Results 141 to 150 of about 93,556 (252)

Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials

Advanced Science, EarlyView.
Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan, Hengheng Zhao, Haotian Wang, Zhanjie Liu, Qian Li, Weifeng Zhang, Qingsong Zhao, Liqun Zhang, Jun Liu   +8 more
wiley   +1 more source

Hyperparameter Tuning of Artificial Neural Networks for Well Production Estimation Considering the Uncertainty in Initialized Parameters. [PDF]

ACS Omega, 2022
Jin M, Liao Q, Patil S, Abdulraheem A, Al-Shehri D, Glatz G.   +5 more
europepmc   +1 more source

How AI Shapes the Future Landscape of Sustainable Building Design With Climate Change Challenges?

Advanced Science, EarlyView.
This review examines how artificial intelligence reshapes sustainable building design faced with climate change challenges. The authors synthesize existing studies to demonstrate AI's transformative potential across design lifecycle phases from climate‐aware form generation to performance optimization.
Pengyuan Shen, Xiaoni Gao, Shuai Lu, Yi Zhang, Xing Zheng, Matthaios Santamouris   +5 more
wiley   +1 more source

A novel method of bayesian genetic optimization on automated hyperparameter tuning. [PDF]

Sci Rep
Li Q, Kamaruddin N, Zhang J, Peng C, Sui Ki Khoo A.   +4 more
europepmc   +1 more source

Creating sparser prediction models of treatment outcome in depression: a proof-of-concept study using simultaneous feature selection and hyperparameter tuning. [PDF]

BMC Med Inform Decis Mak, 2022
Rost N, Brückl TM, Koutsouleris N, Binder EB, Müller-Myhsok B.   +4 more
europepmc   +1 more source

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

Advanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray, Andrew R. Castillo, Manoj Kolel‐Veetil, Surya R. Kalidindi   +3 more
wiley   +1 more source

Reward design and hyperparameter tuning for generalizable deep reinforcement learning agents in autonomous racing. [PDF]

Sci Rep
Kunda NSS, Kc P, Pandey M, Kumaar AAN.
europepmc   +1 more source

Hyperparameter Tuning and Pipeline Optimization via Grid Search Method and Tree-Based AutoML in Breast Cancer Prediction. [PDF]

J Pers Med, 2021
Radzi SFM, Karim MKA, Saripan MI, Rahman MAA, Isa INC, Ibahim MJ.   +5 more
europepmc   +1 more source

Machine‐Learning‐Guided Design of Incommensurate Antiferroelectrics via Field‐Driven Phase Engineering

Advanced Science, EarlyView.
The key to enhancing the energy storage performance of antiferroelectrics lies in regulating the phase transition and reverse phase transition. A phase‐field‐machine learning framework is employed to predict the energy storage performance of Pb‐based incommensurate antiferroelectrics with multi‐scale regulation strategy, thereby revealing the dynamic ...
Ke Xu, Xiaoming Shi, Zhaochen Xi, Shouzhe Dong, Changqing Guo, Rongzhen Gao, Letao Yang, Jing Wang, Di Zhou, Houbing Huang   +9 more
wiley   +1 more source

Semi-supervised GAN with hybrid regularization and evolutionary hyperparameter tuning for accurate melanoma detection. [PDF]

Sci Rep
Golkarieh A, Razmara P, Lagzian A, Dolatabadi A, Mousavirad SJ.   +4 more
europepmc   +1 more source