Results 91 to 100 of about 998,736 (272)

Neural network‐based offset‐free model predictive control for nonlinear systems

AIChE Journal, EarlyView.
Abstract This paper proposes an offset‐free model predictive control (MPC) framework for nonlinear systems modeled using neural network‐based nonlinear autoregressive models with exogenous inputs (NARX). To address plant‐model mismatch and ensure offset‐free tracking, the NARX model is augmented with an integrating disturbance model, resulting in an ...
Hesam Hassanpour, Prashant Mhaskar
wiley   +1 more source

Methods of Mathematical Proof and Logic in Mathematics Courses at the Faculty of Education – Sana'a University

, 2021
Fawzi Abdullah Khaled Al-Haded
openalex   +1 more source

Mathematical proofs in practice: revisiting the reliability of published mathematical proofs

, 2014
Mathematics seems to have a special status when compared to other areas of human knowledge. This special status is linked with the role of proof. Mathematicians often believe that this type of argumentation leaves no room for errors and unclarity. Philosophers of mathematics have differentiated between absolutist and fallibilist views on mathematical ...
Frans, Joachim, Kosolosky, Laszlo
openaire   +3 more sources

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

Proof in mathematics education: research, learning and teaching

, 2011
Matthew Inglis
openalex   +2 more sources

Mathematical artificial intelligence design of mutation-proof COVID-19 monoclonal antibodies [PDF]

, 2022
Jiahui Chen, Guo‐Wei Wei
openalex   +1 more source

Artificial Intelligence‐Driven Insights into Electrospinning: Machine Learning Models to Predict Cotton‐Wool‐Like Structure of Electrospun Fibers

Advanced Intelligent Discovery, EarlyView.
Electrospinning allows the fabrication of fibrous 3D cotton‐wool‐like scaffolds for tissue engineering. Optimizing this process traditionally relies on trial‐and‐error approaches, and artificial intelligence (AI)‐based tools can support it, with the prediction of fiber properties. This work uses machine learning to classify and predict the structure of
Paolo D’Elia, Giovanna Pappalardo, Aldo R. Boccaccini, Liliana Liverani   +3 more
wiley   +1 more source

Teachers’ learning and assessing of mathematical processes with emphasis on representations, reasoning and proof

, 2018
Satsope Maoto, Kwena Masha, Lekwa Mokwana   +2 more
openalex   +2 more sources

Smart Bioinspired Material‐Based Actuators: Current Challenges and Prospects

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
This work gathers, in a review style, an extensive and comprehensive literature overview on the development of autonomous actuators based on synthetic materials, bringing together valuable knowledge from several studies. Furthermore, the article identifies the fundamental principles of actuation mechanisms and defines key parameters to address the size
Alejandro Palacios, Léon Chiriatti, Simon Poppinga, Thomas Speck, Vincent Le Houérou   +4 more
wiley   +1 more source

Mathematical Proofs and Scientific Discovery

, 2020
The idea that science can be automated is so deeply related to the view that the method of mathematics is the axiomatic method, that confuting the claim that mathematical knowledge can be extended by means of the axiomatic method is almost equivalent to confuting the claim that science can be automated.
openaire   +1 more source