Letteratura scientifica selezionata sul tema "States estimation"

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Articoli di riviste sul tema "States estimation":

1

Wasim, Muhammad, Ahsan Ali, Muhammad Mateen Afzal Awan e Inam ul Hasan Shaikh. "Estimation of airship states and model uncertainties using nonlinear estimators". Mehran University Research Journal of Engineering and Technology 43, n. 1 (1 gennaio 2024): 55. http://dx.doi.org/10.22581/muet1982.2401.1613.

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This Airships are lighter than air vehicles and due to their growing number of applications, they are becoming attractive for the research community. Most of the applications require an airship autonomous flight controller which needs an accurate model and state information. Usually, airship states are affected by noise and states information can be lost in the case of sensor's faults, while airship model is affected by model inaccuracies and model uncertainties. This paper presents the application of nonlinear and Bayesian estimators for estimating the states and model uncertainties of neutrally buoyant airship. It is considered that minimum sensor measurements are available, and data is corrupted with process and measurement noise. A novel lumped model uncertainty estimation approach is formulated where airship model is augmented with six extra state variables capturing the model uncertainty of the airship. The designed estimator estimates the airship model uncertainty along with its states. Nonlinear estimators, Extended Kalman Filter and Unscented Kalman Filter are designed for estimating airship attitude, linear velocities, angular velocities and model uncertainties. While Particle filter is designed for the estimation of airship attitude, linear velocities and angular velocities. Simulations have been performed using nonlinear 6-DOF simulation model of experimental airship for assessing the estimator performances. 1−𝜎 uncertainty bound and error analysis have been performed for the validation. A comparative study of the estimator's performances is also carried out.
2

Talla Ouambo, Steve Alan, Alexandre Teplaira Boum e Adolphe Moukengue Imano. "States and Parameters Estimation for Induction Motors Based on a New Adaptive Moving Horizon Estimation". Journal of Electrical and Computer Engineering 2022 (12 novembre 2022): 1–11. http://dx.doi.org/10.1155/2022/8687025.

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This paper investigates the joint states and parameters estimation problem for induction machine. In order to develop new states and parameters estimation methods that greatly improve the estimation bandwidth, this paper proposes an adaptive moving horizon estimation of the crucial states and parameters of the induction machine. The model of the machine under study is the one taking into consideration the magnetic saturation and the iron losses simultaneously. The estimator used is based on a least squares algorithm but includes a dead zone that ensures robustness and a variable forgetting factor that is based on the constant information principle. The simulation results show that the adaptive estimator can efficiently estimate the states and parameters of the induction machine with a fast convergence rate despite the initial parametric errors.
3

Zerdali, Emrah, e Murat Barut. "Extended Kalman Filter Based Speed-Sensorless Load Torque and Inertia Estimations with Observability Analysis for Induction Motors". Power Electronics and Drives 3, n. 1 (1 dicembre 2018): 115–27. http://dx.doi.org/10.2478/pead-2018-0002.

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Abstract This paper aims to introduce a novel extended Kalman filter (EKF) based estimator including observability analysis to the literature associated with the high performance speed-sensorless control of induction motors (IMs). The proposed estimator simultaneously performs the estimations of stator stationary axis components of stator currents and rotor fluxes, rotor mechanical speed, load torque including the viscous friction term, and reciprocal of total inertia by using measured stator phase currents and voltages. The inertia estimation is done since it varies with the load coupled to the shaft and affects the performance of speed estimation especially when the rotor speed changes. In this context, the estimations of all mechanical state and parameters besides flux estimation required for high performance control methods are performed together. The performance of the proposed estimator is tested by simulation and real-time experiments under challenging variations in load torque and velocity references; and in both transient and steady states, the quite satisfactory estimation performance is achieved.
4

Zhang, Xiao, Feng Ding, Ling Xu, Ahmed Alsaedi e Tasawar Hayat. "A Hierarchical Approach for Joint Parameter and State Estimation of a Bilinear System with Autoregressive Noise". Mathematics 7, n. 4 (17 aprile 2019): 356. http://dx.doi.org/10.3390/math7040356.

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This paper is concerned with the joint state and parameter estimation methods for a bilinear system in the state space form, which is disturbed by additive noise. In order to overcome the difficulty that the model contains the product term of the system input and states, we make use of the hierarchical identification principle to present new methods for estimating the system parameters and states interactively. The unknown states are first estimated via a bilinear state estimator on the basis of the Kalman filtering algorithm. Then, a state estimator-based recursive generalized least squares (RGLS) algorithm is formulated according to the least squares principle. To improve the parameter estimation accuracy, we introduce the data filtering technique to derive a data filtering-based two-stage RGLS algorithm. The simulation example indicates the efficiency of the proposed algorithms.
5

Jamal, Alaa, e Raphael Linker. "Genetic Operator-Based Particle Filter Combined with Markov Chain Monte Carlo for Data Assimilation in a Crop Growth Model". Agriculture 10, n. 12 (7 dicembre 2020): 606. http://dx.doi.org/10.3390/agriculture10120606.

