Results 101 to 110 of about 10,435 (267)
Risk‐aware safe reinforcement learning for control of stochastic linear systems
Abstract This paper presents a risk‐aware safe reinforcement learning (RL) control design for stochastic discrete‐time linear systems. Rather than using a safety certifier to myopically intervene with the RL controller, a risk‐informed safe controller is also learned besides the RL controller, and the RL and safe controllers are combined together ...
Babak Esmaeili +2 more
wiley +1 more source
Abstract The linear‐quadratic regulator (LQR) problem of optimal control of an uncertain discrete‐time linear system (DTLS) is revisited in this paper from the perspective of Tikhonov regularization. We show that an optimally chosen regularization parameter reduces, compared to the classical LQR, the values of a scalar error function, as well as the ...
Fernando Pazos, Amit Bhaya
wiley +1 more source
ABSTRACT The necessary environmental transition involves a substantial challenge for micro, small, and medium‐sized enterprises (MSMEs). Moreover, in the Ibero‐American context, it is even more challenging. Our study aims to shed light on the scarce and inconclusive evidence in this regard, analyzing the influence of digitalization, given its inclusion
José Antonio Clemente‐Almendros +2 more
wiley +1 more source
ABSTRACT This study examines the role of managerial ability in driving environmental performance and overall environmental, social, and governance (ESG) ratings in the context of the European Union sustainability reporting regulations. Using a sample of 7242 firm‐year observations over the period 2015–2023, our results indicate a structural change in ...
Mihaela Ionașcu +2 more
wiley +1 more source
Turning Green Into Gold: The Impact of Green Intellectual Capital on Performance in European Firms
ABSTRACT This study examines the impact of green intellectual capital (GIC)—green human, structural and relational capital—on business performance in European firms. Using Eurobarometer 498 data and Partial Least Squares Structural Equation Modelling (PLS‐SEM), results show that GIC explains 15.4% of the variance in business performance, with green ...
María del Carmen Peces Prieto +2 more
wiley +1 more source
It investigated the energy optimal control problem for metro train operation process and established a linear quadratic optimal model in according to the traction and brake capability, speed limits andpassenger comfort.
FENG Jianghua +4 more
doaj
Ensemble‐based soil liquefaction assessment: Leveraging CPT data for enhanced predictions
Abstract This study focuses on predicting soil liquefaction, a critical phenomenon that can significantly impact the stability and safety of structures during seismic events. Accurate liquefaction assessment is vital for geotechnical engineering, as it informs the design and mitigation strategies needed to safeguard infrastructure and reduce the risk ...
Arsham Moayedi Far, Masoud Zare
wiley +1 more source
Abstract We develop a delay‐aware estimation and control framework for a non‐isothermal axial dispersion tubular reactor modelled as a coupled parabolic‐hyperbolic PDE system with recycle‐induced state delay. The infinite‐dimensional dynamics are preserved without spatial discretization by representing the delay as a transport PDE and adopting a late ...
Behrad Moadeli, Stevan Dubljevic
wiley +1 more source
Optimal model‐based design of experiments for parameter precision: Supercritical extraction case
Abstract This study investigates the process of chamomile oil extraction from flowers. A parameter‐distributed model consisting of a set of partial differential equations is used to describe the governing mass transfer phenomena in a cylindrical packed bed with solid chamomile particles under supercritical conditions using carbon dioxide as a solvent ...
Oliwer Sliczniuk, Pekka Oinas
wiley +1 more source
Integrated Aspen HYSYS–machine learning framework for predicting product yields and quality variables. Abstract Crude oil refining is a complex process requiring precise modelling to optimize yield, quality, and efficiency. This study integrates Aspen HYSYS® simulations with machine learning techniques to develop predictive models for key refinery ...
Aldimiro Paixão Domingos +3 more
wiley +1 more source

