[HTML][HTML] Enhancing compressive strength prediction in self-compacting concrete using machine learning and deep learning techniques with incorporation of rice husk …
Focusing on sustainable development, the demand for alternative materials in concrete,
especially for Self-Compacting Concrete (SCC), has risen due to excessive cement usage …
especially for Self-Compacting Concrete (SCC), has risen due to excessive cement usage …
Process Systems Engineering Tools for Optimization of Trained Machine Learning Models: Comparative and Perspective
FJ López-Flores, C Ramírez-Márquez… - Industrial & …, 2024 - ACS Publications
This article studies the relevance of innovative Process Systems Engineering (PSE) tools
that can reformulate trained machine learning models that are driven by advances in …
that can reformulate trained machine learning models that are driven by advances in …
Insight into soft chemometric computational learning for modelling oily-wastewater separation efficiency and permeate flux of polypyrrole-decorated ceramic-polymeric …
Reliable modeling of oily wastewater emphasizes the paramount importance of sustainable
and health-conscious wastewater management practices, which directly aligns with the …
and health-conscious wastewater management practices, which directly aligns with the …
[HTML][HTML] Augmenting optimization-based molecular design with graph neural networks
Computer-aided molecular design (CAMD) studies quantitative structure–property
relationships and discovers desired molecules using optimization algorithms. With the …
relationships and discovers desired molecules using optimization algorithms. With the …
A Pork Price Prediction Model Based on a Combined Sparrow Search Algorithm and Classification and Regression Trees Model
J Qin, D Yang, W Zhang - Applied Sciences, 2023 - mdpi.com
The frequent fluctuation of pork prices has seriously affected the sustainable development of
the pork industry. The accurate prediction of pork prices can not only help pork practitioners …
the pork industry. The accurate prediction of pork prices can not only help pork practitioners …
PySCIPOpt-ML: Embedding trained machine learning models into mixed-integer programs
A standard tool for modelling real-world optimisation problems is mixed-integer
programming (MIP). However, for many of these problems there is either incomplete …
programming (MIP). However, for many of these problems there is either incomplete …
Global optimization: a machine learning approach
D Bertsimas, G Margaritis - Journal of Global Optimization, 2024 - Springer
Many approaches for addressing global optimization problems typically rely on relaxations
of nonlinear constraints over specific mathematical primitives. This is restricting in …
of nonlinear constraints over specific mathematical primitives. This is restricting in …
[HTML][HTML] Deep learning enhanced mixed integer optimization: Learning to reduce model dimensionality
N Triantafyllou, MM Papathanasiou - Computers & Chemical Engineering, 2024 - Elsevier
This work introduces a framework to address the computational complexity inherent in Mixed
Integer Programming (MIP) models by harnessing the potential of deep learning. By …
Integer Programming (MIP) models by harnessing the potential of deep learning. By …
[HTML][HTML] Multiscale optimization of formic acid dehydrogenation process via linear model decision tree surrogates
Multiscale optimization problems require the interconnection of several models of distinct
phenomena which occur at different scales in length or time. However, the best model for …
phenomena which occur at different scales in length or time. However, the best model for …
Beyond the fourth paradigm of modeling in chemical engineering
Differentiable programming underpins the foundations of machine learning, and enables
new approaches to solving chemical engineering problems. This Comment discusses the …
new approaches to solving chemical engineering problems. This Comment discusses the …