Results 91 to 100 of about 223,298 (311)

Surrogate models and surrogate-based design optimisation

, 2020
Surrogate modelling refers to statistical and numerical techniques to model the relationship between multiple input variables and an output variable. A surrogate model can be considered as a multidimensional surface fitting of the output variable based ...
peter zeno korondi
core  

Data analysis-based framework for the design and assessment of chemical process plants: a case study in amine gas-treating systems

Frontiers in Chemical Engineering
This work presents a process-integrity assessment framework to chemical process design that combines first principles, heuristics, vendor specifications, standards/codes, data analysis, and machine learning modelling, hypothesized as an efficient route ...
Rahul Gupta, Gladys Navas, Daniela Galatro   +2 more
doaj   +1 more source

Three phosphatase families form a community: The phosphohydrolases that act upon inositol pyrophosphates

FEBS Letters, EarlyView.
Inositol pyrophosphates are energy‐rich signaling molecules that perform critical functions in cells. Three different families of phosphatases hydrolyze the β phosphate of the inositol pyrophosphate molecules: two have narrow specificities and one is promiscuous.
Ronda J. Rolfes
wiley   +1 more source

Surrogate-assisted evolutionary optimization frameworks for high-fidelity engineering design problems

, 2004
Over the last decade, Evolutionary Algorithms (EAs) have emerged as a powerful paradigm for global optimization of multimodal functions. More recently, there has been significant interest in applying EAs to engineering design problems.
Wong, K.W., Ong, Yew Soon, Keane, A.J., Nair, P.B., Ong, Y.S.   +4 more
core  

DeforestVis: Behaviour Analysis of Machine Learning Models with Surrogate Decision Stumps

As the complexity of machine learning (ML) models increases and their application in different (and critical) domains grows, there is a strong demand for more interpretable and trustworthy ML.
Chatzimparmpas, Angelos, Martins, Rafeal M., Telea, Alexandru C., Kerren, Andreas   +3 more
core   +1 more source

A deep learning framework for rapid prediction of floor response spectra in multi-story buildings

Journal of Asian Architecture and Building Engineering
This paper presents a study on the development of a deep learning-based methodology for rapidly predicting the floor response spectrum (FRS) of multi-story buildings.
Yuhong Hu, Jianze Wang, Xuelian Li, Kaoshan Dai, Reza Sharbati, Yuanli Tang, Adane Demeke Wasse   +6 more
doaj   +1 more source

Study on the impact of uncertain design parameters on the performances of a permanent magnet-assisted synchronous reluctance motor

Science and Technology for Energy Transition
In this paper, deterministic and robust design optimizations of a permanent magnet-assisted synchronous reluctance motor were performed to study the impact of different uncertain input parameters on the design.
Reyes Adán Reyes, Nasr André, Sinoquet Delphine, Hlioui Sami   +3 more
doaj   +1 more source

Modelling stem cell differentiation related processes—A practical overview for biologists

FEBS Letters, EarlyView.
Stem cell differentiation is complex and difficult to control experimentally. This review introduces suitable computational modelling approaches that can support stem cell research, from mechanistic ODE and abstract models to multiscale and deep learning methods.
Ricco Zeegelaar, Xinqi Yan, Lucas Jansen Klomp, Stefano Schivo, Janine N. Post   +4 more
wiley   +1 more source

Balancing Exploration and Exploitation using Kriging Surrogate Models in Electromagnetic Design Optimization

, 2006
The balance between exploration and exploitation is an important issue when attempting to find the global minimum of an objective function. This paper describes how this balance may be carefully controlled when using Kriging surrogate models to ...
Hawe, G.I., Sykulski, J.K.
core  

Modelling for Digital Twins—Potential Role of Surrogate Models

, 2021
The application of white box models in digital twins is often hindered by missing knowledge, uncertain information and computational difficulties. Our aim was to overview the difficulties and challenges regarding the modelling aspects of digital twin ...
Tibor Chován, Ágnes Bárkányi, Sándor Németh, János Abonyi   +3 more
core   +1 more source