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Particle filter has received increasing attention in data assimilation for estimating model states and parameters in cases of non-linear and non-Gaussian dynamic processes. Various modifications of the original particle filter have been suggested in the literature, including integrating particle filter with Markov Chain Monte Carlo (PF-MCMC) and, later, using genetic algorithm evolutionary operators as part of the state updating process. In this work, a modified genetic-based PF-MCMC approach for estimating the states and parameters simultaneously and without assuming Gaussian distribution for priors is presented. The method was tested on two simulation examples on the basis of the crop model AquaCrop-OS. In the first example, the method was compared to a PF-MCMC method in which states and parameters are updated sequentially and genetic operators are used only for state adjustments. The influence of ensemble size, measurement noise, and mutation and crossover parameters were also investigated. Accurate and stable estimations of the model states were obtained in all cases. Parameter estimation was more challenging than state estimation and not all parameters converged to their true value, especially when the parameter value had little influence on the measured variables. Overall, the proposed method showed more accurate and consistent parameter estimation than the PF-MCMC with sequential estimation, which showed highly conservative behavior. The superiority of the proposed method was more pronounced when the ensemble included a large number of particles and the measurement noise was low.
6

Gao, Chao, Guorong Zhao, Jianhua Lu e Shuang Pan. "Decentralized state estimation for networked spatial-navigation systems with mixed time-delays and quantized complementary measurements: The moving horizon case". Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 232, n. 11 (8 giugno 2017): 2160–77. http://dx.doi.org/10.1177/0954410017712277.

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In this paper, the navigational state estimation problem is investigated for a class of networked spatial-navigation systems with quantization effects, mixed time-delays, and network-based observations (i.e. complementary measurements and regional estimations). A decentralized moving horizon estimation approach, featuring complementary reorganization and recursive procedure, is proposed to tackle this problem. First, through the proposed reorganized scheme, a random delayed system with complementary observations is reconstructed into an equivalent delay-free one without dimensional augment. Second, with this equivalent system, a robust moving horizon estimation scheme is presented as a uniform estimator for the navigational states. Third, for the demand of real-time estimate, the recursive form of decentralized moving horizon estimation approach is developed. Furthermore, a collective estimation is obtained through the weighted fusion of two parts, i.e. complementary measurements based estimation, and regional estimations directly from the neighbors. The convergence properties of the proposed estimator are also studied. The obtained stability condition implicitly establishes a relation between the upper bound of the estimation error and two parameters, i.e. quantization density and delay occur probability. Finally, an application example to networked unmanned aerial vehicles is presented and comparative simulations demonstrate the main features of the proposed method.
7

Zhao, Dengfeng, Haiyang Li, Fang Zhou, Yudong Zhong, Guosheng Zhang, Zhaohui Liu e Junjian Hou. "Research Progress on Data-Driven Methods for Battery States Estimation of Electric Buses". World Electric Vehicle Journal 14, n. 6 (2 giugno 2023): 145. http://dx.doi.org/10.3390/wevj14060145.

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Battery states are very important for the safe and reliable use of new energy vehicles. The estimation of power battery states has become a research hotspot in the development of electric buses and transportation safety management. This paper summarizes the basic workflow of battery states estimation tasks, compares, and analyzes the advantages and disadvantages of three types of data sources for battery states estimation, summarizes the characteristics and research progress of the three main models used for estimating power battery states such as machine learning models, deep learning models, and hybrid models, and prospects the development trend of estimation methods. It can be concluded that there are many data sources used for battery states estimation, and the onboard sensor data under natural driving conditions has the characteristics of objectivity and authenticity, making it the main data source for accurate power battery states estimation; Artificial neural network promotes the rapid development of deep learning methods, and deep learning models are increasingly applied in power battery states estimation, demonstrating advantages in accuracy and robustness; Hybrid models estimate the states of power batteries more accurately and reliably by comprehensively utilizing the characteristics of different types of models, which is an important development trend of battery states estimation methods. Higher accuracy, real-time performance, and robustness are the development goals of power battery states estimation methods.
8

Shaw, David A., Vu C. Dinh e Frederick A. Matsen. "Joint Maximum Likelihood of Phylogeny and Ancestral States Is Not Consistent". Molecular Biology and Evolution 36, n. 10 (23 maggio 2019): 2352–57. http://dx.doi.org/10.1093/molbev/msz128.

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Abstract Maximum likelihood estimation in phylogenetics requires a means of handling unknown ancestral states. Classical maximum likelihood averages over these unknown intermediate states, leading to provably consistent estimation of the topology and continuous model parameters. Recently, a computationally efficient approach has been proposed to jointly maximize over these unknown states and phylogenetic parameters. Although this method of joint maximum likelihood estimation can obtain estimates more quickly, its properties as an estimator are not yet clear. In this article, we show that this method of jointly estimating phylogenetic parameters along with ancestral states is not consistent in general. We find a sizeable region of parameter space that generates data on a four-taxon tree for which this joint method estimates the internal branch length to be exactly zero, even in the limit of infinite-length sequences. More generally, we show that this joint method only estimates branch lengths correctly on a set of measure zero. We show empirically that branch length estimates are systematically biased downward, even for short branches.
9

Abdul Jalil, Nur Raihan, Nur Anisah Mohamed e Rossita Mohamad Yunus. "Estimation in regret-regression using quadratic inference functions with ridge estimator". PLOS ONE 17, n. 7 (21 luglio 2022): e0271542. http://dx.doi.org/10.1371/journal.pone.0271542.

