Results 21 to 30 of about 68,126 (238)

Optimised Internet of Thing framework based hybrid meta‐heuristic algorithms for E‐healthcare monitoring

IET Networks, EarlyView., 2022
Abstract Everything can be connected in the Internet of Things (IoTs) technology that enables efficient communication between connected objects. IoTs industry‐based meta‐heuristic and mining algorithms, which are considered an important field of Artificial Intelligence will be used to construct a healthcare application in this study for lowering costs,
Muhaned Al‐Hashimi, Shymaa Mohammed Jameel, Firas Husham Almukhtar, Musaddak Maher Abdul Zahra, Refed Adnan Jaleel   +4 more
wiley   +1 more source

Quality Performance Criterion Model for Distributed Automated Control Systems Based on Markov Processes for Smart Grid

Applied Sciences
This paper addresses the problem of decision-making support for the modernization of distributed automated control systems (ACS) in power engineering by proposing an integral quality criterion that combines similarity-driven Markov process modeling with ...
Waldemar Wojcik, Ainur Ormanbekova, Muratkali Jamanbayev, Maria Yukhymchuk, Vladyslav Lesko   +4 more
doaj   +1 more source

Stochastic-based pavement performance and deterioration models: A review of techniques and applications

Alexandria Engineering Journal
Infrastructure assets, such as pavements, naturally deteriorate over time due to traffic loads, environmental conditions, and other external factors. Traditionally, deterministic models have been employed to predict performance, aiding in work planning ...
Che Shobry Shahid, Zulhilmi Amir Zainal, Nur Izzi Md Yusoff, Noraziah Mohammad, Zamira Hasanah Zamzuri, Iswandaru Widyatmoko   +5 more
doaj   +1 more source

Optimal Control of Partially Observable Piecewise Deterministic Markov Processes

, 2018
In this paper we consider a control problem for a Partially Observable Piecewise Deterministic Markov Process of the following type: After the jump of the process the controller receives a noisy signal about the state and the aim is to control the ...
Bäuerle, Nicole, Lange, Dirk
core   +1 more source

AI in chemical engineering: From promise to practice

AIChE Journal, EarlyView.
Abstract Artificial intelligence (AI) in chemical engineering has moved from promise to practice: physics‐aware (gray‐box) models are gaining traction, reinforcement learning complements model predictive control (MPC), and generative AI powers documentation, digitization, and safety workflows.
Jia Wei Chew, Ronnie Andersson, Thomas Bierweiler, Patrik Ryttestal, Torsten Wik   +4 more
wiley   +1 more source

Computational study of permeability in cardboard coating layers

AIChE Journal, EarlyView.
Abstract We develop a virtual material structure model based on a combination of tessellations and Gaussian random fields for a coating layer of paperboard used for packaging and designed to facilitate printing on the surface. To fit the model to tomographic image data acquired using combined focused ion beam and scanning electron microscopy (FIB‐SEM),
Sandra Barman, Torben Nilsson Pingel, Niklas Lorén, Tobias Gebäck, Eva Olsson, Aila Särkkä, Magnus Röding   +6 more
wiley   +1 more source

Wide sense one-dependent processes with embedded Harris chains and their applications in inventory management [PDF]

, 2003
In this paper we consider stochastic processes with an embedded Harris chain. The embedded Harris chain describes the dependence structure of the stochastic process.
Bazsa-Oldenkamp, E.M. (Emö), Iseger, P. den   +1 more
core  

From Infinite to Finite Programs: Explicit Error Bounds with Applications to Approximate Dynamic Programming

, 2017
We consider linear programming (LP) problems in infinite dimensional spaces that are in general computationally intractable. Under suitable assumptions, we develop an approximation bridge from the infinite-dimensional LP to tractable finite convex ...
Esfahani, Peyman Mohajerin, Kuhn, Daniel, Lygeros, John, Sutter, Tobias   +3 more
core   +1 more source

Overcoming the Nyquist Limit in Molecular Hyperspectral Imaging by Reinforcement Learning

Advanced Intelligent Discovery, EarlyView.
Explorative spectral acquisition guide automatically selects informative spectral bands to optimize downstream tasks, outperforming full‐spectrum acquisition. The selected hyperspectral data are used for tasks such as unmixing and segmentation. BandOptiNet encodes selection states and outputs optimal bands to guide spectral acquisition. Recent advances
Xiaobin Tang, Yongqing Zhang, Xinyu Deng, Hyeon Jeong Lee, Delong Zhang   +4 more
wiley   +1 more source

Update or Wait: How to Keep Your Data Fresh

, 2017
In this work, we study how to optimally manage the freshness of information updates sent from a source node to a destination via a channel. A proper metric for data freshness at the destination is the age-of-information, or simply age, which is defined ...
Koksal, C. Emre, Shroff, Ness B., Sun, Yin, Uysal-Biyikoglu, Elif, Yates, Roy D.   +4 more
core   +1 more source