Relevant bibliographies by topics / Accuracy of model

Academic literature on the topic 'Accuracy of model'

Author: Grafiati
Published: 30 May 2022
Last updated: 31 May 2022

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Journal articles on the topic "Accuracy of model"

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Aubakirov, S. S., P. Trigo, and D. Zh Ahmed-zaki. "BUILDING A MODEL TO PREDICT CLASSIFIER ACCURACY." Eurasian Journal of Mathematical and Computer Applications 5, no. 3 (2017): 4–14. http://dx.doi.org/10.32523/2306-3172-2017-5-3-4-14.

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Fan, Mingyu, Daisuke Tanaka, and Seiichi Serikawa. "Proposal of Triggered Touch Switch Model with High Accuracy." Journal of the Institute of Industrial Applications Engineers 4, no. 2 (April 25, 2016): 94–99. http://dx.doi.org/10.12792/jiiae.4.94.

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Weld, Daniel S. "Reasoning about model accuracy." Artificial Intelligence 56, no. 2-3 (August 1992): 255–300. http://dx.doi.org/10.1016/0004-3702(92)90029-w.

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Ravibabu, Mandla V., and Kamal Jain. "Digital Elevation Model Accuracy Aspects." Journal of Applied Sciences 8, no. 1 (December 15, 2007): 134–39. http://dx.doi.org/10.3923/jas.2008.134.139.

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Ljung, L. "Model Accuracy in System Identification." IFAC Proceedings Volumes 24, no. 1 (January 1991): 277–81. http://dx.doi.org/10.1016/s1474-6670(17)51332-4.

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Nash, Murray, Michael Anstis, and Michael Bradbury. "Testing Corporate Model Prediction Accuracy." Australian Journal of Management 14, no. 2 (December 1989): 211–21. http://dx.doi.org/10.1177/031289628901400205.

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TOLSTOY, A. "PROPAGATION MODEL ACCURACY FOR MFP." Journal of Computational Acoustics 08, no. 03 (September 2000): 389–99. http://dx.doi.org/10.1142/s0218396x00000315.

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The selection of a propagation model for use in many underwater acoustic applications has been understood to be highly important for quite some time. However, it has not previously been understood how various models might actually degrade Matched Field Processing (MFP) performance even when input parameters are known exactly. That is, acoustic propagation models have not previously been benchmarked within the context of MFP where acoustic amplitudes and phases need to be highly accurate depending on the nature of the processor of interest, such as for a high resolution Capon processor. This paper discusses the SCOOTER, ORCA, and KRAKEN models, and a high angle PE model within the context of MFP. These models are compared to the SAFARI data generated for the Workshop97 geoacoustic inversion CAL case. In general it seems that all the abovementioned models show excellent accuracy for use with the Linear Processor. However, it is found that KRAKEN may experience unexpected difficulties at unpredictable frequencies where these errors can affect high resolution processing (as demonstrated by geoacoustic inversions via the RIGS method),14 that SCOOTER and PE require relatively long CPU times for high accuracy, and that how accurately parameters are interpolated, e.g., sound-speed profiles, can also be important. It should be noted that all of the models discussed in this work may be considered to be very accurate in the context of most applications, particularly those involving data.
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Molin, Bengt-Arne. "On MOS transistor model accuracy." Microelectronics Journal 18, no. 1 (January 1987): 5–11. http://dx.doi.org/10.1016/s0026-2692(87)80359-2.

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Chatfield, Chris. "Model uncertainty and forecast accuracy." Journal of Forecasting 15, no. 7 (December 1996): 495–508. http://dx.doi.org/10.1002/(sici)1099-131x(199612)15:7<495::aid-for640>3.0.co;2-o.

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Galkin, V. S., and S. V. Rusakov. "Accuracy of model kinetic equations." Fluid Dynamics 51, no. 1 (January 2016): 109–19. http://dx.doi.org/10.1134/s0015462816010130.

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Dissertations / Theses on the topic "Accuracy of model"

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Fann, Chee Meng. "Development of an artillery accuracy model." Thesis, Monterey, Calif. : Naval Postgraduate School, 2006. http://bosun.nps.edu/uhtbin/hyperion.exe/06Dec%5FFann.pdf.

