Results 51 to 60 of about 1,355,935 (279)
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
Advances in Mechanical EngineeringThis paper investigates the structural parameter optimization of RBF networks with the goal of economic control. The cost function and its implementation method are analyzed, and the cost function model of RBF neural network is established.
Lianhui Li, Adham Manyara, Jie Liu
doaj +1 more source
Advanced Intelligent Discovery, EarlyView.In this study we employed support vector regressor and quantum support vector regressor to predict the hydrogen storage capacity of metal–organic frameworks using structural and physicochemical descriptors. This study presents a comparative analysis of classical support vector regression (SVR) and quantum support vector regression (QSVR) in predicting ...
Chandra Chowdhury
wiley +1 more source
Similarity networks for classification: a case study in the Horse Colic problem [PDF]
, 2014 This paper develops a two-layer neural network in which the neuron model computes a user-defined similarity function between inputs and weights. The neuron transfer function is formed by composition of an adapted logistic function with the mean of the ...
Belanche Muñoz, Luis Antonio +1 more
core +1 more source
Advanced Intelligent Discovery, EarlyView.Exosomes are emerging as powerful biomarkers for disease diagnosis and monitoring. This review highlights the integration of surface‐enhanced Raman spectroscopy with artificial intelligence to enhance molecular fingerprinting of exosomes. Machine learning and deep learning techniques improve spectral interpretation, enabling accurate classification of ...
Munevver Akdeniz +2 more
wiley +1 more source
, 2010 Recently, applying the novel data mining techniques for evaluating enterprise financial distress has received much research alternation. Support Vector Machine (SVM) and back propagation neural (BPN) network has been applied successfully in many areas ...
Lee, Ming-Chang, To, Chang
core +1 more source
A Machine Learning Model for Interpretable PECVD Deposition Rate Prediction
Advanced Intelligent Discovery, EarlyView.This study develops six machine learning models (k‐nearest neighbors, support vector regression, decision tree, random forest, CatBoost, and backpropagation neural network) to predict SiNx deposition rates in plasma‐enhanced chemical vapor deposition using hybrid production and simulation data.
Yuxuan Zhai +8 more
wiley +1 more source
Actuators, 2023 Modeling errors and external disturbances have significant impacts on the control accuracy of robotic arm trajectory tracking. To address this issue, this paper proposes a novel method, the neural network terminal sliding mode control (ALSSA-RBFTSM ...
Jianguo Duan +3 more
doaj +1 more source
Using RBF nets in rubber industry process control [PDF]
, 2010 This paper describes the use of a radial basis function (RBF) neural network. It approximates the process parameters for the extrusion of a rubber profile used in tyre production.
Brause, Rüdiger W., Pietruschka, Ulf
core
Reinforcement Learning using Augmented Neural Networks
, 2018 Neural networks allow Q-learning reinforcement learning agents such as deep Q-networks (DQN) to approximate complex mappings from state spaces to value functions.
Grzes, Marek, Shannon, Jack
core +1 more source