Results 71 to 80 of about 84,677 (290)
MathematicsIn the context of neural network optimization, this study explores the performance and computational efficiency of learning rate adjustment strategies applied with Adam and SGD optimizers. Methods evaluated include exponential annealing, step decay, and SHAP-informed adjustments across three datasets: Breast Cancer, Diabetes, and California Housing ...
Jarrod Graham, Victor S. Sheng
openaire +2 more sources
OSL Characterisation of Two Fluvial Sequences of the River Usmacinta in its Middle Catchment (SE Mexico) [PDF]
, 2014 The report summarizes luminescence profiling, initially using a SUERC PPSL system in Mexico, and laboratory analysis at SUERC, used to characterise the stratigraphy and interpret sedimentary processes in terrace deposits of the Usumacinta River, SE ...
Castillo Rodriguez, Miguel +4 more
core
Customizing Tactile Sensors via Machine Learning‐Driven Inverse Design
Advanced Science, EarlyView.ABSTRACT Replicating the sophisticated sense of touch in artificial systems requires tactile sensors with precisely tailored properties. However, manually navigating the complex microstructure‐property relationship results in inefficient and suboptimal designs.
Baocheng Wang +15 more
wiley +1 more source
Dianxin kexue在电信行业中，客户流失的准确预测对于相关企业维持市场竞争力和增加收益至关重要。为此提出一个结合CatBoost算法和SHAP（shapley additive explanations）模型的客户流失预测框架，旨在提高预测的准确性，同时增强模型的可解释性。利用新疆某通信公司的实际营业数据，通过数据预处理及特征工程，构建预测模型，选取5种主要关键性能指标评估模型性能。实验结果显示，所提出模型在选取的评价指标上均优于当前主流机器学习预测模型。最后引入SHAP框架增强模型可解释性，揭示影响客户流失的关键因素 ...
王圣节, 张庆红
doaj +1 more source
Advanced Science, EarlyView.Integrating interpretable machine learning with the fixed‐potential method reveals a novel mechanism: the catalytic activity of the electrochemical nitrogen reduction reaction is governed by partial charge transfer, induced by variations in the intermediate potential of zero charge under constant potential.
Yufei Xue +6 more
wiley +1 more source
Soil temperature prediction based on explainable artificial intelligence and LSTM
Frontiers in Environmental ScienceSoil temperature is a key parameter in many disciplines, and its research has important practical significance. In recent years, the prediction of soil temperature by deep learning has achieved good results.
Qingtian Geng, Leilei Wang, Qingliang Li
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Advanced Science, EarlyView.ABSTRACT Methane's efficient catalytic removal is vital for sustainable development. Bimetallic catalysts, though promising for methane activation, pose a design challenge due to their complex compositional space. This work introduces an integrated framework that combines high‐throughput density functional theory (DFT) and interpretable machine ...
Mingzhang Pan +8 more
wiley +1 more source
Luminescence Dating of Beach Dunes and Fluvial Sediments, Nayarit, Mexico [PDF]
, 2018 The Pacific coast of the state of Nayarit, Mexico, is dominated by extensive sand dune systems and lagoons. 16 samples from three transects through dunes near the town of Santa Cruz were collected to establish ages of the beach dune ridges and establish ...
Castillo, M. +3 more
core
Advanced Science, EarlyView.CellFreeGMF traces plasma cfRNA to likely originating cell types by integrating single‐cell atlases with graph‐regularized matrix factorization. The method decomposes cfRNA profiles into sample–cell contributions to reconstruct pseudo single‐cell expression.
Wenxiang Zhang +9 more
wiley +1 more source
Machine learning models have grown increasingly deep and high dimensional, making it difficult to understand how individual and combined features influence their predictions. While Shapley value based methods provide principled feature attributions, existing formulations cannot tractably evaluate higher order interactions: the Shapley Taylor ...
Hasegawa, Hiroki, Okada, Yukihiko
openaire +2 more sources