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In this paper, we propose a new estimation method in estimating optimal dynamic treatment regimes. The quadratic inference functions in myopic regret-regression (QIF-MRr) can be used to estimate the parameters of the mean response at each visit, conditional on previous states and actions. Singularity issues may arise during computation when estimating the parameters in ODTR using QIF-MRr due to multicollinearity. Hence, the ridge penalty was introduced in rQIF-MRr to tackle the issues. A simulation study and an application to anticoagulation dataset were conducted to investigate the model’s performance in parameter estimation. The results show that estimations using rQIF-MRr are more efficient than the QIF-MRr.
10

Qin, Yongming, Makoto Kumon e Tomonari Furukawa. "Estimation of a Human-Maneuvered Target Incorporating Human Intention". Sensors 21, n. 16 (6 agosto 2021): 5316. http://dx.doi.org/10.3390/s21165316.

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This paper presents a new approach for estimating the motion state of a target that is maneuvered by an unknown human from observations. To improve the estimation accuracy, the proposed approach associates the recurring motion behaviors with human intentions, and models the association as an intention-pattern model. The human intentions relate to labels of continuous states; the motion patterns characterize the change of continuous states. In the preprocessing, an Interacting Multiple Model (IMM) estimation technique is used to infer the intentions and extract motions, which eventually construct the intention-pattern model. Once the intention-pattern model has been constructed, the proposed approach incorporate the intention-pattern model to estimation using any state estimator including Kalman filter. The proposed approach not only estimates the mean using the human intention more accurately but also updates the covariance using the human intention more precisely. The performance of the proposed approach was investigated through the estimation of a human-maneuvered multirotor. The result of the application has first indicated the effectiveness of the proposed approach for constructing the intention-pattern model. The ability of the proposed approach in state estimation over the conventional technique without intention incorporation has then been demonstrated.

Tesi sul tema "States estimation":

1

Covello, James Anthony. "Nonlinear Bounded-Error Target State Estimation Using Redundant States". Diss., The University of Arizona, 2006. http://hdl.handle.net/10150/195557.

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When the primary measurement sensor is passive in nature--by which we mean that it does not directly measure range or range rate--there are well-documented challenges for target state estimation. Most estimation schemes rely on variations of the Extended Kalman Filter (EKF), which, in certain situations, suffer from divergence and/or covariance collapse. For this and other reasons, we believe that the Kalman filter is fundamentally ill-suited to the problems that are inherent in target state estimation using passive sensors. As an alternative, we propose a bounded-error (or set-membership) approach to the target state estimation problem. Such estimators are nearly as old as the Kalman filter, but have enjoyed much less attention. In this study we develop a practical estimator that bounds the target states, and apply it to the two-dimensional case of a submarine tracking a surface vessel, which is commonly referred to as Target Motion Analysis (TMA). The estimator is robust in the sense that the true target state does not escape the determined bounds; and the estimator is not unduly pessimistic in the sense that the bounds are not wider than the situation dictates. The estimator is--as is the problem itself--nonlinear and geometric in nature. In part, the simplicity of the estimator is maintained by using redundant states to parameterize the target's velocity. These redundant states also simplify the incorporation of other measurements that are frequently available to the system. The estimator's performance is assessed in a series of simulations and the results are analyzed. Extensions of the algorithm are considered.
2

Song, Hui. "Real time feedback control using predictive states estimation". Thesis, University of Ottawa (Canada), 2005. http://hdl.handle.net/10393/27041.

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In this thesis, we present a real time feedback control strategy to optimize the dynamic performance of computer communication network. In previous studies [8-10], feedback delay, arising from communication delay, was shown to degrade system performance. Considering this negative impact of delay, we propose a new control law which predicts, in advance, the traffic and exercises control based on the predicted traffic. In experiments, we apple the token bucket (TB) mechanism to construct a discrete dynamic system model [8-10], in which one multiplexor, linked to all the TBs, multiplexes the conforming traffic that have been policed at TBs. We demonstrate that the improvement of the system performance by presenting the simulation results corresponding to different stochastic traffic models. The experiments and analysis in this thesis provide valuable insight for the network researchers to do traffic optimal control [35].
3

Streff, Michael J. "The estimation of United States Army reenlistment rates". Thesis, Monterey, California. Naval Postgraduate School, 1989. http://hdl.handle.net/10945/25902.

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Lewis, Clayton S. "Evapotranspiration Estimation: A Study of Methods in the Western United States". DigitalCommons@USU, 2016. https://digitalcommons.usu.edu/etd/4683.