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Thesis (M.S. in Engineering Science (Mechanical Engineering)--Naval Postgraduate School, December 2006.
Thesis Advisor(s): Morris Driels. "December 2006." Includes bibliographical references (p. 91). Also available in print.
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Gunner, J. C. "A model of building price forecasting accuracy." Thesis, University of Salford, 1997. http://usir.salford.ac.uk/26702/.

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The purpose of this research was to derive a statistical model comprising the significant factors influencing the accuracy of a designer's price forecast and as an aid to providing a theoretical framework for further study. To this end data, comprising 181 building contract details, was collected from the Singapore office of an international firm of quantity surveyors over the period 1980 to 1991. Bivariate analysis showed a number of independent variables having significant effect on bias which was in general agreement with previous work in this domain. The research also identified a number of independent variables having significant effect on the consistency, or precision, of designers' building price forecasts. With information gleaned from bivariate results attempts were made to build a multivariate model which would explain a significant portion of the errors occurring in building price forecasts. The results of the models built were inconclusive because they failed to satisfy the assumptions inherent in ordinary least squares regression. The main failure in the models was in satisfying the assumption of homoscedasticity, that is, the conditional variances of the residuals are equal around the mean. Five recognised methodologies were applied to the data in attempts to remove heteroscedasticity but none were successful. A different approach to model building was then adopted and a tenable model was constructed which satisfied all of the regression assumptions and internal validity checks. The statistically significant model also revealed that the variable of Price Intensity was the sole underlying influence when tested against all other independentpage xiv variables in the data of this work and after partialling out the effect of all other independent variables. From this a Price Intensity theory of accuracy is developed and a further review of the previous work in this field suggests that this may be of universal application.
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Xu, Wenwei. "Enhancing model accuracy for control : two case studies /." free to MU campus, to others for purchase, 2002. http://wwwlib.umi.com/cr/mo/fullcit?p3074458.

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Frazier, Alicia. "Accuracy and precision of a sectioned hollow model." Oklahoma City : [s.n.], 2008.

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Lehmann, Christopher, and Alexander Alfredsson. "Intrinsic Equity Valuation : An Emprical Assessment of Model Accuracy." Thesis, Södertörns högskola, Institutionen för samhällsvetenskaper, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:sh:diva-30377.

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The discounted cash flow model and relative valuation models are ever-increasingly prevalent in today’s investment-heavy environment. In other words, theoretically inferior models are used in practice. It is this paradox that has lead us to compare the discounted cash flow model (DCFM), discounted dividend model (DDM), residual income-based model (RIVM) and the abnormal earnings growth model (AEGM) and their relative accuracy to observed stockprices. Adding to previous research, we investigate their performance in relation to the OMX30 index. What is more, we test how the performance of each model is affected by an extension of the forecast horizon. The study finds that AEGM outperforms the other models, both before and after extending the horizon. Our analysis was conducted by looking at accuracy, spread and the inherent speculative nature of each model. Taking all this into account, RIVM outperforms the other models. In this sense, one can question the rationale behind investor’s decision to primarily use the discounted cash flow model in equity valuation.
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Mitchinson, Pelham James. "Crowding indices : experimental methodology and predictive accuracy." Thesis, University of Southampton, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.302320.

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Bilen, Oytun Peksel. "Advanced Model of Acoustic Trim; Effect on NTF Accuracy." Thesis, KTH, MWL Marcus Wallenberg Laboratoriet, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-77768.

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Hone, David M. "Time and space resolution and mixed layer model accuracy." Monterey, California. Naval Postgraduate School, 1997. http://hdl.handle.net/10945/9080.

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The oceanic turbulent boundary layer is a critical region to understand for oceanic and atmospheric prediction. This thesis answers two fundamental questions: (1) what is the response of the ocean mixed layer system to transient forcing at the air sea surface? (2) what is the necessary time and space resolution in an ocean mixed layer model to resolve important transient responses? Beginning with replication of de Szoeke and Rhines' work, additional physical processes were added to include more realistic viscous dissipation and anisotropy in the three-dimensional turbulent kinetic energy (TKE) budget. These refinements resulted in modification of de Szoeke and Rhines' findings. Firstly, TKE unsteadiness is important for a minimum of 10 to the 5th power seconds. Secondly, viscous dissipation should not be approximated as simply proportional to shear production. Thirdly, entrainment shear production remains significant for a minimum of one pendulum-day. The required temporal model resolution is dependent on the phenomena to be studied. This study focused on the diurnal, synoptic, and annual cycles, which the one-hour time step of the Naval Postgraduate School model adequately resolves. The study of spatial resolution showed unexpectedly that model skill was comparable for 1 m, 10 m and even 20 m vertical grid spacing
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Tjoa, Robertus Tjin Hok Carleton University Dissertation Engineering Mechanical. "Assessment of the accuracy of a computational casting model." Ottawa, 1992.

