Results 81 to 90 of about 110,596 (265)

CNN model-relevant hyperparameters.

, 2019
CNN model-relevant hyperparameters.
Takahiro G. Yamada (6386189), Shori Nishimoto (7344497), Noriko F. Hiroi (7344503), Akira Funahashi (109308), Yuta Tokuoka (7344500)   +4 more
core   +1 more source

Hyperparameters for hourly prediction model.

, 2022
Hyperparameters for hourly prediction model.
Tieng Wei Koh (13751576), Fadratul Hafinaz Hassan (11422834), Umair Muneer Butt (13751570), Sukumar Letchmunan (13751573)   +3 more
core   +1 more source

Leveraging Symbolic Artificial Intelligence and Fuzzy Logic for Materials Science: A Review of Methods, Challenges, and Applications to Scarce and Imperfect Experimental Data

Advanced Engineering Materials, EarlyView.
This article explores the transformative potential of symbolic artificial intelligence (AI) in the field of materials science, particularly in leveraging experimental data. The article presents several symbolic AI models and discusses their applications in materials science.
Ahmed Amrani, Mohamed‐Ali Belloum, Laurence Boudet, Valentin Fouillard, Edwin Friedmann, Guillaume Lacharme, Ali Mahmoud, Jean‐Philippe Poli   +7 more
wiley   +1 more source

Distribution network voltage fluctuation source localization based on Bayesian-optimized XGBoost

Zhongguo dianli
In the context of large-scale renewable energy integration, the intermittency and volatility of renewable energy generation superimposed with load variations have exacerbated voltage fluctuation issues.
Fangbing LIU, Ganyun LV, Rui DONG, Jiaxing YE, Lei XU   +4 more
doaj   +1 more source

Hyperparameters of the proposed ReCNN.

, 2022
Hyperparameters of the proposed ReCNN.
Lei Dong (165252), Chaojin Qing (12225185), Guowei Ling (9644284), Jiafan Wang (12225188), Li Wang (15202)   +4 more
core   +1 more source

Detecting Anomalous Cell Behavior in Electrochemical Battery Testing Using Machine Learning

Advanced Engineering Materials, EarlyView.
Machine‐learning‐based screening enables automated identification of anomalous battery cells from complementary electrochemical tests. A curated battery database supports configuration‐aware comparison of rate‐capability and impedance data. Supervised classification of rate‐test data achieves 90% accuracy, while CNN‐VAE‐based impedance analysis reaches
Minu Rose, Sanxchep Sharma, Veit Königer, Vincent Nebel, Jonas Oehm, Christian Weisenberger, Laura Bies, Volker Knoblauch   +7 more
wiley   +1 more source

Multi-Objective Hyperparameter Optimization Improves the Interpretability of LSTM Rainfall–Runoff Models

Hydrology
Rainfall–runoff modeling is a key challenge in hydrological research. Despite the extensive application of long short-term memory (LSTM) networks in rainfall–runoff modeling, our understanding of the influence of different hyperparameter configurations ...
Qiuyang Tan, Jianming Shen, Youqing Wang, Moyuan Yang, Lin Zhu, Juan Zhang, Yang Liu, Zeyuan Chen, Chao Zhai, Yun Zhu   +9 more
doaj   +1 more source

Hyperparameters for grid search.

, 2019
Hyperparameters for grid search.
Cinna Wu (8156757), Yann LeCun (8156763), Mark Tygert (8156760)   +2 more
core   +1 more source

Implantable Ionic Memristors Based on Natural Polymer Heterojunctions

Advanced Functional Materials, EarlyView.
We report an implantable natural polymer‐based ionic memristor composed of hyaluronic acid, chitosan, and PDMS. The device achieved 98.94% accuracy in MNIST classification while reducing training time by 36.8% compared with a conventional artificial neural network (ANN).
Dong‐yup Lee, Byung Ik Park, Gihyeon Yim, Hyunjae Yoo, Sangjun Ma, Jundong Park, Jeong‐Yun Sun   +6 more
wiley   +1 more source

Integrated Hyperparameter Optimization with Dimensionality Reduction and Clustering for Radiomics: A Bootstrapped Approach

Multimodal Technologies and Interaction
Radiomics involves extracting quantitative features from medical images, resulting in high-dimensional data. Unsupervised clustering has been used to discover patterns in radiomic features, potentially yielding hidden biological insights.
S. J. Pawan, Matthew Muellner, Xiaomeng Lei, Mihir Desai, Bino Varghese, Vinay Duddalwar, Steven Y. Cen   +6 more
doaj   +1 more source