Results 81 to 90 of about 75,448 (316)
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
Wavelet ensemble Kalman filters [PDF]
Proceedings of the 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems, 2011 4 pages, 4 ...
Jonathan D. Beezley +2 more
openaire +2 more sources
On structural controllability in complex networks with periodic switching topologies
Asian Journal of Control, EarlyView.Abstract This paper investigates the structural controllability of complex networks with periodic switching topologies. First, several graph transformations that preserve structural controllability are demonstrated. Based on the n‐walk theory, a criterion is derived that determines structural controllability by analyzing only the joint graph within a ...
Jingrui Hou +3 more
wiley +1 more source
PENAKSIRAN KESENJANGAN OUTPUT INDONESIA: APLIKASI METODE KALMAN FILTER DAN HODRICK-PRESCOTT FILTER
Journal of Indonesian Applied Economics, 2012 This  research will measure  the potential output  in  Indonesia using Kalman-filterand Hodrick-Prescott Filter. The model will  observe  the variations of output  gapand inflation in Indonesia.
Teguh Hadi Priyono
doaj +1 more source
Journal of the Royal Statistical Society Series B: Statistical Methodology, 2000 Summary In treating dynamic systems, sequential Monte Carlo methods use discrete samples to represent a complicated probability distribution and use rejection sampling, importance sampling and weighted resampling to complete the on-line ‘filtering’ task. We propose a special sequential Monte Carlo method, the mixture Kalman filter, which
Chen, Rong, Liu, Jun S.
openaire +2 more sources
Chemistry – A European Journal, EarlyView.Several γ$\gamma$‐belite(010)–water interfaces have been studied by molecular dynamics simulations using a high‐dimensional neural network potential. The structure and reactivity of interfacial water have been analyzed and two types of surface defects could be identified, which indicate the possible existence of a wide range of surface structures ...
Bernadeta Prus, Jörg Behler
wiley +1 more source
Understanding the Kalman Filter: an Object Oriented Programming Perspective. [PDF]
The basic ideals underlying the Kalman filter are outlined in this paper without direct recourse to the complex formulae normally associated with this method. The novel feature of the paper is its reliance on a new algebraic system based on the first two
Snyder, R.D., Forbes, C.S.
core
A hidden Markov model and reinforcement learning‐based strategy for fault‐tolerant control
The Canadian Journal of Chemical Engineering, EarlyView.Abstract This study introduces a data‐driven control strategy integrating hidden Markov models (HMM) and reinforcement learning (RL) to achieve resilient, fault‐tolerant operation against persistent disturbances in nonlinear chemical processes. Called hidden Markov model and reinforcement learning (HMMRL), this strategy is evaluated in two case studies
Tamera Leitao +2 more
wiley +1 more source
Robust adaptive estimators for nonlinear systems
, 2013 This paper is concerned with the development of new adaptive nonlinear estimators which incorporate adaptive estimation techniques for system noise statistics with the robust technique.
R. Katebi +3 more
core +1 more source
Bayesian inverse ensemble forecasting for COVID‐19
Canadian Journal of Statistics, EarlyView.Abstract Variations in strains of COVID‐19 have a significant impact on the rate of surges and on the accuracy of forecasts of the epidemic dynamics. The primary goal for this article is to quantify the effects of varying strains of COVID‐19 on ensemble forecasts of individual “surges.” By modelling the disease dynamics with an SIR model, we solve the ...
Kimberly Kroetch, Don Estep
wiley +1 more source