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This research focused on estimating evapotranspiration (i.e., the amount of water vaporizing into the atmosphere through processes of surface evaporation and plant transpiration) under both theoretical and actual conditions. There were two study areas involved: one, on a large scale where 704 agriculturally-representative, electronic weather stations were used to evaluate the drivers and calculated reference evapotranspiration of a NASA gridded weather forcing model in the 17 western states in the contiguous U.S.; and two, transpiration of invasive saltcedar (Tamarix sp.) in the floodplain of the lower Colorado River, California, with Bowen ratio, eddy covariance, and groundwater fluxes. In this study, a fire destroyed the saltcedar forest, which allowed comparison of evapotranspiration before and after\ this event Comparison of the input weather parameters showed some variance between the electronic weather stations and the gridded model, but calculated reference evapotranspiration performed well by relying on the better input and more highly weighed variables of air temperature and downward shortwave radiation. Only in the southern portions of California, Arizona, and New Mexico were the evapotranspiration estimates using the gridded dataset not well correlated with the electronic weather stations and not recommended for prediction. Saltcedar evapotranspiration was found to match more recent and conservative estimates for the phreatophyte than what was historically portrayed in the literature. Horizontal advection from the surrounding desert was also observed to affect the riparian energy balance. Annual average total evapotranspiration before a fire varied from 0.60-1.44 meters/year to 0.25-1.00 meters/year post fire.
5

Doyle, Mary Anne. "Youth vs. experience in the enlisted Air Force productivity estimation and policy analysis /". Santa Monica, CA : Rand, 1998. http://books.google.com/books?id=BIvfAAAAMAAJ.

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Dasso, Michael W. "Analysis of the United States Hop Market". DigitalCommons@CalPoly, 2015. https://digitalcommons.calpoly.edu/theses/1419.

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Hops are one of the four main ingredients used to produce beer. Many studies have been done to analyze the science behind growing and harvesting hops, creating hop hybrids, and how to brew beer with hops. However, there has been little research done revolving around the economic demand and supply model of the hop market. The objectives of this study are to create an econometric model of supply and demand of hops in the United States from 1981 to 2012, and to identify important exogenous variables that explain the supply and demand of hops using the two-stage least squares (2SLS) method of analysis. Using the 2SLS method, the demand model yielded that the US beer production variable is significant at the 10 percent level. For every 1 percent change in US beer production, there will be a 6.25 percent change in quantity of hops demanded in the same direction. The supply model showed that US acreage is significant at the 1 percent level. For every 1 percent change in US acreage, there will be a 0.889 percent change in quantity of hops supplied in the same direction. The implications of this study are viewed in relation to both producers and consumers.
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Al-Rawahy, Khalid Hilal. "Embodied consumption of U.S. copper and sulfur: Implications for intensity of use estimation and forecasting". Diss., The University of Arizona, 1990. http://hdl.handle.net/10150/185277.

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Domestic mineral consumption is defined as a net sum of apparent consumption plus embodied mineral contained in net imported goods. The U.S. is a net importer of copper-containing products, such as automobiles, electrical products, and construction and industrial machinery. Embodied copper which is contained in net imports of these products constitute part of domestic copper consumption. On the other hand, the U.S. is a net exporter of sulfur-using/embodying products, such as fertilizers and grains. The sulfur which is contained/employed in manufacturing exported products is not actually part of domestic sulfur consumption. Net embodied U.S. imports (exports) of copper (sulfur) are estimated. For copper, it is shown that domestic U.S. consumption is understated and increasing, intensity of use is constant rather than decreasing, and, in general, forecast increases in domestic consumption of copper are due mainly to embodied copper imports. For sulfur, it is shown that domestic consumption is overstated and declining; domestic intensity of use is also declining. The domestic copper and sulfur industries will be differentially impacted as a result of this increased reliance on overseas markets.
8

Iossifov, Plamen K. "Estimation of United States money demand functions using longitudinal family-level data". Access to citation, abstract and download form provided by ProQuest Information and Learning Company; downloadable PDF file 192Mb, 133 p, 2005. http://wwwlib.umi.com/dissertations/fullcit/3181862.

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Gursoy, Gonenc. "Neural Network Based Online Estimation Of Maneuvering Steady States And Control Limits". Master's thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/12612147/index.pdf.

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This thesis concerns the design and development of neural network based predictive algorithms to predict approaching aircraft limits. Therefore, approximate dynamics of flight envelope parameters such as angle of attack and load factor are constructed using neural network augmented dynamic models. Then, constructed models are used to predict steady state responses. By inverting the models and solving for critical controls at the known envelope limits, critical control inputs are calculated as well. The performance of the predictor algorithm is then evaluated with a different neural network online adaptation law which uses a stack of recorded data. It is shown that using a stack of recorded data online, constructed models become much more representative of limit parameter dynamics compared to adaptation using instantaneous measured data only. The benefits of recording data online and using it for weight adaptation are presented in the scope of dynamic trim and control limit predictions.
10

Happ, Christof J. [Verfasser]. "Adaptive and Non-Adaptive Estimation of Discrete Quantum States / Christof J. Happ". München : Verlag Dr. Hut, 2013. http://d-nb.info/104287820X/34.

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Libri sul tema "States estimation":

1

Streff, Michael J. The estimation of United States Army reenlistment rates. Monterey, Calif: Naval Postgraduate School, 1989.

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2

United States. Bureau of the Census. Population Division, a cura di. Postcensal population estimates: States, counties, and places. Washington, D.C: U.S. Dept. of Commerce, Economics and Statistics Administration, Bureau of the Census, 1993.

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Long, John F. Postcensal population estimates: States, counties, and places. Washington, D.C: U.S. Dept. of Commerce, Economics and Statistics Administration, Bureau of the Census, 1993.

