Log in

Relevant bibliographies by topics / Hybrid estimation model-based / Journal articles

To see the other types of publications on this topic, follow the link: Hybrid estimation model-based.

Journal articles on the topic 'Hybrid estimation model-based'

Author: Grafiati

Published: 5 June 2025

Last updated: 1 August 2025

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the top 50 journal articles for your research on the topic 'Hybrid estimation model-based.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.

1

Zhang, C., H. Xue, G. Dong, H. Jing, and S. He. "RUNOFF ESTIMATION BASED ON HYBRID-PHYSICS-DATA MODEL." ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences V-3-2022 (May 17, 2022): 347–52. http://dx.doi.org/10.5194/isprs-annals-v-3-2022-347-2022.

Full text

Abstract:

Abstract. Runoff estimations play an important role in water resource planning and management. Existing hydrological models can be divided into physical models and data-driven models. Although the physical model contains certain physical knowledge and can be well generalized to new scenarios, the application of physical models is limited by the high professional knowledge requirements, difficulty in obtaining data and high computational costs. The data-driven model can fit the observed data well, but the estimation may not be physically consistent. In this letter, we propose a hybrid physical

APA, Harvard, Vancouver, ISO, and other styles

2

Demir, Ridvan, and Murat Barut. "Novel hybrid estimator based on model reference adaptive system and extended Kalman filter for speed-sensorless induction motor control." Transactions of the Institute of Measurement and Control 40, no. 13 (2017): 3884–98. http://dx.doi.org/10.1177/0142331217734631.

Full text

Abstract:

This paper presents a novel hybrid estimator consisting of an extended Kalman filter (EKF) and an active power-based model reference adaptive system (AP-MRAS) in order to solve simultaneous estimation problems of the variations in stator resistance ([Formula: see text]) and rotor resistance ([Formula: see text]) for speed-sensorless induction motor control. The EKF simultaneously estimates the stator stationary axis components ([Formula: see text] and [Formula: see text]) of stator currents, the stator stationary axis components ([Formula: see text] and [Formula: see text]) of stator fluxes, r

APA, Harvard, Vancouver, ISO, and other styles

3

Carius, L., J. Pohlodek, B. Morabito, et al. "Model-based State Estimation Based on Hybrid Cybernetic Models." IFAC-PapersOnLine 51, no. 18 (2018): 197–202. http://dx.doi.org/10.1016/j.ifacol.2018.09.299.

Full text

APA, Harvard, Vancouver, ISO, and other styles

4

Bretas, Arturo S., Newton G. Bretas, Julio A. D. Massignan, and João B. A. London Junior. "Hybrid Physics-Based Adaptive Kalman Filter State Estimation Framework." Energies 14, no. 20 (2021): 6787. http://dx.doi.org/10.3390/en14206787.

Full text

Abstract:

State-of-the art physics-model based dynamic state estimation generally relies on the assumption that the system’s transition matrix is always correct, the one that relates the states in two different time instants, which might not hold always on real-life applications. Further, while making such assumptions, state-of-the-art dynamic state estimation models become unable to discriminate among different types of anomalies, as measurement gross errors and sudden load changes, and thus automatically leads the state estimator framework to inaccuracy. Towards the solution of this important challeng

APA, Harvard, Vancouver, ISO, and other styles

5

Liu, Jun, Julian Koch, Simon Stisen, Lars Troldborg, and Raphael J. M. Schneider. "A national-scale hybrid model for enhanced streamflow estimation – consolidating a physically based hydrological model with long short-term memory (LSTM) networks." Hydrology and Earth System Sciences 28, no. 13 (2024): 2871–93. http://dx.doi.org/10.5194/hess-28-2871-2024.

Full text

Abstract:

Abstract. Accurate streamflow estimation is essential for effective water resource management and adapting to extreme events in the face of changing climate conditions. Hydrological models have been the conventional approach for streamflow interpolation and extrapolation in time and space for the past few decades. However, their large-scale applications have encountered challenges, including issues related to efficiency, complex parameterization, and constrained performance. Deep learning methods, such as long short-term memory (LSTM) networks, have emerged as a promising and efficient approac

APA, Harvard, Vancouver, ISO, and other styles

6

Li, Xiang, Feihu Xue, Jianli Ding, et al. "A Hybrid Model Coupling Physical Constraints and Machine Learning to Estimate Daily Evapotranspiration in the Heihe River Basin." Remote Sensing 16, no. 12 (2024): 2143. http://dx.doi.org/10.3390/rs16122143.

