scheme into the Naval Research Laboratory Limited Area Dynamical Weather Prediction Model. Naval Postgraduate School, 1992.

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United States. National Aeronautics and Space Administration., ed. Development of comprehensive numerical schemes for predicting evaporating gas-droplets flow processes of a liquid-fueled combustor: Semi-annual report, June 15, 1988-November 30, 1988. National Aeronautics and Space Administration, 1990.

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Langton, Calvin M. Contrasting approaches to risk assessment with adult male sexual offenders: An evaluation of recidivism prediction schemes and the utility of supplementary clinical information for enhancing predictive accuracy. 2003.

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Book chapters on the topic "Predictive schemes"

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Camacho, Eduardo F., and Carlos Bordons. "Commercial Model Predictive Control Schemes." In Model Predictive Control. Springer London, 1999. http://dx.doi.org/10.1007/978-1-4471-3398-8_3.

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Camacho, E. F., and C. Bordons. "Commercial Model Predictive Control Schemes." In Model Predictive control. Springer London, 2007. http://dx.doi.org/10.1007/978-0-85729-398-5_3.

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Alamir, Mazen. "A Framework for Monitoring Control Updating Period in Real-Time NMPC Schemes." In Nonlinear Model Predictive Control. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01094-1_34.

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Hirzinger, G. "Predictive and Estimation Schemes in Sensor-Controlled Telerobotics." In Sensor Devices and Systems for Robotics. Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/978-3-642-74567-6_24.

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Chen, H., and F. Allgöwer. "Nonlinear Model Predictive Control Schemes with Guaranteed Stability." In Nonlinear Model Based Process Control. Springer Netherlands, 1998. http://dx.doi.org/10.1007/978-94-011-5094-1_16.

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Heinmöller, Petra, Gudrun Bänfer, Marius Grzelinski, Katya Victoria Alexander, Kathrina A. Alexander, and Bharat Jasani. "Quality Control of Immunohistochemical and In Situ Hybridization Predictive Biomarkers for Patient Treatment: Experience from International Guidelines and International Quality Control Schemes." In Predictive Biomarkers in Oncology. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-95228-4_48.

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Rosich, Albert, and Carlos Ocampo-Martinez. "Real-Time Experimental Implementation of Predictive Control Schemes in a Small-Scale Pasteurization Plant." In Developments in Model-Based Optimization and Control. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-26687-9_12.

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Verhaak, Roel G. W., and Peter J. M. Valk. "Genes Predictive of Outcome and Novel Molecular Classification Schemes in Adult Acute Myeloid Leukemia." In Acute Myelogenous Leukemia. Springer New York, 2009. http://dx.doi.org/10.1007/978-0-387-69259-3_5.

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Sun, Wei, Shaoxiong Ji, Erik Cambria, and Pekka Marttinen. "Multitask Recalibrated Aggregation Network for Medical Code Prediction." In Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-86514-6_23.

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AbstractMedical coding translates professionally written medical reports into standardized codes, which is an essential part of medical information systems and health insurance reimbursement. Manual coding by trained human coders is time-consuming and error-prone. Thus, automated coding algorithms have been developed, building especially on the recent advances in machine learning and deep neural networks. To solve the challenges of encoding lengthy and noisy clinical documents and capturing code associations, we propose a multitask recalibrated aggregation network. In particular, multitask lea
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Sukhinov, Aleksandr, Albert Isayev, Alla Nikitina, Aleksandr Chistyakov, Vladimir Sumbaev, and Alena Semenyakina. "Complex of Models, High-Resolution Schemes and Programs for the Predictive Modeling of Suffocation in Shallow Waters." In Communications in Computer and Information Science. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-67035-5_13.

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Conference papers on the topic "Predictive schemes"

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Mousavi, Mahdi S., S. Alireza Davari, Mokhtar Aly, Cristian Garcia, Freddy Flores-Bahamonde, and Jose Rodriguez. "Second-Order Model-Free Predictive Speed Control of PMSM Drives with Comparison of Cascaded and Non-Cascaded Speed Control Schemes." In 2024 IEEE International Conference on Automation/XXVI Congress of the Chilean Association of Automatic Control (ICA-ACCA). IEEE, 2024. http://dx.doi.org/10.1109/ica-acca62622.2024.10766780.