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United States. Bureau of the Census. Population Division., a cura di. Postcensal population estimates: States, counties, and places. Washington, D.C: U.S. Dept. of Commerce, Economics and Statistics Administration, Bureau of the Census, 1993.

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Kaplan, Jonathan D. Army Research Institute Validation-Estimation System (ARIVES) user's manual. Alexandria, Va: U.S. Army Research Institute for the Behavioral and Social Sciences, 1989.

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Pratt, Shannon P. Cost of capital: Estimation and applications. 2a ed. Hoboken, N.J: John Wiley & Sons, 2002.

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Pratt, Shannon P. Cost of capital: Estimation and applications. New York: J. Wiley, 1998.

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David, Koffman, United States. Federal Transit Administration., Transit Cooperative Research Program, Transit Development Corporation e National Research Council (U.S.). Transportation Research Board., a cura di. Improving ADA complementary paratransit demand estimation. Washington, D.C: Transportation Research Board, 2007.

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Atack, Jeremy. Estimation of economies of scale in nineteenth century United States manufacturing. New York: Garland Pub., 1985.

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Causey, Beverly D. Indirect state-level estimation for the private school survey. Washington, DC: National Center for Education Statistics, 1999.

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Capitoli di libri sul tema "States estimation":

1

Bergou, János A., Ulrike Herzog e Mark Hillery. "11 Discrimination of Quantum States". In Quantum State Estimation, 417–65. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-44481-7_11.

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Imine, Hocine, Leonid Fridman, Hassan Shraim e Mohamed Djemai. "States and Parameters Estimation". In Sliding Mode Based Analysis and Identification of Vehicle Dynamics, 61–81. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22224-5_4.

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Fuchs, Christopher A., e Rüdiger Schack. "5 Unknown Quantum States and Operations,a Bayesian View". In Quantum State Estimation, 147–87. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-44481-7_5.

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Chefles, Anthony. "12 Quantum States: Discrimination and Classical Information Transmission.A Review of Experimental Progress". In Quantum State Estimation, 467–511. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-44481-7_12.

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Zhang, Mei Miranda. "Estimation of Shipping Cost". In Competitiveness in United States Grain Exports, 53–100. New York: Routledge, 2021. http://dx.doi.org/10.4324/9781003249153-3.

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Ji, Chuanshu. "Some estimation problems for Gibbs states". In Institute of Mathematical Statistics Lecture Notes - Monograph Series, 130–37. Hayward, CA: Institute of Mathematical Statistics, 1991. http://dx.doi.org/10.1214/lnms/1215460497.

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Harper, Ronald M. "Forebrain Mechanisms Related to Respiratory Patterning During Sleep-Waking States". In Modeling and Parameter Estimation in Respiratory Control, 147–51. Boston, MA: Springer US, 1989. http://dx.doi.org/10.1007/978-1-4613-0621-4_15.

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Shamsi, Mohammad Haris, Hannan Ahmad Khan e Mohammed Aslam Husain. "Accurate Equivalent Circuit Model for Battery States Estimation". In Lecture Notes in Electrical Engineering, 1073–85. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-6772-4_93.

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Zhao, Jin, Rongchen Zhao e Feng He. "Vehicle Lateral States Estimation Using Kalman-Bucy Filter". In Lecture Notes in Electrical Engineering, 227–35. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33795-6_19.

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Shim, Eunha, e Carlos Castillo-Chavez. "The Epidemiological Impact of Rotavirus Vaccination Programs in the United States and Mexico". In Mathematical and Statistical Estimation Approaches in Epidemiology, 303–23. Dordrecht: Springer Netherlands, 2009. http://dx.doi.org/10.1007/978-90-481-2313-1_12.

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Atti di convegni sul tema "States estimation":

1

Nohara, Saki, Ryo Okamoto, Akio Fujiwara e Shigeki Takeuchi. "Adaptive quantum state estimation for dynamic quantum states". In 2017 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC). IEEE, 2017. http://dx.doi.org/10.1109/cleoe-eqec.2017.8087436.

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Kak, Subhash, Pramode Verma e Greg MacDonald. "Cryptography and system state estimation using polarization states". In SPIE Optical Engineering + Applications, a cura di Chandrasekhar Roychoudhuri, Andrei Yu Khrennikov e Al F. Kracklauer. SPIE, 2011. http://dx.doi.org/10.1117/12.893659.

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Oyama, Satoshi, Minako Iefuji, Ryo Okamoto, Koichi Yamagata, Akio Fujiwara e Shigeki Takeuchi. "Adaptive quantum state estimation of mixed states using photons". In 2013 Conference on Lasers and Electro-Optics Pacific Rim (CLEO-PR). IEEE, 2013. http://dx.doi.org/10.1109/cleopr.2013.6600601.

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Bogdanov, Yu I. "Quantum states estimation: root approach". In SPIE Proceedings, a cura di Kamil A. Valiev e Alexander A. Orlikovsky. SPIE, 2004. http://dx.doi.org/10.1117/12.562729.

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5

Samanta, B., e C. Nataraj. "Estimation of States and Parameters in Chaotic Systems Using Particle Swarm Optimization". In ASME 2009 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/detc2009-87535.

