Results 221 to 230 of about 1,020,742 (284)

Fault detection and diagnosis in photovoltaic systems using artificial intelligence and time-frequency analysis. [PDF]

Sci Rep
Seghiour A, Bendjeddou Y, Mostefaoui IM, Chouder A, Alharbi H, Humayd ASB, Wondimeneh AW, Babqi A.   +7 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

Global solar energy potential forecasting through machine learning and deep learning models. [PDF]

Sci Rep
Raza MA, Karim A, Altayeb M, Masud MI, Faheem M, Jumani TA, Aman M.   +6 more
europepmc   +1 more source

Feature Selection for Machine Learning‐Driven Accelerated Discovery and Optimization in Emerging Photovoltaics: A Review

Advanced Intelligent Discovery, EarlyView.
Feature selection combined with machine learning and high‐throughput experimentation enables efficient handling of high‐dimensional datasets in emerging photovoltaics. This approach accelerates material discovery, improves process optimization, and strengthens stability prediction, while overcoming challenges in data quality and model scalability to ...
Jiyun Zhang, Jiayi Tan, Qizhen Song, Tian Du, Jens Hauch, Christoph J. Brabec   +5 more
wiley   +1 more source

Impaired excitability of fast-spiking neurons in a novel mouse model of <i>KCNC1</i> epileptic encephalopathy. [PDF]

Elife
Wengert ER, Liebergall SR, Jimenez T, Cheng MA, Markwalter KH, Clatot J, Hong Y, Arias L, Marsh ED, Zhang X, Tsetsenis T, Somarowthu A, Akizu N, Goldberg EM.   +13 more
europepmc   +1 more source

Deep Learning‐Assisted Design of Mechanical Metamaterials

Advanced Intelligent Discovery, EarlyView.
This review examines the role of data‐driven deep learning methodologies in advancing mechanical metamaterial design, focusing on the specific methodologies, applications, challenges, and outlooks of this field. Mechanical metamaterials (MMs), characterized by their extraordinary mechanical behaviors derived from architected microstructures, have ...
Zisheng Zong, Pu Wen, Zhiping Chai, Dunxuan Wu, Han Ding, Zhigang Wu   +5 more
wiley   +1 more source

IL‑37/IL‑1R8 blocks keratinocyte acantholysis via suppressing ADAM17/EGFR. [PDF]

Int J Mol Med
Hu F, Chen W, Wang Q, Zhang X, Xiao F, Zhang J, Liang J.   +6 more
europepmc   +1 more source

Why Physics Still Matters: Improving Machine Learning Prediction of Material Properties With Phonon‐Informed Datasets

Advanced Intelligent Discovery, EarlyView.
Phonons‐informed machine‐learning predictive models are propitious for reproducing thermal effects in computational materials science studies. Machine learning (ML) methods have become powerful tools for predicting material properties with near first‐principles accuracy and vastly reduced computational cost.
Pol Benítez, Cibrán López, Edgardo Saucedo, Teruyasu Mizoguchi, Claudio Cazorla   +4 more
wiley   +1 more source

Why JAK2-mutated neutrophils deserve to be on center stage in polycythemia vera. [PDF]

Ann Hematol
Masarova L, Qin A, Yoon CH, Yacoub A, Prchal JT, Mascarenhas J.   +5 more
europepmc   +1 more source

Controlling Dynamical Systems Into Unseen Target States Using Machine Learning

Advanced Intelligent Systems, EarlyView.
Parameter‐aware next‐generation reservoir computing enables efficient, data‐driven control of dynamical systems across unseen target states and nonstationary transitions. The approach suppresses transient behavior while navigating system collapse scenarios with minimal training data—over an order of magnitude less than traditional methods.
Daniel Köglmayr, Alexander Haluszczynski, Christoph Räth   +2 more
wiley   +1 more source