Full text

Abstract:

Accurate estimation of surface evapotranspiration (ET) in the Heihe River Basin using remote sensing data is crucial for understanding water dynamics in arid regions. In this paper, by coupling physical constraints and machine learning for hybrid modeling, we develop a hybrid model based on surface conductance optimization. A hybrid modeling algorithm, two physical process-based ET algorithms (Penman–Monteith-based and Priestley–Taylor-based ET algorithms), and three pure machine learning algorithms (Random Forest, Extreme Gradient Boosting, and K Nearest Neighbors) are comparatively analyzed

APA, Harvard, Vancouver, ISO, and other styles

7

Zheng, Yan Ping, Tian Tian, and Zhengang He. "Performance Parameter Estimation of the Parallel Hybrid Electric Vehicle." Applied Mechanics and Materials 130-134 (October 2011): 2180–84. http://dx.doi.org/10.4028/www.scientific.net/amm.130-134.2180.

Full text

Abstract:

Based on the theory of HEV (Hybrid Electric Vehicle) and the idea of reverse simulation, the simulation model of the parallel HEV is established in MATLAB and the estimation of the energy efficiency, the power performance and the fuel economy of HEV is achieved, which provides reference for the performance estimation of parallel HEV. At the same time the definition and the estimating method about HEV energy efficiency were mentioned in this paper and the energy efficiency can be achieved by the simulation model. The results of the simulation show that this estimating method has certain practic

APA, Harvard, Vancouver, ISO, and other styles

8

Jung, Hye-Young, Woo-Joo Lee, and Seung Hoe Choi. "Hybrid Fuzzy Regression Analysis Using the F-Transform." Applied Sciences 10, no. 19 (2020): 6726. http://dx.doi.org/10.3390/app10196726.

Full text

Abstract:

This paper proposes a hybrid estimation algorithm for independently estimating the response function for the center and the response function for the spread in fuzzy regression model. The proposed algorithm combines the least absolute deviations estimation with discriminant analysis. In addition, the F-transform is used to convert spreads of the dependent variable into several groups. Two examples show that our method is superior to the existing methods based on the fuzzy regression model that assumes the same function for spread and center.

APA, Harvard, Vancouver, ISO, and other styles

9

Tsai, Tzong-Ru, Yuhlong Lio, Jyun-You Chiang, and Ya-Wen Chang. "Stress–Strength Inference on the Multicomponent Model Based on Generalized Exponential Distributions under Type-I Hybrid Censoring." Mathematics 11, no. 5 (2023): 1249. http://dx.doi.org/10.3390/math11051249.

Full text

Abstract:

The stress–strength analysis is investigated for a multicomponent system, where all strength variables of components follow a generalized exponential distribution and are subject to the generalized exponential distributed stress. The estimation methods of the maximum likelihood and Bayesian are utilized to infer the system reliability. For the Bayesian estimation method, informative and non-informative priors combined with three loss functions are considered. Because the computational difficulty on working posteriors, the Markov chain Monte Carlo method is adopted to obtain the approximation o

APA, Harvard, Vancouver, ISO, and other styles

10

Emeksiz, Cem, and Muhammed Musa Fındık. "Hybrid Estimation Model (CNN-GRU) Based on Deep Learning for Wind Speed Estimation." International Journal of Multidisciplinary Studies and Innovative Technologies 6, no. 1 (2022): 104. http://dx.doi.org/10.36287/ijmsit.6.1.104.

Full text

APA, Harvard, Vancouver, ISO, and other styles

11

Yang, Zhuo, Yiru Inoue, Jian Wan, and Lei Chen. "Channel Parameters Identification Based on IMM Algorithm for Variant Correlation Channel." Mathematical Problems in Engineering 2015 (2015): 1–11. http://dx.doi.org/10.1155/2015/137528.

Full text

Abstract:

In wireless communication systems, correct knowledge of the correlation of a fading channel is essential for channel estimation. Both the reliability of the estimated channel impulse response (CIR) and the adjustment of an adaptive communication system need the accurate correlation information, which is difficult to identify especially when changing. By modeling the fading channel as a hybrid dynamic system, a channel estimation algorithm based on Interacting Multiple Model (IMM) is presented with the consideration of time-variant channel correlation. Applying the IMM algorithm, the proposed c

APA, Harvard, Vancouver, ISO, and other styles

12

Işık, Mehmet Fatih, Fatih Avcil, Ehsan Harirchian, et al. "A Hybrid Artificial Neural Network—Particle Swarm Optimization Algorithm Model for the Determination of Target Displacements in Mid-Rise Regular Reinforced-Concrete Buildings." Sustainability 15, no. 12 (2023): 9715. http://dx.doi.org/10.3390/su15129715.

Full text

Abstract:

The realistic determination of damage estimation and building performance depends on target displacements in performance-based earthquake engineering. In this study, target displacements were obtained by performing pushover analysis for a sample reinforced-concrete building model, taking into account 60 different peak ground accelerations for each of the five different stories. Three different target displacements were obtained for damage estimation, such as damage limitation (DL), significant damage (SD), and near collapse (NC), obtained for each peak ground acceleration for five different nu

APA, Harvard, Vancouver, ISO, and other styles

13

Kumar, B. Anil, Lelitha Vanajakshi, and Shankar C. Subramanian. "A hybrid model based method for bus travel time estimation." Journal of Intelligent Transportation Systems 22, no. 5 (2017): 390–406. http://dx.doi.org/10.1080/15472450.2017.1378102.