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Yan, Liming, Yang Yang, and Xuding Song. "A Comparison on Finite-Set Predictive Torque Control Schemes for Induction Machines." In 2021 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics (PRECEDE). IEEE, 2021. http://dx.doi.org/10.1109/precede51386.2021.9681002.

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Hill, Elyse D., Donald L. Simon, and Joseph W. Connolly. "A Comparison of Model Predictive Control Architectures for Application to Electrified Aircraft Propulsion Systems." In ASME Turbo Expo 2024: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2024. http://dx.doi.org/10.1115/gt2024-123859.

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Abstract As electrified aircraft propulsion (EAP) systems continue to mature, more sophisticated hardware and software are being developed to balance operations among electric machines and gas-turbine engines. In hybrid-electric propulsion systems, the increased complexity resulting from integrating turbine-engine shafts with electric machines necessitates control methodologies to account for various physical domains. Ideal controllers for hybrid-electric engines manage systems, subsystems, and their interactions in a coordinated fashion, able to account for safety and performance goals while
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Yu, Zhanfan, and Sally Sajadian. "Trends on Predictive Control Schemes for Impedance Source Converters." In 2020 IEEE Power and Energy Conference at Illinois (PECI). IEEE, 2020. http://dx.doi.org/10.1109/peci48348.2020.9064639.

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Kozubik, Michal, Pavel Vaclavek, and Inigo Garcia de Madinabeitia Merino. "Adaptivity Schemes for Model Predictive Speed Control of PMSM." In IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society. IEEE, 2022. http://dx.doi.org/10.1109/iecon49645.2022.9968981.

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Li, Po, Ruinan Liu, and Xianghui Ma. "Adaptive indirect model predictive control schemes for boost converters." In 2017 36th Chinese Control Conference (CCC). IEEE, 2017. http://dx.doi.org/10.23919/chicc.2017.8028822.

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Ananduta, Wicak, Julian Barreiro-Gomez, Carlos Ocampo-Martinez, and Nicanor Quijano. "Resilient Information-Exchange Protocol for Distributed Model Predictive Control Schemes." In 2018 Annual American Control Conference (ACC). IEEE, 2018. http://dx.doi.org/10.23919/acc.2018.8430923.

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Findeisen, R., M. Diehl, Z. Nagy, F. Allgower, H. G. Bock, and J. P. Schloder. "Computational feasibility and performance of nonlinear model predictive control schemes." In 2001 European Control Conference (ECC). IEEE, 2001. http://dx.doi.org/10.23919/ecc.2001.7076036.

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Donoso, Felipe, Andres Mora, Mauricio Espinoza, Matias Urrutia, Enrique Espina, and Roberto Cardenas. "Predictive-based Modulation Schemes for the Hybrid Modular Multilevel Converter." In 2019 21st European Conference on Power Electronics and Applications (EPE '19 ECCE Europe). IEEE, 2019. http://dx.doi.org/10.23919/epe.2019.8914876.

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Xiang, Yujiang. "Muscle Force Prediction of 2D Gait Using Predictive Dynamics Optimization." In ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/detc2016-59107.

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Cyclic human gait is simulated in this work by using a 2D musculoskeletal model with 12 degrees of freedom (DOF). Eight muscle groups are modeled on each leg. Predictive dynamics approach is used to predict the walking motion. In this process, the model predicts joints dynamics and muscle forces simultaneously using optimization schemes and task-based physical constraints. The results indicated that the model can realistically match human motion, ground reaction forces (GRF), and muscle force data during walking task. The proposed optimization algorithm is robust and the optimal solution is ob
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Reports on the topic "Predictive schemes"

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von Lilienfeld-Toal, Otto Anatole. Multiscale schemes for the predictive description and virtual engineering of materials. Office of Scientific and Technical Information (OSTI), 2010. http://dx.doi.org/10.2172/991008.

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Stebbing, Nicola, Claire Witham, Frances Beckett, Helen Webster, Lois Huggett, and David Thomson. © Crown copyright 2024, Met Office Page 1 of 43 Can we improve plume dispersal modelling for fire related emergency response operations by utilising short-range dispersion schemes? Met Office, 2024. http://dx.doi.org/10.62998/wnnr5415.

