A New Approach Combining Neural Networks and Simulated Annealing for Solving Petroleum Inverse Problems

ECMOR IV - 4th European Conference on the Mathematics of Oil Recovery ◽

10.3997/2214-4609.201411185 ◽

1994 ◽

Author(s):

Ahmed Ouenes ◽

Rao S. Doddi ◽

Yinghua Lin ◽

George Cunningham ◽

Naji Saad

Keyword(s):

Neural Networks ◽

Simulated Annealing ◽

Inverse Problems ◽

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Intelligent methods for solving inverse problems of backscattering spectra with noise: a comparison between neural networks and simulated annealing

Neural Computing and Applications ◽

10.1007/s00521-008-0219-x ◽

2008 ◽

Vol 18 (5) ◽

pp. 423-430 ◽

Author(s):

Michael M. Li ◽

William Guo ◽

Brijesh Verma ◽

Kevin Tickle ◽

John O’Connor

Keyword(s):

Neural Networks ◽

Simulated Annealing ◽

Inverse Problems ◽

Intelligent Methods

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A hybrid approach with artificial neural networks, Levenberg–Marquardt and simulated annealing methods for the solution of gas–liquid adsorption inverse problems

Inverse Problems in Science and Engineering ◽

10.1080/17415970802082922 ◽

2009 ◽

Vol 17 (1) ◽

pp. 85-96 ◽

Author(s):

Jader Lugon ◽

Antônio J. Silva Neto ◽

César Costapinto Santana

Keyword(s):

Neural Networks ◽

Artificial Neural Networks ◽

Simulated Annealing ◽

Inverse Problems ◽

Hybrid Approach ◽

Liquid Adsorption ◽

Levenberg Marquardt ◽

Artificial Neural

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Neural Networks and Classical Algorithms in Inverse Problems of Anomalous Diffusion

2020 Science and Artificial Intelligence conference (S.A.I.ence) ◽

10.1109/s.a.i.ence50533.2020.9303217 ◽

2020 ◽

Author(s):

Vasily A. Dedok ◽

Tatyana V. Bugueva

Keyword(s):

Neural Networks ◽

Inverse Problems ◽

Anomalous Diffusion

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Solving inverse problems in stochastic models using deep neural networks and adversarial training

Computer Methods in Applied Mechanics and Engineering ◽

10.1016/j.cma.2021.113976 ◽

2021 ◽

Vol 384 ◽

pp. 113976

Author(s):

Kailai Xu ◽

Eric Darve

Keyword(s):

Neural Networks ◽

Inverse Problems ◽

Stochastic Models ◽

Deep Neural Networks ◽

Adversarial Training

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A New Approach to the Development of Genetically Optimized Multilayer Fuzzy Polynomial Neural Networks

IEEE Transactions on Industrial Electronics ◽

10.1109/tie.2006.878300 ◽

2006 ◽

Vol 53 (4) ◽

pp. 1309-1321 ◽

Author(s):

S.-K. Oh ◽

W. Pedrycz ◽

H.-S. Park

Keyword(s):

Neural Networks ◽

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A new approach to intrusion detection using Artificial Neural Networks and fuzzy clustering

Expert Systems with Applications ◽

10.1016/j.eswa.2010.02.102 ◽

2010 ◽

Vol 37 (9) ◽

pp. 6225-6232 ◽

Author(s):

Gang Wang ◽

Jinxing Hao ◽

Jian Ma ◽

Lihua Huang

Keyword(s):

Neural Networks ◽

Artificial Neural Networks ◽

Intrusion Detection ◽

Fuzzy Clustering ◽

New Approach ◽

Artificial Neural

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Global Exponential Stability of Delayed Cohen-Grossberg Neural Networks: A New Approach via Halanay Inequality and Bellman Inequality

2008 Fourth International Conference on Natural Computation ◽

10.1109/icnc.2008.247 ◽

2008 ◽

Author(s):

Kaiyu Liu ◽

Ya Li

Keyword(s):

Neural Networks ◽

Exponential Stability ◽

Global Exponential Stability ◽

New Approach ◽

Halanay Inequality

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Side-chain prediction by neural networks and simulated annealing optimization

Protein Engineering Design and Selection ◽

10.1093/protein/8.4.363 ◽

1995 ◽

Vol 8 (4) ◽

pp. 363-370 ◽

Author(s):

Jenn-Kang Hwang ◽

Wen-Fa Liao

Keyword(s):

Neural Networks ◽

Simulated Annealing ◽

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Convergence suppression and divergence facilitation: new approach to prune hidden layer and weights of feedforward neural networks

Proceedings of ISCAS'95 - International Symposium on Circuits and Systems ◽

10.1109/iscas.1995.521466 ◽

2002 ◽

Author(s):

S. Yasui ◽

A. Malinowski ◽

J.M. Zurada

Keyword(s):

Neural Networks ◽

Feedforward Neural Networks ◽

New Approach ◽

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Physics-Informed Graph Convolutional Neural Networks: A Unified Framework for Solving PDE-Governed Forward and Inverse Problems

10.1115/1.0004979v ◽

2021 ◽

Author(s):

Han Gao ◽

Jian-Xun Wang

Keyword(s):

Neural Networks ◽

Inverse Problems ◽

Convolutional Neural Networks ◽

Unified Framework

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