Full text

APA, Harvard, Vancouver, ISO, and other styles

14

Skok, Srdjan, Igor Ivankovic, and Zdeslav Cerina. "Hybrid State Estimation Model Based on PMU and SCADA Measurements." IFAC-PapersOnLine 49, no. 27 (2016): 390–94. http://dx.doi.org/10.1016/j.ifacol.2016.10.764.

Full text

APA, Harvard, Vancouver, ISO, and other styles

15

Rienmüller, Theresa, Michael Hofbaur, Louise Travé-Massuyès, and Mehdi Bayoudh. "Mode set focused hybrid estimation." International Journal of Applied Mathematics and Computer Science 23, no. 1 (2013): 131–44. http://dx.doi.org/10.2478/amcs-2013-0011.

Full text

Abstract:

Estimating the state of a hybrid system means accounting for the mode of operation or failure and the current state of the continuously valued entities concurrently. Existing hybrid estimation schemes try to overcome the problem of an exponentially growing number of possible mode-sequence/continuous-state combinations by merging hypotheses and/or deducing likelihood measures to identify tractable sets of the most likely hypotheses. However, they still suffer from unnecessarily high computational costs as the number of possible modes increases. Hybrid diagnosis schemes, on the other hand, estim

APA, Harvard, Vancouver, ISO, and other styles

16

Li, Jing, and Jiaxu Zhang. "Vehicle Sideslip Angle Estimation Based on Hybrid Kalman Filter." Mathematical Problems in Engineering 2016 (2016): 1–10. http://dx.doi.org/10.1155/2016/3269142.

Full text

Abstract:

Vehicle sideslip angle is essential for active safety control systems. This paper presents a new hybrid Kalman filter to estimate vehicle sideslip angle based on the 3-DoF nonlinear vehicle dynamic model combined with Magic Formula tire model. The hybrid Kalman filter is realized by combining square-root cubature Kalman filter (SCKF), which has quick convergence and numerical stability, with square-root cubature based receding horizon Kalman FIR filter (SCRHKF), which has robustness against model uncertainty and temporary noise. Moreover, SCKF and SCRHKF work in parallel, and the estimation ou

APA, Harvard, Vancouver, ISO, and other styles

17

Corona, Piermaria, Lorenzo Fattorini, Sara Franceschi, Gianfranco Scrinzi, and Chiara Torresan. "Estimation of standing wood volume in forest compartments by exploiting airborne laser scanning information: model-based, design-based, and hybrid perspectives." Canadian Journal of Forest Research 44, no. 11 (2014): 1303–11. http://dx.doi.org/10.1139/cjfr-2014-0203.

Full text

Abstract:

Forest compartments are usually delineated according to artificial or natural boundaries and usually include portions of different strata. While volume estimation of each stratum can be performed from field plots located within each stratum, volume estimation in portions of the stratum may be problematic owing to the small number (or even the absence) of plots falling in those portions. If upper canopy heights from airborne laser scanning are available at the pixel level for the whole survey area, these data are used as auxiliary information. A ratio model presuming a proportional relationship

APA, Harvard, Vancouver, ISO, and other styles

18

Chaturvedi, Ankita, Sanjay Kumar Singh, and Umesh Singh. "Statistical Inferences of Type-II Progressively Hybrid Censored Fuzzy Data with Rayleigh Distribution." Austrian Journal of Statistics 47, no. 3 (2018): 40–62. http://dx.doi.org/10.17713/ajs.v47i3.752.

Full text

Abstract:

This article presents the procedures for the estimation of the parameter of Rayleighdistribution based on Type-II progressive hybrid censored fuzzy lifetime data. Classicalas well as the Bayesian procedures for the estimation of unknown model parameters has been developed. The estimators obtained here are Maximum likelihood (ML) estimator, Method of moments (MM) estimator, Computational approach (CA) estimator and Bayes estimator. Highest posterior density (HPD) credible intervals of the unknown parameter are obtained by using Markov Chain Monte Carlo (MCMC) technique. For numerical illustrati

APA, Harvard, Vancouver, ISO, and other styles

19

Tu, Hongbin, Renyu Xu, Rui Chi, and Yuanyuan Peng. "Multiperson Interactive Activity Recognition Based on Interaction Relation Model." Journal of Mathematics 2021 (August 11, 2021): 1–12. http://dx.doi.org/10.1155/2021/5576369.

