Search Results - "Kocijan, Jus"
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Design of a hybrid mechanistic/Gaussian process model to predict full-scale wastewater treatment plant effluent
Published in Computers & chemical engineering (02-09-2020)“…•Hybrid mechanistic/data-driven model improves the prediction accuracy of wastewater treatment plant model•Serial data-driven model is designed for gap-filling…”
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Input variable selection using machine learning and global sensitivity methods for the control of sludge bulking in a wastewater treatment plant
Published in Computers & chemical engineering (01-11-2021)“…•Sludge bulking is a severe condition in wastewater-treatment-plant operation.•Machine learning helps to find relationships in the process data for bulking…”
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Distributed predictive control based on Gaussian process models
Published in Automatica (Oxford) (01-03-2023)“…A suboptimal approach to distributed NMPC is proposed based on Gaussian process models of the interconnected systems dynamics and taking into account the…”
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Near-infrared spectroscopy of the placenta for monitoring fetal oxygenation during labour
Published in PloS one (16-04-2020)“…Although being the golden standard for intrapartum fetal surveillance, cardiotocography (CTG) has been shown to have poor specificity for detecting fetal…”
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Predictive control of a gas–liquid separation plant based on a Gaussian process model
Published in Computers & chemical engineering (01-01-2007)“…Gaussian process models provide a probabilistic non-parametric modelling approach for black-box identification of non-linear dynamic systems. The Gaussian…”
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Simulation of variational Gaussian process NARX models with GPGPU
Published in ISA transactions (01-03-2021)“…Gaussian processes (GP) regression is a powerful probabilistic tool for modeling nonlinear dynamical systems. The downside of the method is its cubic…”
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Ensembles of Fuzzy Linear Model Trees for the Identification of Multioutput Systems
Published in IEEE transactions on fuzzy systems (01-08-2016)“…We address the task of discrete-time modeling of nonlinear dynamic systems with multiple outputs using measured data. In the area of control engineering, this…”
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Introduction to the special issue on Intelligent Control and Optimisation
Published in Engineering Applications of Artificial Intelligence (01-08-2023)Get full text
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Dynamic System Identification of Underwater Vehicles Using Multi-Output Gaussian Processes
Published in International journal of automation and computing (01-10-2021)“…Non-parametric system identification with Gaussian processes for underwater vehicles is explored in this research with the purpose of modelling autonomous…”
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Data-driven method for the improving forecasts of local weather dynamics
Published in Engineering applications of artificial intelligence (01-10-2021)“…This paper describes the modeling approach for lower atmosphere dynamics in a selected location. The purpose of this model is to provide short-term and…”
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Evolving Gaussian process models for prediction of ozone concentration in the air
Published in Simulation modelling practice and theory (01-04-2013)“…Ozone is one of the main air pollutants with harmful influence to human health. Therefore, predicting the ozone concentration and informing the population when…”
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Surrogate modelling for the forecast of Seveso-type atmospheric pollutant dispersion
Published in Stochastic environmental research and risk assessment (2023)“…This paper presents a framework for the development of a computationally-efficient surrogate model for air pollution dispersion. Numerical simulation of air…”
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Surrogate tree ensemble model representing 2D population doses over complex terrain in the event of a radiological release into the air
Published in Progress in nuclear energy (New series) (01-04-2023)“…Atmospheric dispersion models predict the dispersion of harmful substances in case of accidents at industrial facilities and nuclear power plants (NPPs)…”
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Equation Discovery for Nonlinear System Identification
Published in IEEE access (2020)“…Equation discovery methods enable modelers to combine domain-specific knowledge and system identification to construct models most suitable for a selected…”
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Sequencing batch-reactor control using Gaussian-process models
Published in Bioresource technology (01-06-2013)“…•A novel framework for the optimisation of phases duration in the SBR operation.•Signal smoothing and the transitions recognition are done within the same…”
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Introduction to Dependence Relations and Their Links to Algebraic Hyperstructures
Published in Mathematics (Basel) (01-10-2019)“…The aim of this paper is to study, from an algebraic point of view, the properties of interdependencies between sets of elements (i.e., pieces of secrets,…”
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Explicit stochastic predictive control of combustion plants based on Gaussian process models
Published in Automatica (Oxford) (01-06-2008)“…Energy production is one of the largest sources of air pollution. A feasible method to reduce the harmful flue gases emissions and to increase the efficiency…”
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On-line algorithm for ground-level ozone prediction with a mobile station
Published in Atmospheric environment (1994) (01-04-2016)“…It is important to be able to predict high concentrations of tropospheric ozone and to inform the population about any violations of air-quality standards, as…”
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Multi-criteria analyses of wastewater treatment bio-processes under an uncertainty and a multiplicity of steady states
Published in Water research (Oxford) (15-11-2012)“…This paper presents a multi-criteria evaluation methodology for determining the operating strategies for bio-chemical, wastewater treatment plants based on a…”
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Improving wind vector predictions for modelling of atmospheric dispersion during Seveso-type accidents
Published in Atmospheric pollution research (01-02-2021)“…In case of a major accident involving airborne emissions of harmful gases, a temporary portable meteorological station may be used to improve atmospheric…”
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