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A study is presented on the application of particle swarm optimization (PSO) for estimation of states and parameters in chaotic systems. The parameter estimation is formulated as a nonlinear optimization problem using PSO to minimize the synchronization error for the observable states of the actual system and its mathematical model. The procedure is illustrated using a typical chaotic system of Lorenz equations. Results are presented to study the effects of different observable system states and observation noise on parameter estimation. The effectiveness of different variants of PSO on parameter estimation is also studied. The results show the capability of the proposed PSO based approach in estimating the chaotic system parameters with wide search range (50–200%) and in the presence of observation noise.
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Achicanoy M., Wilson O., e Carlos F. Rodriguez H. "Integration of GPS and Accelerometer Uncertainties to Improve the Estimation of the Pose of Autonomous Vehicles". In ASME 2010 International Mechanical Engineering Congress and Exposition. ASMEDC, 2010. http://dx.doi.org/10.1115/imece2010-40463.

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Uncertainty fusion techniques based on Kalman filtering are commonly used to provide a better estimation of the state of a system. A comparison between three different methods to combine the sensor information in order to improve the estimation of the pose of an autonomous vehicle is presented. Two sensors and their uncertainty models are used to measure the observables states of a process: a Global Positioning System (GPS) and an accelerometer. Given that GPS has low sampling rate and the uncertainty of the position, calculated by double integration from the accelerometer signal, increases with time, first a resetting of the estimator based on accelerometer by the GPS measurement is done. Next, a second method makes the fusion of both sensor uncertainties to calculate the estimation. Finally, a double estimation is done, one for each sensor, and a estimated state is calculated joining the individual estimations. These methods are explained by a case study of a guided bomb.
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Mohammadi, Hanieh, Gholamreza Khademi, Dan Simon e Hanz Richter. "State Estimation of an Advanced Rowing Machine Using Optimized Kalman Filtering". In ASME 2017 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/dscc2017-5319.

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This research addresses the problem of state estimation of an advanced rowing machine with energy regeneration. It is assumed that the states of the system, which are position, velocity, and capacitor charge, are measurable. The user force input to the system can be measured by load cells. It is shown that the need for load cells can be eliminated by estimating the force with an unknown-input Kalman filter. The estimated states and the unknown user force input are passed to the controller of the system, which is either an inversion-based controller or a semi-active impedance controller. Two friction models are considered for this system: Coulomb friction, and LuGre friction. The Kalman gains are tuned using an evolutionary algorithm to minimize the standard deviation of the estimation error. The results verify the effectiveness of the proposed approach for simultaneous estimation of the states and the input force. The standard deviation of the state estimation errors are only 10% of their measurement noise. The standard deviation of the input force estimation error is 0.1 N when using an optimized Kalman gain, which is only 25% of the value obtained when using manually tuned gains.
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Funfgeld, Sebastian, Marc Holzapfel, Michael Frey e Frank Gauterin. "Driver state estimation for prediction of vehicle states within control systems". In 2016 IEEE Intelligent Vehicles Symposium (IV). IEEE, 2016. http://dx.doi.org/10.1109/ivs.2016.7535571.

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Sampathraghavan, Lakshmi, e Krishnakumar Ramarathnam. "Simultaneous and Iterative Estimation of Vehicle Ride Model States and Parameters". In ASME 2019 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/imece2019-11260.

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Abstract With advancements in vehicle electronics and growing focus on vehicle safety systems, state and parameter estimation has become a remarkable sphere of research. In this study, the vehicle vertical dynamics states and parameters were estimated simultaneously and iteratively with relevant vehicle responses. This was achieved through vehicle tests, designed to excite the corresponding vehicle states. A linear Kalman filter was used for state estimation. Vehicle parameters were obtained as a optimal solution using an optimization algorithm. With the help of multi-DOF vehicle ride model along with real vehicle measurements, the state and parameter estimators work concurrently to obtain the results. A cleat test was performed for a Sports Utility Vehicle (SUV) in IPG CarMaker® and in reality, for evaluation of the proposed framework. The state estimation results showed upto 93% correlation from simulated data and upto 81% correlation from real time measurements. Parameter estimation produced an average error of only 9.1%. This demonstrated the efficacy of the algorithm for use in vehicle systems.
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Huang, Jihua. "Vehicle State Estimation for Rollover Avoidance". In ASME 2008 International Mechanical Engineering Congress and Exposition. ASMEDC, 2008. http://dx.doi.org/10.1115/imece2008-66730.

