Results 91 to 100 of about 9,274 (303)

Distributed Extended Kalman Filtering for Wastewater Treatment Processes

, 2016
A wastewater treatment plant is a large-scale nonlinear system including a series of biological reactors and a settler. In this work, we propose a distributed state estimation scheme for wastewater treatment processes in the context of extended Kalman ...
Zeng, Jing, Liu, Jinfeng, Zou T(邹涛), Yuan DC(袁德成)   +3 more
core   +1 more source

On Improving the Performance of Kalman Filter in Denoising Oil Palm Hyperspectral Data

Agriculture
A common drawback of denoising methods of images is that all pixels are filtered regardless of the amount of noise affecting them individually. Since the essence of denoising is lowpass filtering, subjecting clean pixels to denoising results in blurring.
Imanurfatiehah Ibrahim, Hamzah Arof, Mohd Izzuddin Anuar, Mohamad Sofian Abu Talip   +3 more
doaj   +1 more source

A Concept of Approximated Densities for Efficient Nonlinear Estimation

EURASIP Journal on Advances in Signal Processing, 2002
This paper presents the theoretical development of a nonlinear adaptive filter based on a concept of filtering by approximated densities (FAD). The most common procedures for nonlinear estimation apply the extended Kalman filter.
Virginie F. Ruiz
doaj   +1 more source

Spatio‐Temporal Dual‐Encoder Transformer for Short‐Term Regional Wind Power Forecasting

Energy Science &Engineering, EarlyView.
ST‐DualFormer separates temporal and spatial encoding to model complex dependencies in regional wind power forecasting. The fused dual‐stream representation enables accurate short‐term regional forecasts from multi‐farm meteorological and historical power data. The method achieved 5.25% nMAE and 7.53% nRMSE for three‐day‐ahead forecasting on real‐world
Jianfeng Che, Bo Wang, Keru Chen, Siqi Yan, Fei Qi   +4 more
wiley   +1 more source

Precision planter monitoring system based on mobile communication network

IET Networks, EarlyView., 2022
Abstract Sowing is an important link in agricultural production and the basis for ensuring high yields and bumper harvests. Agriculture requires precision plows with good performance and stable work. However, the seeding process is in a completely closed state, and the operator relies mainly on experience to judge the operating state and performance of
Bing Li, Jiyun Li
wiley   +1 more source

The Impact of Uncertainty on Forecasting the US Economy

Journal of Forecasting, EarlyView.
ABSTRACT This paper examines the predictive value of uncertainty measures for key macroeconomic indicators across multiple forecast horizons. We evaluate how different uncertainty proxies—economic policy uncertainty (EPU), VIX, geopolitical risk, and measures of macroeconomic and financial uncertainty—enhance forecast accuracy for industrial production,
Angelica Ghiselli
wiley   +1 more source

NONLINEAR FILTERING OF RANDOM SEQUENCES WITH EXTENDED LEAST-SQUARE METHOD 1

Informatika, 2018
For nonlinear random sequences filtering the extended least-square method is proposed. The received suboptimal filter equations include linearization for nonlinear measurement function only.
V. M. Artemiev, A. O. Naumov, L. L. Kokhan   +2 more
doaj  

New methods for the estimation of Takagi-Sugeno model based extended Kalman filter and its applications to optimal control for nonlinear systems

, 2012
This paper describes new approaches to improve the local and global approximation (matching) and modeling capability of Takagi–Sugeno (T-S) fuzzy model. The main aim is obtaining high function approximation accuracy and fast convergence. The main problem
Al-Hadithi, Basil M., Matía Espada, Fernando, Jiménez Avello, Agustín   +2 more
core   +1 more source

DSGE Model Forecasting: Rational Expectations Versus Adaptive Learning

Journal of Forecasting, EarlyView.
ABSTRACT This paper compares within‐sample and out‐of‐sample fit of a DSGE model with rational expectations to a model with adaptive learning. The Galí, Smets, and Wouters model is the chosen laboratory using quarterly real‐time euro area data vintages, covering 2001Q1–2019Q4.
Anders Warne
wiley   +1 more source

Forecasting With Dynamic Factor Models Estimated by Partial Least Squares

Journal of Forecasting, EarlyView.
ABSTRACT Dynamic factor models (DFMs) have found great success in nowcasting and short‐term macroeconomic forecasting when incorporating large sets of predictive information. The factor loadings are typically estimated cross‐sectionally with principal component analysis (PCA) or maximum likelihood (ML), which ignore whether the factors have predictive ...
Samuel Rauhala
wiley   +1 more source