Results 51 to 60 of about 94,605 (282)
Volatility estimation for COVID-19 daily rates using Kalman filtering technique
Results in Physics, 2021 This paper discusses the use of stochastic modeling in the prognosis of Corona Virus-Infected Disease 2019 (COVID-19) cases. COVID-19 is a new disease that is highly infectious and dangerous.
Md Al Masum Bhuiyan +3 more
doaj +1 more source
Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.It is a fact that slippage causes tracking errors in both longitudinal and lateral directions which results to have less travel distance in tracking a reference trajectory. Less travel distance means having energy loss of the battery and carrying loads less than planned.
Gokhan Bayar +2 more
wiley +1 more source
Considering spatiotemporal evolutionary information in dynamic multi‐objective optimisation
CAAI Transactions on Intelligence Technology, EarlyView., 2023 Abstract Preserving population diversity and providing knowledge, which are two core tasks in the dynamic multi‐objective optimisation (DMO), are challenging since the sampling space is time‐ and space‐varying. Therefore, the spatiotemporal property of evolutionary information needs to be considered in the DMO.
Qinqin Fan +3 more
wiley +1 more source
A parallel Kalman filter via the square root Kalman filtering [PDF]
, 1993 A parallel algorithm for Kalman filtering with contaminated observations is developed. Theı parallel implementation is based on the square root version of the Kalman filter (see [3]).
Cipra, Tomas, Romera, Rosario
core +4 more sources
An Adaptive Unscented Kalman Filtering Algorithm for MEMS/GPS Integrated Navigation Systems
Journal of Applied Mathematics, 2014 MEMS/GPS integrated navigation system has been widely used for land-vehicle navigation. This system exhibits large errors because of its nonlinear model and uncertain noise statistic characteristics.
Jianhua Cheng +4 more
doaj +1 more source
Target tracking in the recommender space: Toward a new recommender system based on Kalman filtering [PDF]
, 2010 In this paper, we propose a new approach for recommender systems based on target tracking by Kalman filtering. We assume that users and their seen resources are vectors in the multidimensional space of the categories of the resources. Knowing this space,
Bernier, Cédric +2 more
core +6 more sources
Advanced Intelligent Systems, EarlyView.This study introduces a real‐time light detection and ranging‐camera fusion framework for vehicle detection and tracking. Using a Gaussian mixture model‐based association and improved affinity metrics, the method enhances tracking reliability in dynamic conditions.
Muhammad Adeel Altaf, Min Young Kim
wiley +1 more source
A Neuron-Based Kalman Filter with Nonlinear Autoregressive Model
Sensors, 2020 The control effect of various intelligent terminals is affected by the data sensing precision. The filtering method has been the typical soft computing method used to promote the sensing level. Due to the difficult recognition of the practical system and
Yu-ting Bai +4 more
doaj +1 more source
Gaussian Filtering for Simultaneously Occurring Delayed and Missing Measurements
IEEE Access, 2022 Approximate filtering algorithms in nonlinear systems assume Gaussian prior and predictive density and remain popular due to ease of implementation as well as acceptable performance. However, these algorithms are restricted by two major assumptions: they
Amit Kumar Naik +4 more
doaj +1 more source
Advanced Intelligent Systems, EarlyView.This paper presents a degeneracy‐aware light detection and ranging (LiDAR)‐inertial framework that enhances LiDAR simultaneous localization and mapping performance in challenging environments. The proposed system integrates a dual‐layer robust odometry frontend with a Scan‐Context‐based loop‐closure detection backend.
Haoming Yang +4 more
wiley +1 more source