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Lee, Jacob Scott. "Accuracy of a Simplified Analysis Model for Modern Skyscrapers." BYU ScholarsArchive, 2013. https://scholarsarchive.byu.edu/etd/4055.

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A new simplified skyscraper analysis model (SSAM) was developed and implemented in a spreadsheet to be used for preliminary skyscraper design and teaching purposes. The SSAM predicts linear and nonlinear response to gravity, wind, and seismic loading of "modern" skyscrapers which involve a core, megacolumns, outrigger trusses, belt trusses, and diagonals. The SSAM may be classified as a discrete method that constructs a reduced system stiffness matrix involving selected degrees of freedom (DOF's). The steps in the SSAM consist of: 1) determination of megacolumn areas, 2) construction of stiffness matrix, 3) calculation of lateral forces and displacements, and 4) calculation of stresses. Seven configurations of a generic skyscraper were used to compare the accuracy of the SSAM against a space frame finite element model. The SSAM was able to predict the existence of points of contraflexure in the deflected shape which are known to exist in modern skyscrapers. The accuracy of the SSAM was found to be very good for displacements (translations and rotations), and reasonably good for stress in configurations that exclude diagonals. The speed of execution, data preparation, data extraction, and optimization were found to be much faster with the SSAM than with general space frame finite element programs.
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Books on the topic "Accuracy of model"

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Fildes, Robert. Accuracy gains through individual univariate forecasting: Model selection. Manchester: Manchester Business School, 1986.

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Miller, Nicholas P., Sean M. Doyle, Bradley L. Nicholas, Monty Gettys, Joe Gettys, and Greg Price. Integrated Noise Model Accuracy for General Aviation Aircraft. Washington, D.C.: Transportation Research Board, 2014. http://dx.doi.org/10.17226/22269.

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Hone, David M. Time and space resolution and mixed layer model accuracy. Monterey, Calif: Naval Postgraduate School, 1997.

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Eckstein, Miguel P. Analytic guided-search model of human performance accuracy in target-localization search tasks. Moffett Field, Calif: National Aeronautics and Space Administration, Ames Research Center, 2000.

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Ogawa, Hiroyuki. Testing the accuracy of a three-dimensional acoustic coupled mode model. Monterey, Calif: Naval Postgraduate School, 1991.

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Morelli, Eugene A. Determining the accuracy of aerodynamic model parameters estimated from flight test data. Washington, D.C: American Institute of Aeronautics and Astronautics, 1995.

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Morelli, Eugene A. Determining the accuracy of aerodynamic model parameters estimated from flight test data. Washington, D.C: American Institute of Aeronautics and Astronautics, 1995.

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Morelli, Eugene A. Determining the accuracy of aerodynamic model parameters estimated from flight test data. Washington, D.C: American Institute of Aeronautics and Astronautics, 1995.

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Thalieb, Rio M. An accuracy analysis of Army Material System Analysis Activity discrete reliability growth model. Monterey, California: Naval Postgraduate School, 1988.

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Williams, Brian J. Effects of storm-related parameters on the accuracy of the nested tropical cyclone model. Monterey, Calif: Naval Postgraduate School, 1986.

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Book chapters on the topic "Accuracy of model"

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Burkholder, Earl F. "Spatial Data Accuracy." In The 3-D Global Spatial Data Model, 305–28. Second edition. | Boca Raton : CRC Press, 2017.: CRC Press, 2017. http://dx.doi.org/10.1201/9781315120102-12.

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Burkholder, Earl F. "Computing Network Accuracy and Local Accuracy Using the Global Spatial Data Model." In The 3-D Global Spatial Data Model, 365–77. Second edition. | Boca Raton : CRC Press, 2017.: CRC Press, 2017. http://dx.doi.org/10.1201/9781315120102-14.

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Prado, Hércules A., Karla F. Machado, Sandra R. Frigeri, and Paulo M. Engel. "Accuracy Tuning on Combinatorial Neural Model." In Methodologies for Knowledge Discovery and Data Mining, 247–52. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/3-540-48912-6_33.

