Results 41 to 50 of about 2,398,960 (400)
Artificial Neural Network Methods for the Solution of Second Order Boundary Value Problems
Computers Materials & Continua, 2019 : We present a method for solving partial differential equations using artificial neural networks and an adaptive collocation strategy. In this procedure, a coarse grid of training points is used at the initial training stages, while more points are ...
C. Anitescu +3 more
semanticscholar +1 more source
Estimation of soil properties by an artificial neural network
Magazine of Civil Engineering, 2022 Empirical dependencies are often used in various fields of geotechnics and civil engineering. The existing empirical formulas are mainly developed with the use of regression and multiple regression.
Ofrikhter Ian +3 more
doaj +1 more source
Artificial Neural Network in Cosmic Landscape [PDF]
, 2017 In this paper we propose that artificial neural network, the basis of machine learning, is useful to generate the inflationary landscape from a cosmological point of view.
Liu, Junyu
core +3 more sources
Threat analysis of IoT networks using artificial neural network intrusion detection system [PDF]
International Symposium on Networks, Computers and Communications, 2016 The Internet of things (IoT) is still in its infancy and has attracted much interest in many industrial sectors including medical fields, logistics tracking, smart cities and automobiles. However as a paradigm, it is susceptible to a range of significant
Elike Hodo +6 more
semanticscholar +1 more source
Sensors, 2022 Structural anomaly diagnosis, such as damage identification, is a continuously interesting issue. Artificial neural networks have an excellent ability to model complex structure dynamics.
Zhi-Gang Ruan, Zu-Guang Ying
doaj +1 more source
PERMODELAN INVERSI PEREDAM MAGNET-REOLOGI BERBASIS JARINGAN SARAF TIRUAN UNTUK SISTEM KENDALI
Rekayasa Mesin, 2022 The application of artificial neural network (ANN) models in magnet-rheological damper modeling is of great interest in recently challenges. Therefore, this study aims to propose a solution to overcome this problem by conducting inverse modeling using an
Rafly Asprilla Alwi +4 more
doaj +1 more source
Artificial Neural Network and its Application Research Progress in Distillation [PDF]
arXiv, 2021 Artificial neural networks learn various rules and algorithms to form different ways of processing information, and have been widely used in various chemical processes. Among them, with the development of rectification technology, its production scale continues to expand, and its calculation requirements are also more stringent, because the artificial ...
arxiv
International Journal of Distributed Sensor Networks, 2016 This article offers a hybrid computational approach that combines an artificial neural network with Bayesian probability to improve on the conventional artificial neural network model.
Pao-Kuan Wu, Tsung-Chih Hsiao, Ming Xiao
doaj +1 more source
Advances in Artificial Neural Networks – Methodological Development and Application
Algorithms, 2009 Artificial neural networks as a major soft-computing technology have been extensively studied and applied during the last three decades. Research on backpropagation training algorithms for multilayer perceptron networks has spurred development of other ...
Yanbo Huang
doaj +1 more source
A proactive metaheuristic model for optimizing weights of artificial neural network [PDF]
, 2020 This paper proposes the Particle Swarm Optimization model for enhancing the performance of an Artificial Neural Network. The learning process of Artificial Neural Network requires a long time to satisfy requirements because of processing complexity of ...
Ebady Manna, Mehdi +3 more
core +3 more sources