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To enhance vehicle/road safety, rollover warning and control systems have received considerable research interest in recent years, especially for vehicles with high center of gravity (CG). Accurate and reliable estimates of the relevant vehicle states facilitate the design of such systems. This paper investigates the state estimation for rollover avoidance, in which the relevant states include vehicle roll velocity and roll angle, as well as sideslip velocity and yaw velocity. The main challenge of the design comes from the fact that, under near-rollover situations, vehicle dynamics is complex and nonlinear. Not only vehicle suspension and tires are in their nonlinear region, but also vehicle yaw, sideslip and roll motions are highly coupled. In addition, the estimation needs to deal with sensor biases and sensor nonlinearity under this extreme condition. To address those issues, this paper proposes a vehicle state estimation design that consists of three parts: a sensor pre-filter, an Extended Kalman filter (EKF), and a sideslip velocity estimator. The sensor pre-processor removes sensor biases by utilizing the Recursive Least Square technique with a varying forgetting factor. The EKF is designed based on a linear yaw/sideslip/roll model, and its feedback gains are further scheduled based on vehicle lateral acceleration in order to reduce the effects of increased model inaccuracy as vehicle roll motion becomes more severe. The sideslip velocity estimator adjusts the sideslip velocity estimated by the EKF to extend the estimation to the nonlinear region. Both simulation and vehicle fishhook testing have been used to verify the effectiveness of the design.

Rapporti di organizzazioni sul tema "States estimation":

1

Mayer, J. Estimation of the number of wild pigs found in the United States. Office of Scientific and Technical Information (OSTI), agosto 2014. http://dx.doi.org/10.2172/1169581.

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Coughlin, Cletus C., Joseph V. Terza e Vachira Arromdee. State Characteristics and the Location of Foreign Direct Investment within the United States: Minimum Chi-Square Conditional Logit Estimation. Federal Reserve Bank of St. Louis, 1987. http://dx.doi.org/10.20955/wp.1987.006.

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Byram, Sharyl, e Christine Hackman. High-precision GNSS Orbit, Clock and EOP Estimation at the United States Naval Observatory. Fort Belvoir, VA: Defense Technical Information Center, aprile 2012. http://dx.doi.org/10.21236/ada564787.

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Dudel, Christian, e Julian Schmied. Pension adequacy standards: an empirical estimation strategy and results for the United States and Germany. Rostock: Max Planck Institute for Demographic Research, gennaio 2019. http://dx.doi.org/10.4054/mpidr-wp-2019-003.

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Hunter, Margaret, Jijo K. Mathew, Ed Cox, Matthew Blackwell e Darcy M. Bullock. Estimation of Connected Vehicle Penetration Rate on Indiana Roadways. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317343.

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Over 400 billion passenger vehicle trajectory waypoints are collected each month in the United States. This data creates many new opportunities for agencies to assess operational characteristics of roadways for more agile management of resources. This study compared traffic counts obtained from 24 Indiana Department of Transportation traffic counts stations with counts derived by the vehicle trajectories during the same periods. These stations were geographically distributed throughout Indiana with 13 locations on interstates and 11 locations on state or US roads. A Wednesday and a Saturday in January, August, and September 2020 are analyzed. The results show that the analyzed interstates had an average penetration of 4.3% with a standard deviation of 1.0. The non-interstate roads had an average penetration of 5.0% with a standard deviation of 1.36. These penetration levels suggest that connected vehicle data can provide a valuable data source for developing scalable roadway performance measures. Since all agencies currently have a highway monitoring system using fixed infrastructure, this paper concludes by recommending agencies integrate a connected vehicle penetration monitoring program into their traditional highway count station program to monitor the growing penetration of connected cars and trucks.
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Prasad, Rajiv, Lyle F. Hibler, Andre M. Coleman e Duane L. Ward. Design-Basis Flood Estimation for Site Characterization at Nuclear Power Plants in the United States of America. Office of Scientific and Technical Information (OSTI), novembre 2011. http://dx.doi.org/10.2172/1036933.

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McWilliams, William H., James A. Westfall, Patrick H. Brose, Daniel C. Dey, Mark Hatfield, Katherine Johnson, Kenneth M. Laustsen et al. A regeneration indicator for Forest Inventory and Analysis: history, sampling, estimation, analytics, and potential use in the midwest and northeast United States. Newtown Square, PA: U.S. Department of Agriculture, Forest Service, Northern Research Station, 2015. http://dx.doi.org/10.2737/nrs-gtr-148.

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Brosh, Arieh, David Robertshaw, Yoav Aharoni, Zvi Holzer, Mario Gutman e Amichai Arieli. Estimation of Energy Expenditure of Free Living and Growing Domesticated Ruminants by Heart Rate Measurement. United States Department of Agriculture, aprile 2002. http://dx.doi.org/10.32747/2002.7580685.bard.