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Strug, Joanna. "Mutation Testing in Model Accuracy Assessment." In Advances in Intelligent Systems and Computing, 201–11. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46586-9_16.

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Han, Yaofei, Chao Gong, and Jinqiu Gao. "MPC Accuracy Improvement for PMSMs—Part I." In Model Predictive Control for AC Motors, 65–98. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-8066-3_4.

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Han, Yaofei, Chao Gong, and Jinqiu Gao. "MPC Accuracy Improvement for PMSMs—Part II." In Model Predictive Control for AC Motors, 99–126. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-8066-3_5.

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Vasandani, Juily, Saumya Bharti, Deepankar Singh, and Shreeansh Priyadarshi. "Improving Model Accuracy with Probability Scoring Machine Learning Models." In Advances in Data Science and Information Engineering, 517–30. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-71704-9_34.

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Sun, Guang, Lirong Shen, Xiangyu Zhu, Xiaolin Jia, Xiaogang Liu, Meijun Guo, Wei Zhai, Yingjie Hong, and Jie Zheng. "Accuracy Analysis of GNSS Broadcast Ionospheric Model." In Lecture Notes in Electrical Engineering, 355–67. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-7759-4_32.

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Memon, Tasneem, Jie Lu, and Farookh Khadeer Hussain. "An Enhanced Mental Model Elicitation Technique to Improve Mental Model Accuracy." In Neural Information Processing, 82–89. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-42054-2_11.

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Romero-Fresco, Pablo, and Juan Martínez Pérez. "Accuracy Rate in Live Subtitling: The NER Model." In Audiovisual Translation in a Global Context, 28–50. London: Palgrave Macmillan UK, 2015. http://dx.doi.org/10.1057/9781137552891_3.

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Conference papers on the topic "Accuracy of model"

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Czarnecki, Andrzej, and Kirill Melnikov. "|Vcb| from semileptonic B decays with two-loop QCD accuracy." In Beyond the standard model. American Institute of Physics, 1997. http://dx.doi.org/10.1063/1.54488.

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Karshenas, Hossein, Amin Nikanjam, B. Hoda Helmi, and Adel T. Rahmani. "Model accuracy for hierarchical problems." In 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems (ICIS 2009). IEEE, 2009. http://dx.doi.org/10.1109/icicisys.2009.5358041.

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Knyazev, Andrew, Peizhen Zhu, and Stefano Di Cairano. "Explicit model predictive control accuracy analysis." In 2015 54th IEEE Conference on Decision and Control (CDC). IEEE, 2015. http://dx.doi.org/10.1109/cdc.2015.7402565.

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Van der Ha, Jozef C. "Spin Axis Attitude Determination Accuracy Model." In 54th International Astronautical Congress of the International Astronautical Federation, the International Academy of Astronautics, and the International Institute of Space Law. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2003. http://dx.doi.org/10.2514/6.iac-03-a.5.08.

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Storz, Mark, Bruce Bowman, and James Branson. "High Accuracy Satellite Drag Model (HASDM)." In AIAA/AAS Astrodynamics Specialist Conference and Exhibit. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2002. http://dx.doi.org/10.2514/6.2002-4886.

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Sendur, Polat, Jeffrey L. Stein, Huei Peng, and Loucas S. Louca. "A Model Accuracy and Validation Algorithm." In ASME 2002 International Mechanical Engineering Congress and Exposition. ASMEDC, 2002. http://dx.doi.org/10.1115/imece2002-39580.

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Dynamic models of physical systems with physically meaningful states and parameters have become increasingly important, for design, control and even procurement decisions. The successful use of models in these contexts requires that the models be of sufficient quality. However, while algorithms have been developed to help formulate and integrate physical system models, as well as to generate minimum complexity physical system models, algorithms to assess the “quality” of dynamic system models have not been produced. This is true even if the attributes of model are limited to accuracy and validity. The objective of this paper is to introduce a new methodology that systematically quantifies the accuracy of a predicted system response and determines the validity of the physical system model used to predict the system response. The accuracy and validity of the model are evaluated using statistical properties of measured system response. The new algorithm is called Accuracy & Validation Algorithm for Simulation (AVASIM), and is a time-domain perspective comparing the model’s time trajectories at user-defined points of interest as well as over the entire simulation horizon. To illustrate AVASIM, the quality of a handling model of a DaimlerChrysler Grand Cherokee is compared to the measurements obtained from that vehicle subjected to known steering inputs. Results demonstrate that the accuracy and validity of the Grand Cherokee model can be systematically assessed using the proposed methodology, and, thus, AVASIM appears to be a powerful tool for assessing the quality of system models.
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Busany, Nimrod, Shahar Maoz, and Yehonatan Yulazari. "Size and Accuracy in Model Inference." In 2019 34th IEEE/ACM International Conference on Automated Software Engineering (ASE). IEEE, 2019. http://dx.doi.org/10.1109/ase.2019.00087.