Full text

Abstract:

Multiperson activity recognition is a pivotal branch as well as a challenging topic of human action recognition research. This paper adopts a hybrid learning model to the spatio-temporal relationship and occlusion relationship among multiple people. Initially, this paper builds up an active multiperson interaction relationship estimation framework model to capture interpersonal spatio-temporal relation. This model incorporates the interaction relationship estimation framework with the multiperson relationship network. On this ground, it automatically learns from the human-computer interaction

APA, Harvard, Vancouver, ISO, and other styles

20

Wang, Zhenpo, Jianyang Wu, Lei Zhang, and Yachao Wang. "Vehicle sideslip angle estimation for a four-wheel-independent-drive electric vehicle based on a hybrid estimator and a moving polynomial Kalman smoother." Proceedings of the Institution of Mechanical Engineers, Part K: Journal of Multi-body Dynamics 233, no. 1 (2018): 125–40. http://dx.doi.org/10.1177/1464419318770923.

Full text

Abstract:

This paper presents a vehicle sideslip angle estimation scheme against noises and outliers in sensor measurements for a four-wheel-independent-drive electric vehicle. The proposed scheme combines a robust unscented Kalman filter estimator based on the 3-DOF vehicle dynamics model and an extended Kalman filter estimator based on the kinematic model to form a hybrid estimator through a weighting factor. The weighting factor can be dynamically adjusted in real time to optimize the overall estimation performance under different driving conditions. The main contributions of this study to the relate

APA, Harvard, Vancouver, ISO, and other styles

21

Tok, Michael, Alexander Glantz, Andreas Krutz, and Thomas Sikora. "Monte-Carlo-Based Parametric Motion Estimation Using a Hybrid Model Approach." IEEE Transactions on Circuits and Systems for Video Technology 23, no. 4 (2013): 607–20. http://dx.doi.org/10.1109/tcsvt.2012.2211173.

Full text

APA, Harvard, Vancouver, ISO, and other styles

22

Yoo, Min Young, Jung Heon Lee, Joo-Ho Choi, Jae Sung Huh, and Woosuk Sung. "State-of-Charge Estimation of Batteries for Hybrid Urban Air Mobility." Aerospace 10, no. 6 (2023): 550. http://dx.doi.org/10.3390/aerospace10060550.

Full text

Abstract:

This paper proposes a framework for accurately estimating the state-of-charge (SOC) and current sensor bias, with the aim of integrating it into urban air mobility (UAM) with hybrid propulsion. Considering the heightened safety concerns in an airborne environment, more reliable state estimation is required, particularly for the UAM that uses a battery as its primary power source. To ensure the suitability of the framework for the UAM, a two-pronged approach is taken. First, realistic test profiles, reflecting actual operational scenarios for the UAM, are used to model the battery and validate

APA, Harvard, Vancouver, ISO, and other styles

23

Utami, Tiani Wahyu, Endang Tri Wahyuni Maharani, and Alwan Fadlurohman. "MODELING DHF IN CENTRAL JAVA USING HYBRID NONPARAMETRIC SPLINE TRUNCATED-FOURIER SERIES APPROACH." BAREKENG: Jurnal Ilmu Matematika dan Terapan 18, no. 3 (2024): 1459–70. http://dx.doi.org/10.30598/barekengvol18iss3pp1459-1470.

Full text

Abstract:

Regression analysis aims to determine the relationship and influence of predictor variables on response variables through regression curve. The problem with nonparametric regression research so far is that it only uses one approach, causing the estimation results to be biased, even though each data sub-pattern has its own suitability depending on the approach method used. Therefore, the hybrid method emerged as a development of nonparametric regression. Hybrid models are models that combine approach methods, with the hope of increasing accuracy in modeling analysis. This research was carried o

APA, Harvard, Vancouver, ISO, and other styles

24

Li, Shuang, Yongxin Lin, Ping Zhu, Liping Jin, Chunsong Bian, and Jiangang Liu. "Combining UAV Multispectral Imaging and PROSAIL Model to Estimate LAI of Potato at Plot Scale." Agriculture 14, no. 12 (2024): 2159. http://dx.doi.org/10.3390/agriculture14122159.

Full text

Abstract:

Accurate and rapid estimation of the leaf area index (LAI) is essential for assessing crop growth and nutritional status, guiding farm management, and providing valuable phenotyping data for plant breeding. Compared to the tedious and time-consuming manual measurements of the LAI, remote sensing has emerged as a valuable tool for rapid and accurate estimation of the LAI; however, the empirical inversion modeling methods face challenges of low efficiency for actual LAI measurements and poor model interpretability. The integration of radiative transfer models (RTMs) can overcome these problems t

APA, Harvard, Vancouver, ISO, and other styles

25

El Oufir, Mohamed Karim, Karem Chokmani, Anas El Alem, and Monique Bernier. "Estimating Snowpack Density from Near-Infrared Spectral Reflectance Using a Hybrid Model." Remote Sensing 13, no. 20 (2021): 4089. http://dx.doi.org/10.3390/rs13204089.

