Hybrid approach to predict the effective properties of heterogeneous materials using Artificial Neural Networks and micromechanical models

Effective Properties ◽

Hybrid Approach ◽

Heterogeneous Materials ◽

Artificial Neural ◽

Micromechanical Models

Artificial Neural Networks and Haken’s Synergetic Computer: A Hybrid Approach for Solving Bistable Reversible Figures

Ambiguity in Mind and Nature - Springer Series in Synergetics ◽

10.1007/978-3-642-78411-8_16 ◽

1995 ◽

pp. 311-335

Author(s):

H. H. Szu ◽

F. Lu ◽

J. S. Landa

Keyword(s):

Neural Networks ◽

Hybrid Approach ◽

Reversible Figures ◽

Studies in Computational Intelligence - Intelligent Computing Paradigm: Recent Trends ◽

Product Prediction and Recommendation in E-Commerce Using Collaborative Filtering and Artificial Neural Networks: A Hybrid Approach

10.1007/978-981-13-7334-3_5 ◽

2019 ◽

pp. 59-67

Author(s):

Soma Bandyopadhyay ◽

S. S. Thakur

Keyword(s):

Neural Networks ◽

Collaborative Filtering ◽

Hybrid Approach ◽

A computationally efficient hybrid approach based on artificial neural networks and the wavelet transform for quantum simulations of graphene nanoribbon FETs

Journal of Computational Electronics ◽

10.1007/s10825-019-01350-2 ◽

2019 ◽

Vol 18 (3) ◽

pp. 813-825 ◽

Cited By ~ 11

Author(s):

Khalil Tamersit ◽

Fayçal Djeffal

Keyword(s):

Neural Networks ◽

Wavelet Transform ◽

Hybrid Approach ◽

Graphene Nanoribbon ◽

Computationally Efficient ◽

Quantum Simulations ◽

A Hybrid Approach Using Hydrodynamic Modeling and Artificial Neural Networks for Extreme Storm Surge Prediction

Coastal Engineering Journal ◽

10.1142/s0578563415400045 ◽

2015 ◽

Vol 57 (1) ◽

pp. 1540004-1-1540004-36 ◽

Cited By ~ 6

Author(s):

Mohamed Tayel ◽

Hocine Oumeraci

Keyword(s):

Neural Networks ◽

Storm Surge ◽

Hybrid Approach ◽

Hydrodynamic Modeling ◽

Extreme Storm ◽

Motion Planning for Highly Automated Road Vehicles with a Hybrid Approach Using Nonlinear Optimization and Artificial Neural Networks

Strojniški vestnik – Journal of Mechanical Engineering ◽

10.5545/sv-jme.2018.5802 ◽

2019 ◽

pp. 148-160 ◽

Cited By ~ 2

Author(s):

Ferenc Hegedüs ◽

Tamás Bécsi ◽

Szilárd Aradi ◽

Péter Gáspár

Keyword(s):

Neural Networks ◽

Motion Planning ◽

Nonlinear Optimization ◽

Hybrid Approach ◽

Road Vehicles ◽

New hybrid approach based on artificial neural networks for RFID network planning with random redundant antenna elimination

10.1109/tst52996.2021.00011 ◽

2021 ◽

Author(s):

Maimouni Mustapha ◽

Badr Abou El Majd

Keyword(s):

Neural Networks ◽

Hybrid Approach ◽

Network Planning ◽

Modeling cation exchange capacity in gypsiferous soils using hybrid approach involving the artificial neural networks and ant colony optimization (ANN–ACO)

Modeling Earth Systems and Environment ◽

10.1007/s40808-021-01344-9 ◽

2022 ◽

Author(s):

Shiva Nazari ◽

Hamid Reza Momtaz ◽

Moslem Servati

Keyword(s):

Neural Networks ◽

Cation Exchange ◽

Ant Colony Optimization ◽

Cation Exchange Capacity ◽

Hybrid Approach ◽

Exchange Capacity ◽

Ant Colony ◽

A Hybrid Approach of Partial Least Squared Analysis and Artificial Neural Networks for Predictive Control of a Ceramic Process

Transactions of the Indian Ceramic Society ◽

10.1080/0371750x.2010.11090823 ◽

2010 ◽

Vol 69 (2) ◽

pp. 89-98 ◽

Cited By ~ 1

Author(s):

Najmeh Neshat ◽

Nasser Salmasi ◽

Aliyeh Kazemi

Keyword(s):

Neural Networks ◽

Predictive Control ◽

Hybrid Approach ◽

Ceramic Process ◽

Hybrid Approach Based on Combination of Backpropagation and Evolutionary Algorithms for Artificial Neural Networks Training by Using Mobile Devices in Distributed Computing Environment

Large-Scale Scientific Computing - Lecture Notes in Computer Science ◽

10.1007/978-3-319-73441-5_46 ◽

2018 ◽

pp. 425-432

Author(s):

Iliyan Zankinski ◽

Maria Barova ◽

Petar Tomov

Keyword(s):

Neural Networks ◽

Distributed Computing ◽

Evolutionary Algorithms ◽

Mobile Devices ◽

Hybrid Approach ◽

Computing Environment ◽

Ro-Ro Freight Prediction Using a Hybrid Approach Based on Empirical Mode Decomposition, Permutation Entropy and Artificial Neural Networks

Lecture Notes in Computer Science - Hybrid Artificial Intelligent Systems ◽

10.1007/978-3-030-29859-3_48 ◽

2019 ◽

pp. 563-574

Author(s):

Jose Antonio Moscoso-Lopez ◽

Juan Jesus Ruiz-Aguilar ◽

Javier Gonzalez-Enrique ◽

Daniel Urda ◽

Hector Mesa ◽

...

Keyword(s):

Neural Networks ◽

Empirical Mode Decomposition ◽

Hybrid Approach ◽

Permutation Entropy ◽

Mode Decomposition ◽