Results 221 to 230 of about 217,698 (308)

Deep Learning Prediction of Surface Roughness in Multi‐Stage Microneedle Fabrication: A Long Short‐Term Memory‐Recurrent Neural Network Approach

Advanced Intelligent Discovery, EarlyView.
A sequential deep learning framework is developed to model surface roughness progression in multi‐stage microneedle fabrication. Using real‐world experimental data from 3D printing, molding, and casting stages, an long short‐term memory‐based recurrent neural network captures the cumulative influence of geometric parameters and intermediate outputs ...
Abdollah Ahmadpour, Sara Soltanabadi Farshi, Tuanna Ozcan, Amir Mohammad Ketabchi, Alper Kiraz, Savas Tasoglu   +5 more
wiley   +1 more source

Breast Cancer Data Analysis Using Supervised Machine Learning Algorithms. [PDF]

Cureus
Kutal DH, Koseoglu BN.
europepmc   +1 more source

Identification of Exhaled Volatile Organic Compounds Biomarkers for Lung Cancer Under Data‐Limited Conditions Using Data Augmentation and Multi‐View Feature Selection

Advanced Intelligent Discovery, EarlyView.
This work introduces a novel framework for identifying non‐small cell lung cancer biomarkers from hundreds of volatile organic compounds in breath, analyzed via gas chromatography‐mass spectrometry. This method integrates generative data augmentation and multi‐view feature selection, providing a stable and accurate solution for biomarker discovery in ...
Guancheng Ren, Bohao Liu, Zhiyuan Qu, Xue Jiang, Heng Zhao, Danyao Qu, Ruizhi Ning, Chen Su, Taoping Liu, Guangjian Zhang, Weiwei Wu   +10 more
wiley   +1 more source

Predicting system dynamics of pervasive growth patterns in complex systems. [PDF]

Sci Rep
Hedayatifar L, Morales AJ, Saadi DE, Rigg RA, Buchel O, Akhavan A, Sert E, Kar AA, Sasanpour M, Epstein IR, Bar-Yam Y.   +10 more
europepmc   +1 more source

About rectified sigmoid function for enhancing the accuracy of Physics-Informed Neural Networks [PDF]

Vasiliy A. Es’kin, Alexey O. Malkhanov, Mikhail E. Smorkalov   +2 more
openalex   +1 more source

A Physics Constrained Machine Learning Pipeline for Young's Modulus Prediction in Multimaterial Hyperelastic Cylinders Guided by Contact Mechanics

Advanced Intelligent Discovery, EarlyView.
A physics‐guided machine learning framework estimates Young's modulus in multilayered multimaterial hyperelastic cylinders using contact mechanics. A semiempirical stiffness law is embedded into a custom neural network, ensuring physically consistent predictions. Validation against experimental and numerical data on C.
Christoforos Rekatsinas, Panagiotis Krokidas, Vasileios Vavourakis, Clara Essmann, George Giannakopoulos   +4 more
wiley   +1 more source

Towards accurate penetration depth estimation in near-infrared spectroscopy: a quantitative analysis of source-detector distance dependence in porcine kidney models. [PDF]

Biomed Opt Express
Khurana AS, Khodavandi A, Amani Tehrani I, Shadgan B.   +3 more
europepmc   +1 more source

Predicting the mechanical properties of polypropylene and recycled polypropylene by the application of sigmoid and ReLU functions in neural networks

Jittiwat Nithikarnjanatharn, Jetnipat Pimollukanakul, Wannisa Nutkhum, Kanchit Rongchai, Thongchai Arunchai, Panuput Satuwong   +5 more
openalex   +1 more source

Gamma Transformation (Tone Rescaling)by Sigmoid Function (II): Subjective Estimation by Paired Comparison

, 2001
Yoshitaka Iwasaki, Takashi Yamaguchi, Takashi Watanabe, Yasushi Hoshino   +3 more
openalex   +2 more sources

Solving Data Overlapping Problem Using A Class‐Separable Extreme Learning Machine Auto‐Encoder

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
The overlapping and imbalanced data in classification present key challenges. Class‐separable extreme learning machine auto‐encoding (CS‐ELM‐AE) is proposed, which is an enhancement of ELM‐AE that better handles overlapping data by clustering points from the same class together. Applying oversampling addresses imbalanced data.
Ekkarat Boonchieng, Wanchaloem Nadda
wiley   +1 more source