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A Robust Predictive Control Formulation for Heliogyro Blade Stability
The Generalized Predictive Control (GPC) algorithm provides a framework with which to approach challenging systems of considerable non-linearity. Its...
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Automated Electricity Price Forecast Using Combined Models
AbstractWe investigate the problem of short-term prediction of the free market price for electricity using various types of forecast models. A...
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Big Data and Sustainable Applications for Healthy and Safe Coastal Cities
A huge amount of data is generated by humans on a daily basis but as businesses transform as more digital data is larger, resulting to more complex...
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A Leak Localization Algorithm in Water Distribution Networks Using Probabilistic Leak Representation and Optimal Transport Distance
Leaks in water distribution networks are estimated to account for up to 30% of the total distributed water: the increasing demand, and the...
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Nonlinear Methods
So far, we have exclusively considered model-free and linear models for regression, since (1) the theory is simple(er), (2) (imputation) models are...
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Analysis of Covid-19 Dynamics in Brazil by Recursive State and Parameter Estimations
In this article, the epidemiological dynamics of COVID-19 in Brazil were studied for each federative unit using state and parameter estimations based...
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Improved Maximum Likelihood Estimation of ARMA Models
AbstractIn this paper we propose a new optimization model for maximum likelihood estimation of causal and invertible ARMA models. Through a set of...
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Bond Portfolio Optimization
The identification of bonds as a risk-free asset must be viewed in the context of the deterministic or known nature of its return, provided the...
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Whittle’s Index Based Sensor Scheduling for Multiprocess Systems Under DoS Attacks
In this paper, the authors consider how to design defensive countermeasures against DoS attacks for remote state estimation of multiprocess systems....
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Global dynamic optimization with Hammerstein–Wiener models embedded
Hammerstein–Wiener models constitute a significant class of block-structured dynamic models, as they approximate process nonlinearities on the basis...
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Data-Driven Modeling and Control of Complex Dynamical Systems Arising in Renal Anemia Therapy
This project is based on a mathematical model of erythropoiesis for anemia (Fuertinger, A model of erythropoiesis. PhD thesis, Karl-Franzens...
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Globally optimal scheduling of an electrochemical process via data-driven dynamic modeling and wavelet-based adaptive grid refinement
Electrochemical recovery of succinic acid is an electricity intensive process with storable feeds and products, making its flexible operation...
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Mathematical Modeling of the Propagation of Covid-19 Pandemic Waves in the World
We develop a mathematical model of the coronavirus propagation in different countries (Brazil, India, US, Japan, Israel, Spain, Sweden), in the city...
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Modeling Fluid Flows in Oil Fields Using the Kalman Filter
In this paper, we present a statistical model of the relationship between injection and production wells on an oil field. The model is based on...
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A first look back: model performance under Solvency II
We consider an empirical backtesting for the Solvency Capital Required (SCR) under Solvency II. Based on empirical facts that the Basic own Funds...
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Optimal Control and Stabilization for Itô Systems with Input Delay
The paper considers the linear quadratic regulation (LQR) and stabilization problems for Ito stochastic systems with two input channels of which one...
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A rotation-based branch-and-price approach for the nurse scheduling problem
In this paper, we describe an algorithm for the personalized nurse scheduling problem. We focus on the deterministic counterpart of the specific...
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Semiparametric prediction models for variables related with energy production
In this paper a review of semiparametric models developed throughout the years thanks to an extensive collaboration between the Department of...