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Research objectives were: 1) To study the effect of diet energy density, level of exercise, thermal conditions and reproductive state on cardiovascular function as it relates to oxygen (O2) mobilization. 2) To validate the use of heart rate (HR) to predict energy expenditure (EE) of ruminants, by measuring and calculating the energy balance components at different productive and reproductive states. 3) To validate the use of HR to identify changes in the metabolizable energy (ME) and ME intake (MEI) of grazing ruminants. Background: The development of an effective method for the measurement of EE is essential for understanding the management of both grazing and confined feedlot animals. The use of HR as a method of estimating EE in free-ranging large ruminants has been limited by the availability of suitable field monitoring equipment and by the absence of empirical understanding of the relationship between cardiac function and metabolic rate. Recent developments in microelectronics provide a good opportunity to use small HR devices to monitor free-range animals. The estimation of O2 uptake (VO2) of animals from their HR has to be based upon a consistent relationship between HR and VO2. The question as to whether, or to what extent, feeding level, environmental conditions and reproductive state affect such a relationship is still unanswered. Studies on the basic physiology of O2 mobilization (in USA) and field and feedlot-based investigations (in Israel) covered a , variety of conditions in order to investigate the possibilities of using HR to estimate EE. In USA the physiological studies conducted using animals with implanted flow probes, show that: I) although stroke volume decreases during intense exercise, VO2 per one heart beat per kgBW0.75 (O2 Pulse, O2P) actually increases and measurement of EE by HR and constant O2P may underestimate VO2unless the slope of the regression relating to heart rate and VO2 is also determined, 2) alterations in VO2 associated with the level of feeding and the effects of feeding itself have no effect on O2P, 3) both pregnancy and lactation may increase blood volume, especially lactation; but they have no effect on O2P, 4) ambient temperature in the range of 15 to 25°C in the resting animal has no effect on O2P, and 5) severe heat stress, induced by exercise, elevates body temperature to a sufficient extent that 14% of cardiac output may be required to dissipate the heat generated by exercise rather than for O2 transport. However, this is an unusual situation and its affect on EE estimation in a freely grazing animal, especially when heart rate is monitored over several days, is minor. In Israel three experiments were carried out in the hot summer to define changes in O2P attributable to changes in the time of day or In the heat load. The animals used were lambs and young calves in the growing phase and highly yielding dairy cows. In the growing animals the time of day, or the heat load, affected HR and VO2, but had no effect on O2P. On the other hand, the O2P measured in lactating cows was affected by the heat load; this is similar to the finding in the USA study of sheep. Energy balance trials were conducted to compare MEI recovery by the retained energy (RE) and by EE as measured by HR and O2P. The trial hypothesis was that if HR reliably estimated EE, the MEI proportion to (EE+RE) would not be significantly different from 1.0. Beef cows along a year of their reproductive cycle and growing lambs were used. The MEI recoveries of both trials were not significantly different from 1.0, 1.062+0.026 and 0.957+0.024 respectively. The cows' reproductive state did not affect the O2P, which is similar to the finding in the USA study. Pasture ME content and animal variables such as HR, VO2, O2P and EE of cows on grazing and in confinement were measured throughout three years under twenty-nine combinations of herbage quality and cows' reproductive state. In twelve grazing states, individual faecal output (FO) was measured and MEI was calculated. Regression analyses of the EE and RE dependent on MEI were highly significant (P<0.001). The predicted values of EE at zero intake (78 kcal/kgBW0.75), were similar to those estimated by NRC (1984). The EE at maintenance condition of the grazing cows (EE=MEI, 125 kcal/kgBW0.75) which are in the range of 96.1 to 125.5 as presented by NRC (1996 pp 6-7) for beef cows. Average daily HR and EE were significantly increased by lactation, P<0.001 and P<0.02 respectively. Grazing ME significantly increased HR and EE, P<0.001 and P<0.00l respectively. In contradiction to the finding in confined ewes and cows, the O2P of the grazing cows was significantly affected by the combined treatments (P<0.00l ); this effect was significantly related to the diet ME (P<0.00l ) and consequently to the MEI (P<0.03). Grazing significantly increased O2P compared to confinement. So, when EE of grazing animals during a certain season of the year is estimated using the HR method, the O2P must be re measured whenever grazing ME changes. A high correlation (R2>0.96) of group average EE and of HR dependency on MEI was also found in confined cows, which were fed six different diets and in growing lambs on three diets. In conclusion, the studies conducted in USA and in Israel investigated in depth the physiological mechanisms of cardiovascular and O2 mobilization, and went on to investigate a wide variety of ruminant species, ages, reproductive states, diets ME, time of intake and time of day, and compared these variables under grazing and confinement conditions. From these combined studies we can conclude that EE can be determined from HR measurements during several days, multiplied by O2P measured over a short period of time (10-15 min). The study showed that RE could be determined during the growing phase without slaughtering. In the near future the development microelectronic devices will enable wide use of the HR method to determine EE and energy balance. It will open new scopes of physiological and agricultural research with minimizes strain on animals. The method also has a high potential as a tool for herd management.
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Dejene Mamo, Bekana. The Impact of Intergovernmental Transfers on Fiscal Behaviour of Local Governments in Ethiopia. Institute of Development Studies (IDS), novembre 2020. http://dx.doi.org/10.19088/ictd.2020.001.

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This paper examines the effect of intergovernmental fiscal transfers on the fiscal behaviour of local governments in Ethiopia for the period 2004-2018. The empirical findings suggest that central government grants bolster state-level employment and expenditure. However, grants from the central government to states do not crowd out state-level revenue collection. Hence, this paper argues that fiscal decentralisation in Ethiopia has mostly, at least in theory, taken the form of devolution of the power to tax and spend public money. However, on average state-level revenue can only finance up to 26 per cent of their annual expenditure. As a result, fiscal federalism in Ethiopia appears to be a form of delegation of spending responsibilities. It has to be considered in the context of a decentralised tax system, but with a transfer scheme and political hierarchy. The results are found to be robust to alternative econometric estimation techniques.
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Czaplewski, Raymond L. Complex sample survey estimation in static state-space. Ft. Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, 2010. http://dx.doi.org/10.2737/rmrs-gtr-239.

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