Full text

Abstract:

Improving the estimation of snow density is a key task in current snow research. Characterization of the variability of density in time and space is essential for the estimation of water equivalent, hydroelectric power production, assessment of natural hazards (avalanches, floods, etc.). Hyperspectral imaging is proving to be a promising and reliable tool for monitoring and estimating this physical property. Indeed, the spectral reflectance of snow is partly controlled by changes in its physical properties, particularly in the near-infrared (NIR) part of the spectrum. For this purpose, several

APA, Harvard, Vancouver, ISO, and other styles

26

Sieberg, Philipp Maximilian, and Dieter Schramm. "Ensuring the Reliability of Virtual Sensors Based on Artificial Intelligence within Vehicle Dynamics Control Systems." Sensors 22, no. 9 (2022): 3513. http://dx.doi.org/10.3390/s22093513.

Full text

Abstract:

The use of virtual sensors in vehicles represents a cost-effective alternative to the installation of physical hardware. In addition to physical models resulting from theoretical modeling, artificial intelligence and machine learning approaches are increasingly used, which incorporate experimental modeling. Due to the resulting black-box characteristics, virtual sensors based on artificial intelligence are not fully reliable, which can have fatal consequences in safety-critical applications. Therefore, a hybrid method is presented that safeguards the reliability of artificial intelligence-base

APA, Harvard, Vancouver, ISO, and other styles

27

Lee, Yongkyu, and Jungsoo Lee. "Advancing Stem Volume Estimation Using Multi-Platform LiDAR and Taper Model Integration for Precision Forestry." Remote Sensing 17, no. 5 (2025): 785. https://doi.org/10.3390/rs17050785.

Full text

Abstract:

Stem volume is a critical factor in managing and evaluating forest resources. At present, stem volume is commonly estimated indirectly by constructing a taper model that utilizes sampling, diameter at breast height (DBH), and tree height. However, these estimates are constrained by errors arising from spatial and stand environment variations as well as uncertainties in height measurements. To address these issues, this study aimed to accurately estimate stem volume using light detection and ranging (LiDAR) technology, a key tool in modern precision forestry. LiDAR data were used to build compr

APA, Harvard, Vancouver, ISO, and other styles

28

Minh, Vu Trieu, Nitin Afzulpurkar, and W. M. Wan Muhamad. "Fault Detection and Control of Process Systems." Mathematical Problems in Engineering 2007 (2007): 1–20. http://dx.doi.org/10.1155/2007/80321.

Full text

Abstract:

This paper develops a stochastic hybrid model-based control system that can determine online the optimal control actions, detect faults quickly in the control process, and reconfigure the controller accordingly using interacting multiple-model (IMM) estimator and generalized predictive control (GPC) algorithm. A fault detection and control system consists of two main parts: the first is the fault detector and the second is the controller reconfiguration. This work deals with three main challenging issues: design of fault model set, estimation of stochastic hybrid multiple models, and stochasti

APA, Harvard, Vancouver, ISO, and other styles

29

Hesamian, Gholamreza, Arne Johannssen, and Nataliya Chukhrova. "A Three-Stage Nonparametric Kernel-Based Time Series Model Based on Fuzzy Data." Mathematics 11, no. 13 (2023): 2800. http://dx.doi.org/10.3390/math11132800.

Full text

Abstract:

In this paper, a nonlinear time series model is developed for the case when the underlying time series data are reported by LR fuzzy numbers. To this end, we present a three-stage nonparametric kernel-based estimation procedure for the center as well as the left and right spreads of the unknown nonlinear fuzzy smooth function. In each stage, the nonparametric Nadaraya–Watson estimator is used to evaluate the center and the spreads of the fuzzy smooth function. A hybrid algorithm is proposed to estimate the unknown optimal bandwidths and autoregressive order simultaneously. Various goodness-of-

APA, Harvard, Vancouver, ISO, and other styles

30

ÇETİNER, Halit. "Recurrent Neural Network Based Model Development for Energy Consumption Forecasting." Bitlis Eren Üniversitesi Fen Bilimleri Dergisi 11, no. 3 (2022): 759–69. http://dx.doi.org/10.17798/bitlisfen.1077393.

Full text

Abstract:

The world population is increasing day by day. As a result, limited resources are decreasing day by day. On the other hand, the amount of energy needed is constantly increasing. In this sense, decision makers must accurately estimate the amount of energy that society will require in the coming years and make plans accordingly. These plans are of critical importance for the peace and welfare of society. Based on the energy consumption values of Germany, it is aimed at estimating the energy consumption values with the GRU, LSTM, and proposed hybrid LSTM-GRU methods, which are among the popular R

APA, Harvard, Vancouver, ISO, and other styles

31

Prakash, Gyan. "Pareto Distribution under Hybrid Censoring: Some Estimation." Journal of Modern Applied Statistical Methods 19, no. 1 (2021): 2–17. http://dx.doi.org/10.22237/jmasm/1619481660.

