Results 41 to 50 of about 59,820 (274)

Using growing RBF-nets in rubber industry process control [PDF]

, 2010
This paper describes the use of a Radial Basis Function (RBF) neural network in the approximation of process parameters for the extrusion of a rubber profile in tyre production. After introducing the rubber industry problem, the RBF network model and the
Brause, Rüdiger W., Pietruschka, Ulf
core  

Comparison of Support Vector Machine and Back Propagation Neural Network in Evaluating the Enterprise Financial Distress

, 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

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, Depeng Kong, Zhiao He, Jikai Liang, Yuyao Lu, Zikang Deng, Honghe Li, Mengke Wang, M. Jamal Deen, Zhiqiu Ye, Shuyao Zhou, Huayong Yang, Honghao Lyu, Jun Chen, Kaichen Xu, Geng Yang   +15 more
wiley   +1 more source

Enabling image optimisation and artificial intelligence technologies for better Internet of Things framework to predict COVID

IET Networks, EarlyView., 2022
Abstract Sensor technology advancements have provided a viable solution to fight COVID and to develop healthcare systems based on Internet of Things (IoTs). In this study, image processing and Artificial Intelligence (AI) are used to improve the IoT framework.
Noor M Allayla, Farah Nazar Ibraheem, Refed Adnan Jaleel   +2 more
wiley   +1 more source

Structural parameter optimization of radial basis function neural network based on improved genetic algorithm and cost function model

Advances in Mechanical Engineering
This 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

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, Hernández González, Jerónimo   +1 more
core   +1 more source

Exploring Quantum Support Vector Regression for Predicting Hydrogen Storage Capacity of Nanoporous Materials

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

A new optimized GA-RBF neural network algorithm. [PDF]

Comput Intell Neurosci, 2014
When confronting the complex problems, radial basis function (RBF) neural network has the advantages of adaptive and self-learning ability, but it is difficult to determine the number of hidden layer neurons, and the weights learning ability from hidden layer to the output layer is low; these deficiencies easily lead to decreasing learning ability and ...
Jia W, Zhao D, Shen T, Su C, Hu C, Zhao Y.   +5 more
europepmc   +4 more sources

Magnetic Modelling of Synchronous Reluctance and Internal Permanent Magnet Motors Using Radial Basis Function Networks [PDF]

, 2018
The general trend toward more intelligent energy-aware ac drives is driving the development of new motor topologies and advanced model-based control techniques.
Ortombina, L., Tinazzi, F., Zigliotto, M.   +2 more
core   +1 more source

A Solution for Exosome‐Based Analysis: Surface‐Enhanced Raman Spectroscopy and Artificial Intelligence

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, Zakarya Al‐Shaebi, Omer Aydin   +2 more
wiley   +1 more source