Results 171 to 180 of about 331,059 (292)

An expectile-based framework for risk-calibrated credible capacity evaluation of virtual power plants under wind and PV forecast uncertainties. [PDF]

Sci Rep
Hua D, Zeng J, Lin Q, Cui S, Liu Y, Liang Y.   +5 more
europepmc   +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

A hierarchical deep learning framework with doubly regularized loss for robust malware detection and family categorization. [PDF]

Sci Rep
Abed Alsaedi S, Alwateer M, Helal Alharbi N, Magdy Balaha H, M Aboelnaga M, Badawy M, A Elhosseini M.   +6 more
europepmc   +1 more source

Exploring Quantum Support Vector Regression for Predicting Hydrogen Storage Capacity of Nanoporous Materials

Advanced Intelligent Discovery, EarlyView.
In this study we employed support vector regressor and quantum support vector regressor to predict the hydrogen storage capacity of metal–organic frameworks using structural and physicochemical descriptors. This study presents a comparative analysis of classical support vector regression (SVR) and quantum support vector regression (QSVR) in predicting ...
Chandra Chowdhury
wiley   +1 more source

From Molecular Cleavage to Clinical Effect: A Probabilistic Field Model of Botulinum Toxin Action. [PDF]

Biology (Basel)
Armenti AF, Armenti F.
europepmc   +1 more source

Probabilistic-Deterministic Modeling of the Genetic Code: A Mathematical Verification

This study presents a mathematical framework to explore the evolutionary formation of the genetic code using a probabilistic-deterministic model. The model is defined by the equation P(y|x) = Δ(x) · f(x), where f(x) is the normalized codon frequency and Δ(x) is an environmental weighting factor based on GC content.
openaire   +1 more source

Application of Neural Networks for Advanced Ir Spectroscopy Characterization of Ceria Catalysts Surfaces

Advanced Intelligent Discovery, EarlyView.
A novel convolutional neural network architecture enables rapid, unsupervised analysis of IR spectroscopic data from DRIFTS and IRRAS. By combining synthetic data generation with parallel convolutional layers and advanced regularization, the model accurately resolves spectral features of adsorbed CO, offering real‐time insights into ceria surface ...
Mehrdad Jalali, Lachlan Caulfield, Eric Sauter, Alexei Nefedov, Chengwu Yang, Christof Wöll   +5 more
wiley   +1 more source

Quantum-Inspired and Non-Classical Approaches to Consciousness: Models, Evidence and Constraints. [PDF]

Brain Sci
Arias-Carrión O, Ortega-Robles E, Manjarrez E.   +2 more
europepmc   +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

Source identification of sudden water pollution events in the Dongliao River using a hybrid machine learning framework. [PDF]

Sci Rep
Wang Y, Wang Y, Shi P, Bian J, Chen C.
europepmc   +1 more source