Results 151 to 160 of about 36,835 (256)

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

Integrating Automated Electrochemistry and High‐Throughput Characterization with Machine Learning to Explore Si─Ge─Sn Thin‐Film Lithium Battery Anodes

Advanced Energy Materials, Volume 15, Issue 11, March 18, 2025.
A closed‐loop, data‐driven approach facilitates the exploration of high‐performance Si─Ge─Sn alloys as promising fast‐charging battery anodes. Autonomous electrochemical experimentation using a scanning droplet cell is combined with real‐time optimization to efficiently navigate composition space.
Alexey Sanin, Jackson K. Flowers, Tobias H. Piotrowiak, Frederic Felsen, Leon Merker, Alfred Ludwig, Dominic Bresser, Helge Sören Stein   +7 more
wiley   +1 more source

A hybrid LSTM-GRU framework for lung cancer classification using GWO-WOA algorithm for hyperparameter tuning and BPSO for feature selection. [PDF]

Sci Rep
Amrir MMS, Ayid YM, Elshewey AM, Fouad Y.   +3 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

Prediction of Structural Stability of Layered Oxide Cathode Materials: Combination of Machine Learning and Ab Initio Thermodynamics

Advanced Energy Materials, EarlyView.
In this work, we developed a phase‐stability predictor by combining machine learning and ab initio thermodynamics approaches, and identified the key factors determining the favorable phase for a given composition. Specifically, a lower TM ionic potential, higher Na content, and higher mixing entropy favor the O3 phase.
Liang‐Ting Wu, Milica Zdravković, Dijana Milosavljević, Konstantin Köster, Olivier Guillon, Jyh‐Chiang Jiang, Payam Kaghazchi   +6 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

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

Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

Advanced Energy Materials, EarlyView.
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen, Zheyu Zhang, Kelvian T. Mularso, Bonghyun Jo, Hyun Suk Jung   +4 more
wiley   +1 more source

Minimizing unnecessary tax audits using multi-objective hyperparameter tuning of XGBoost with focal loss. [PDF]

Front Artif Intell
Malashin IP, Masich IS, Tynchenko VS, Gantimurov AP, Nelyub VA, Borodulin AS.   +5 more
europepmc   +1 more source

How Video‐Based Information Affects Farmers' Willingness to Pay for Drone Services

Applied Economic Perspectives and Policy, EarlyView.
ABSTRACT Professional service for digital technology like agricultural drones lowers transaction costs and scope thresholds for smallholders. Meanwhile, perceptual adoption barriers remain underexplored. We conduct a two‐stage choice experiment with a randomized video‐based information treatment among 384 Chinese crop farmers to measure its effect on ...
Hua Zhang, Lena Kuhn, Hang Xiong, Zhanli Sun, Thomas Glauben   +4 more
wiley   +1 more source