Full text

Abstract:

In the present study, the Pareto model is considered as the model from which observations are to be estimated using a Bayesian approach. Properties of the Bayes estimators for the unknown parameters have studied by using different asymmetric loss functions on hybrid censoring pattern and their risks have compared. The properties of maximum likelihood estimation and approximate confidence length have also been investigated under hybrid censoring. The performances of the procedures are illustrated based on simulated data obtained under the Metropolis-Hastings algorithm and a real data set.

APA, Harvard, Vancouver, ISO, and other styles

32

Zhao, Yu-Xin, Li-Juan Chen, and Yan Ma. "An FEM-Based State Estimation Approach to Nonlinear Hybrid Positioning Systems." Mathematical Problems in Engineering 2013 (2013): 1–10. http://dx.doi.org/10.1155/2013/175425.

Full text

Abstract:

For hybrid positioning systems (HPSs), the estimator design is a crucial and important problem. In this paper, a finite-element-method- (FEM-) based state estimation approach is proposed to HPS. As the weak solution of hybrid stochastic differential model is denoted by the Kolmogorov's forward equation, this paper constructs its interpolating point through the classical fourth-order Runge-Kutta method. Then, it approaches the solution with biquadratic interpolation function to obtain a prior probability density function of the state. A posterior probability density function is gained through B

APA, Harvard, Vancouver, ISO, and other styles

33

Ye, Yuning, and Hanhoon Park. "FusionNet: An End-to-End Hybrid Model for 6D Object Pose Estimation." Electronics 12, no. 19 (2023): 4162. http://dx.doi.org/10.3390/electronics12194162.

Full text

Abstract:

In this study, we propose a hybrid model for Perspective-n-Point (PnP)-based 6D object pose estimation called FusionNet that takes advantage of convolutional neural networks (CNN) and Transformers. CNN is an effective and potential tool for feature extraction, which is considered the most popular architecture. However, CNN has difficulty in capturing long-range dependencies between features, and most CNN-based models for 6D object pose estimation are bulky and heavy. To address these problems, we propose a lighter-weight CNN building block with attention, design a Transformer-based global depe

APA, Harvard, Vancouver, ISO, and other styles

34

Bin Sulong, Ghazali, and M . Randles. "Computer Vision Using Pose Estimation." Wasit Journal of Computer and Mathematics Science 2, no. 1 (2023): 85–92. http://dx.doi.org/10.31185/wjcm.111.

Full text

Abstract:

Pose estimation involves estimating the position and orientation of objects in a 3D space, and it has applications in areas such as robotics, augmented reality, and human-computer interaction. There are several methods for pose estimation, including model-based, feature-based, direct, hybrid, and deep learning-based methods. Each method has its own strengths and weaknesses, and the choice of method depends on the specific requirements of the application, object being estimated, and available data. Advancements in computer vision and machine learning have made it possible to achieve high accura

APA, Harvard, Vancouver, ISO, and other styles

35

Wu, Jianping, Xiaowen Liu, Yaoping Tang, and Hongfei Xu. "Research on Agricultural Drought Risk Measurement Based on Bayes Hybrid Model." Tobacco Regulatory Science 7, no. 5 (2021): 3983–87. http://dx.doi.org/10.18001/trs.7.5.1.172.

Full text

Abstract:

The development of agricultural economy depends to a large extent on the drought. It is necessary to accurately analyze the current drought risk in order to formulate a more reliable drought risk management strategy and reduce the impact of disasters on the development of the agricultural economy. In order to improve the level of drought risk measurement, this paper selects VaR as the measurement tool, and proposes a mixed distribution model research. Use this model to fit the distribution of drought loss rate, and measure the drought risk by estimating VaR. Among them, the mixed distribution

APA, Harvard, Vancouver, ISO, and other styles

36

Luo, Hongmei, Yi Zhou, Lijie Pei, et al. "Method for analysing of wind power wave nature based on kernel density estimation." Journal of Physics: Conference Series 2728, no. 1 (2024): 012031. http://dx.doi.org/10.1088/1742-6596/2728/1/012031.

Full text

Abstract:

Abstract It is beneficial for improving the accuracy of wind power output prediction by analysing and mastering the inherent laws of the fluctuation characteristics of wind power output, guiding the power grid dispatching department to reasonably arrange power generation plans, and improving the economic efficiency of system operation. In order to characterize the probability density distribution of wind power output fluctuation, two adaptive bandwidth kernel density estimation models are established by correcting the fixed bandwidth obtained from the empirical method and unbiased cross-valida

APA, Harvard, Vancouver, ISO, and other styles

37

Klima, André, Thomas Schlesinger, Paul W. Thurner, and Helmut Küchenhoff. "Combining Aggregate Data and Exit Polls for the Estimation of Voter Transitions." Sociological Methods & Research 48, no. 2 (2017): 296–325. http://dx.doi.org/10.1177/0049124117701477.