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Large fires that produce plumes of smoke and other contaminants can cause harm to both people and the environment. To support UK emergency responders, the Met Office Environmental Monitoring and Response Centre (EMARC) provides dedicated weather advice and forecasts of the plume in the form of CHEmical METeorological (CHEMET) reports. The plume’s expected location, extent and relative air concentrations of pollutants are predicted using the Numerical Atmospheric-dispersion Modelling Environment (NAME), which simulates the transport and dispersion of pollutants using numerical weather predictio
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Ziegler, Nancy, Nicholas Webb, John Gillies, et al. Plant phenology drives seasonal changes in shear stress partitioning in a semi-arid rangeland. Engineer Research and Development Center (U.S.), 2023. http://dx.doi.org/10.21079/11681/47680.

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Accurate representation of surface roughness in predictive models of aeolian sediment transport and dust emission is required for model accuracy. While past studies have examined roughness effects on drag partitioning, the spatial and temporal variability of surface shear velocity and the shear stress ratio remain poorly described. Here, we use a four-month dataset of total shear velocity (u*) and soil surface shear velocity (us*) measurements to examine the spatiotemporal variability of the shear stress ratio (R) before, during, and after vegetation green-up at a honey mesquite (Prosopis glan
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Hedrick and Jacobs. PR-457-14201-R01 Variable Natural Gas - Composition Effects and Control Methods for Two-Stroke Engines. Pipeline Research Council International, Inc. (PRCI), 2015. http://dx.doi.org/10.55274/r0010027.

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Literature is reviewed for the impacts of variable natural gas composition on two-stroke lean burn pipeline compressor engines. Information gathered for these engines can be simplified for development of control algorithms in four-stroke and richer burning engines. Data shows that geospatial, geological, and transient hydraulic effects cause composition variations that adversely affect engine emissions, efficiency, rated performance, and operational safety considering auto-ignition effects. In order to compensate for these changes in composition, better engine control schemes can help meet des
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Karypis, George. Better Kernels and Coding Schemes Lead to Improvements in SVM-Based Secondary Structure Prediction. Defense Technical Information Center, 2005. http://dx.doi.org/10.21236/ada439626.

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Mogliani, Matteo, and Florens Odendahl. Density forecast transformations. Banco de España, 2025. https://doi.org/10.53479/38959.

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The common choice of using a direct forecasting scheme implies that the individual predictions ignore information on their cross-horizon dependence. However, this dependence is needed if the forecaster has to construct, based on direct density forecasts, predictive objects that are functions of several horizons (e.g. when constructing annual-average growth rates from quarter-on-quarter growth rates). To address this issue we propose using copulas to combine the individual h-step-ahead predictive distributions into one joint predictive distribution. Our method is particularly appealing to those
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7

Knaff, John A. Development and Implementation of a Statistical Typoon Intensity Prediction Scheme for the Western North Pacific. Defense Technical Information Center, 2002. http://dx.doi.org/10.21236/ada404023.

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Robinson, Allan R. Ocean Prediction Research: Regional Forecasting, Process and Methodology. A Forecast Scheme for the Iceland-Faeroes Front in the GIUK Gap. Defense Technical Information Center, 1989. http://dx.doi.org/10.21236/ada238462.

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9

Dutra, Lauren M., Matthew C. Farrelly, Brian Bradfield, Jamie Ridenhour, and Jamie Guillory. Modeling the Probability of Fraud in Social Media in a National Cannabis Survey. RTI Press, 2021. http://dx.doi.org/10.3768/rtipress.2021.mr.0046.2109.

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Cannabis legalization has spread rapidly in the United States. Although national surveys provide robust information on the prevalence of cannabis use, cannabis disorders, and related outcomes, information on knowledge, attitudes, and beliefs (KABs) about cannabis is lacking. To inform the relationship between cannabis legalization and cannabis-related KABs, RTI International launched the National Cannabis Climate Survey (NCCS) in 2016. The survey sampled US residents 18 years or older via mail (n = 2,102), mail-to-web (n = 1,046), and two social media data collections (n = 11,957). This report
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Fan, Xiaoyuan, Renke Huang, Qiuhua Huang, et al. Adaptive RAS/SPS System Setting for Improving Grid Reliability and Asset Utilization through Predictive Simulation and Controls: A Use Case for Transformative Remedial Action Scheme Tool (TRAST): Jim Bridger RAS Evaluation and Analysis. Office of Scientific and Technical Information (OSTI), 2019. http://dx.doi.org/10.2172/1604168.

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