Results 161 to 170 of about 42,332 (292)

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

Deep Neural Network Weight Initialization from Hyperparameter Tuning Trials

Training of deep neural networks from scratch requires initialization of the neural network weights as a first step. Over the years, many policies and techniques for weight initialization have been proposed and widely used, including Kaiming ...
Wang, Tianze, Payberah, Amir H., Vlassov, Vladimir, Payberah, Amir H.,, Sheikholeslami, Sina,, Vlassov, Vladimir,, Dowling, Jim, Wang, Tianze,, Dowling, Jim,, Sheikholeslami, Sina   +9 more
core   +1 more source

Optimizing Image Classification: Automated Deep Learning Architecture Crafting with Network and Learning Hyperparameter Tuning. [PDF]

Biomimetics (Basel), 2023
Ang KM, Lim WH, Tiang SS, Sharma A, Eid MM, Tawfeek SM, Khafaga DS, Alharbi AH, Abdelhamid AA.   +8 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

Stochastic Grey Wolf Optimization for Hyperparameter Tuning of LSTM and RNN Models in Energy Forecasting. [PDF]

Sci Rep
Albser OA, Mouhamed MR, Shatta SA, Sweilem NH, Darwish A.   +4 more
europepmc   +1 more source

Hybrid XGBoost model with hyperparameter tuning for prediction of liver disease with better accuracy. [PDF]

World J Gastroenterol, 2022
Dalal S, Onyema EM, Malik A.
europepmc   +1 more source

Mechanisms of Alkali Ionic Transport in Amorphous Oxyhalides Solid State Conductors

Advanced Energy Materials, EarlyView.
Large‐scale machine learning‐based molecular dynamics simulations are used to investigate isovalent amorphous oxyhalides, revealing a remarkable chemically independent ionic conductivity. A rigorous analysis of alkali residence times across different metal–anion environments identifies divalent anions as key diffusion bottlenecks.
Luca Binci, KyuJung Jun, Bowen Deng, Gerbrand Ceder   +3 more
wiley   +1 more source

Optimized Machine Learning Pipeline for Lung Cancer Classification: Feature Reduction and Hyperparameter Tuning. [PDF]

Diagnostics (Basel)
Ansari GA, Shafi S, Alhazzaa L.
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

Hybrid Aquila optimizer-Harris Hawks optimization for CNN hyperparameter tuning in brain tumor classification. [PDF]

Sci Rep
Kumar M, Mohd N, Shivam G, Goyal A, Parashar D, Khan R.   +5 more
europepmc   +1 more source