Full text

Abstract:

Our objective is the estimation of voter transitions between two consecutive parliamentary elections. Usually, such analyses have been based either on individual survey data or on aggregated data. To move beyond these methods and their respective problems, we propose the application of so-called hybrid models, which combine aggregate and individual data. We use a Bayesian approach and extend a multinomial-Dirichlet model proposed in the ecological inference literature. Our new hybrid model has been implemented in the R-package eiwild (= Ecological Inference with individual-level data). Based o

APA, Harvard, Vancouver, ISO, and other styles

38

Jin, Xue-Bo, Ruben Jonhson Robert Jeremiah, Ting-Li Su, Yu-Ting Bai, and Jian-Lei Kong. "The New Trend of State Estimation: From Model-Driven to Hybrid-Driven Methods." Sensors 21, no. 6 (2021): 2085. http://dx.doi.org/10.3390/s21062085.

Full text

Abstract:

State estimation is widely used in various automated systems, including IoT systems, unmanned systems, robots, etc. In traditional state estimation, measurement data are instantaneous and processed in real time. With modern systems’ development, sensors can obtain more and more signals and store them. Therefore, how to use these measurement big data to improve the performance of state estimation has become a hot research issue in this field. This paper reviews the development of state estimation and future development trends. First, we review the model-based state estimation methods, including

APA, Harvard, Vancouver, ISO, and other styles

39

Cai, Rui, and Deng Yin Zhang. "Hybrid Distributed Correlation Noise Model and Parameter Estimation." Applied Mechanics and Materials 752-753 (April 2015): 1110–15. http://dx.doi.org/10.4028/www.scientific.net/amm.752-753.1110.

Full text

Abstract:

In transform domain distributed video coding scheme, we found that there was a certain deviation between Laplacian statistical distribution and the distribution of small and large residual coefficients. To reduce this deviation, this paper proposes a hybrid distribution correlation noise model (HDCNM) based on K-Mediods, which models small coefficients as improved Laplacian distribution while modeling large ones as Cauchy distribution. The parameter estimation algorithm is also given. The experimental results show that the hybrid model proposed in this paper can describe the distribution of re

APA, Harvard, Vancouver, ISO, and other styles

40

Xu, Jun Ling, Li Wei Li, and An Na Jiang. "SOC Estimation on PNGV Model and Hybrid Electric Vehicle." Advanced Materials Research 986-987 (July 2014): 874–77. http://dx.doi.org/10.4028/www.scientific.net/amr.986-987.874.

Full text

Abstract:

Based on PNGV (the Partnership for a New Generation of Vehicles) equivalent battery model, establishing state-space equations, discrediting them and using UKF (Unsvented Kalman Filtering) arithmetic to achieve an exact SOC estimation under the non-linear condition. According to simulation experiment, UKF estimation just has an error rate of less than 6 percent, and has a quite high use value.

APA, Harvard, Vancouver, ISO, and other styles

41

Kong, Daqian, Dekun Yuan, Haojie Li, et al. "Improving the Estimation of Gross Primary Productivity across Global Biomes by Modeling Light Use Efficiency through Machine Learning." Remote Sensing 15, no. 8 (2023): 2086. http://dx.doi.org/10.3390/rs15082086.

Full text

Abstract:

Estimating gross primary productivity (GPP) is important for simulating the subsequent carbon cycle elements and assessing the capacity of terrestrial ecosystems to support the sustainable development of human society. Light use efficiency (LUE) models were widely used to estimate GPP due to their concise model structures. However, quantifying LUEmax (maximum light use efficiency) and representing the responses of photosynthesis to environmental factors are still subject to large uncertainties, which lead to substantial errors in GPP simulations. In this study, we developed a hybrid model base

APA, Harvard, Vancouver, ISO, and other styles

42

Xiao, Jie, William Lee, Jianhui Jiang, and Xuhua Yang. "Circuit reliability estimation based on an iterative PTM model with hybrid coding." Microelectronics Journal 52 (June 2016): 117–23. http://dx.doi.org/10.1016/j.mejo.2016.03.013.

Full text

APA, Harvard, Vancouver, ISO, and other styles

43

Vikraman, Vignaraj, and S. Srinivasan. "AGS: A Precise and Efficient AI Based Hybrid Software Effort Estimation Model." International Journal of Business Intelligence and Data Mining 1, no. 1 (2019): 1. http://dx.doi.org/10.1504/ijbidm.2019.10013150.

Full text

APA, Harvard, Vancouver, ISO, and other styles

44

Ananth, V. Vignaraj, and S. Srinivasan. "AGS: a precise and efficient AI-based hybrid software effort estimation model." International Journal of Business Intelligence and Data Mining 18, no. 1 (2021): 1. http://dx.doi.org/10.1504/ijbidm.2021.111739.

Full text

APA, Harvard, Vancouver, ISO, and other styles

45

Vellayikot, Shijoh, and M. V. Vaidyan. "ANN Approach for State Estimation of Hybrid Systems and Its Experimental Validation." Mathematical Problems in Engineering 2015 (2015): 1–13. http://dx.doi.org/10.1155/2015/382324.