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Lyons, Adam, Tom Wallow, Christoph Hennerkes, Chris Spence, Maxence Delorme, David Rio, Dai Tsunoda, Yohei Torigoe, and Masakazu Hamaji. "Mask contribution to OPC model accuracy." In International Conference on Extreme Ultraviolet Lithography 2020, edited by Kurt G. Ronse, Paolo A. Gargini, Patrick P. Naulleau, and Toshiro Itani. SPIE, 2020. http://dx.doi.org/10.1117/12.2573160.

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Sudkamp, Elizabeth, John Nehrbass, Eric Branch, and Michael Levy. "Synthetic data accuracy sensitivity to CAD model accuracy using ATR-based metrics." In Algorithms for Synthetic Aperture Radar Imagery XXVI, edited by Edmund Zelnio and Frederick D. Garber. SPIE, 2019. http://dx.doi.org/10.1117/12.2523456.

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Kong, L. X., and P. D. Hodgson. "Improving the prediction accuracy of constitutive model with ANN models." In Proceedings of the Second International Conference on Intelligent Processing and Manufacturing of Materials. IPMM'99 (Cat. No.99EX296). IEEE, 1999. http://dx.doi.org/10.1109/ipmm.1999.792511.

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Reports on the topic "Accuracy of model"

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Hembree, Charles E., Alan Mar, and Perry J. Robertson. High Accuracy Transistor Compact Model Calibrations. Office of Scientific and Technical Information (OSTI), September 2015. http://dx.doi.org/10.2172/1222177.

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Bass, J. N., N. Grossbard, and E. C. Robinson. Statistical Parameters for Describing Model Accuracy. Fort Belvoir, VA: Defense Technical Information Center, March 1989. http://dx.doi.org/10.21236/ada209933.

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Ramirez, A., and S. Myers. Accuracy tests of the tessellated SLBM model. Office of Scientific and Technical Information (OSTI), July 2007. http://dx.doi.org/10.2172/921153.

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Sauter, Barbara. Forecast Model Uncertainty; MM5 Accuracy Over Utah. Fort Belvoir, VA: Defense Technical Information Center, March 2004. http://dx.doi.org/10.21236/ada422720.

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McCracken, Michael W., and Todd E. Clark. Nested Forecast Model Comparisons: A New Approach to Testing Equal Accuracy. Federal Reserve Bank of St. Louis, 2009. http://dx.doi.org/10.20955/wp.2009.050.

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Menikoff, Ralph. Accuracy of High Explosive Data used for Reactive Burn Model Calibration. Office of Scientific and Technical Information (OSTI), August 2020. http://dx.doi.org/10.2172/1578002.

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Wu, S. T., T. W. Zhang, Xueshang Feng, and Arjun Tan. Physics-Based Analysis Using the Empirical High Accuracy Satellite Dray Model (HASD). Fort Belvoir, VA: Defense Technical Information Center, September 2002. http://dx.doi.org/10.21236/ada465798.

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Goldman, Nir, and Ryan Mullen. Completed coarse-grained model for Pu hydriding that has quantum accuracy (Progress Summary). Office of Scientific and Technical Information (OSTI), June 2019. http://dx.doi.org/10.2172/1527288.

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Hu, Miao, and Scott R. Fulton. Comparison of Discretization Accuracy in an Adaptive Multigrid Barotropic Tropical Cyclone Track Model. Fort Belvoir, VA: Defense Technical Information Center, May 2000. http://dx.doi.org/10.21236/ada377011.

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Rao, Vivek, Vineet Kumar, Alexandra Anderson, and Prashant Jain. High-Accuracy Simulations to Model Pyrometallurgical Processes in a Secondary Lead Reverberatory Furnace. Office of Scientific and Technical Information (OSTI), August 2021. http://dx.doi.org/10.2172/1824975.

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