Full text

Abstract:

A novel artificial neural network based state estimator has been proposed to ensure the robustness in the state estimation of autonomous switching hybrid systems under various uncertainties. Taking the autonomous switching three-tank system as benchmark hybrid model working under various additive and multiplicative uncertainties such as process noise, measurement error, process–model parameter variation, initial state mismatch, and hand valve faults, real-time performance evaluation by the comparison of it with other state estimators such as extended Kalman filter and unscented Kalman Filter w

APA, Harvard, Vancouver, ISO, and other styles

46

Lee, Hyunjoon, Min Young Yoo, Joo-Ho Choi, Woosuk Sung, and Jae Sung Heo. "State-of-Charge and State-of-Health Estimation for Li-Ion Batteries of Hybrid Electric Vehicles under Deep Degradation." PHM Society European Conference 8, no. 1 (2024): 10. http://dx.doi.org/10.36001/phme.2024.v8i1.4032.

Full text

Abstract:

In recent industry, hybrid vehicles are gaining more recognition as a practical means for future transportation due to the longer distance, reduced charging time, and less charging stations dependency. The batteries in the hybrid vehicles, however, undergo more complex operation of charge depleting and sustaining modes alternately, which may need more accurate battery state estimation. In this study, a model based method is explored for the Li-ion batteries in the hybrid electric vehicles to estimate State-of Charge (SOC) and State-of-Health (SOH) accurately. While there have been widespread s

APA, Harvard, Vancouver, ISO, and other styles

47

Li, Shun, and Xinxiu Zhou. "Sensorless Energy Conservation Control for Permanent Magnet Synchronous Motors Based on a Novel Hybrid Observer Applied in Coal Conveyer Systems." Energies 11, no. 10 (2018): 2554. http://dx.doi.org/10.3390/en11102554.

Full text

Abstract:

A large number of permanent magnet synchronous motors (PMSMs) are used to drive coal conveyer belts in coal enterprises. Sensorless energy conservation control has important economic value for these enterprises. The key problem of sensorless energy conservation control for PMSMs is how to decompose the stator current through estimating the rotor position and speed accurately. Then a double closed loop control for stator current and speed is formed to make the stator current drive the motor as an entire torque current. In this paper, the proposed startup estimation algorithm can utilize the cur

APA, Harvard, Vancouver, ISO, and other styles

48

Hu, Tao, Yuman Sun, Weiwei Jia, Dandan Li, Maosheng Zou, and Mengku Zhang. "Study on the Estimation of Forest Volume Based on Multi-Source Data." Sensors 21, no. 23 (2021): 7796. http://dx.doi.org/10.3390/s21237796.

Full text

Abstract:

We performed a comparative analysis of the prediction accuracy of machine learning methods and ordinary Kriging (OK) hybrid methods for forest volume models based on multi-source remote sensing data combined with ground survey data. Taking Larix olgensis, Pinus koraiensis, and Pinus sylvestris plantations in Mengjiagang forest farms as the research object, based on the Chinese Academy of Forestry LiDAR, charge-coupled device, and hyperspectral (CAF-LiTCHy) integrated system, we extracted the visible vegetation index, texture features, terrain factors, and point cloud feature variables, respect

APA, Harvard, Vancouver, ISO, and other styles

49

Yu, Ming, Haotian Lu, Hai Wang, Chenyu Xiao, Dun Lan, and Junjie Chen. "Computational Intelligence-Based Prognosis for Hybrid Mechatronic System Using Improved Wiener Process." Actuators 10, no. 9 (2021): 213. http://dx.doi.org/10.3390/act10090213.

Full text

Abstract:

In this article, a fast krill herd algorithm is developed for prognosis of hybrid mechatronic system using the improved Wiener degradation process. First, the diagnostic hybrid bond graph is used to model the hybrid mechatronic system and derive global analytical redundancy relations. Based on the global analytical redundancy relations, the fault signature matrix and mode change signature matrix for fault and mode change isolation can be obtained. Second, in order to determine the true faults from the suspected fault candidates after fault isolation, a fault estimation method based on adaptive

APA, Harvard, Vancouver, ISO, and other styles

50

Takahashi, Tomoroh, and Gia Khanh Tran. "Research on Advancing Radio Wave Source Localization Technology Through UAV Path Optimization." Future Internet 17, no. 5 (2025): 224. https://doi.org/10.3390/fi17050224.

Full text

Abstract:

With an increasing number of illegal radio stations, connected cars, and IoT devices, high-accuracy radio source localization techniques are in demand. Traditional methods such as GPS positioning and triangulation suffer from accuracy degradation in NLOS (non-line-of-sight) environments due to obstructions. In contrast, the fingerprinting method builds a database of pre-collected radio information and estimates the source location via pattern matching, maintaining relatively high accuracy in NLOS environments. This study aims to improve the accuracy of fingerprinting-based localization by opti

APA, Harvard, Vancouver, ISO, and other styles

We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!