Artificial Neural Networks for Engineering Applications


Artificial Neural Networks for Engineering Applications
ISBN-10 书号: 0128182474
ISBN-13 书号: 9780128182475
Edition 版本: 1
Release Finelybook 出版日期: 2019-02-13
pages 页数: (176 )

The Book Description robot was collected from Amazon and arranged by Finelybook

Artificial Neural Networks for Engineering Applications presents current trends for the solution of complex engineering problems that cannot be solved through conventional methods. The proposed methodologies can be applied to modeling, pattern recognition, classification, forecasting, estimation, and more. Readers will find different methodologies to solve various problems, including complex nonlinear systems, cellular computational networks, waste water treatment, attack detection on cyber-physical systems, control of UAVs, biomechanical and biomedical systems, time series forecasting, biofuels, and more. Besides the real-time implementations, the book contains all the theory required to use the proposed methodologies for different applications.

Presents the current trends for the solution of complex engineering problems that cannot be solved through conventional methods
Includes real-life scenarios where a wide range of artificial neural network architectures can be used to solve the problems encountered in engineering
Contains all the theory required to use the proposed methodologies for different applications
Acknowledgment
1Hierarchical Dynamic Neural Networks for Cascade System Modeling With Application
to Wastewater Treatment
2 Hyperellipsoidal Neural Network Trained With Extended Kalman Filter for Forecasting
of Time Series
3Neural Networks:A Methodology for Modeling and Control Design of Dynamical
Systems
4 Continuous-Time Decentralized Neural Control of a Quadrotor UAV
5Adaptive PID Controller Using a Multilayer Perceptron Trained With the Extended
Kalman Filter for an Unmanned Aerial Vehicle
6Support Vector Regression for Digital Video Processing
7 Artificial Neural Networks Based on Nonlinear Bioprocess Models for Predicting
Wastewater Organic Compounds and Biofuel Production
8 Learning-Based Identification of Viral Infection Dynamics
9 Attack Detection and Estimation for Cyber-Physical Systems by Using Learning
Methodology
10 Sensitivity Analysis With Artificial Neural Networks for Operation of Photovoltaic
Systems
11 Pattern Classification and Its Applications to Control of Biomechatronic Systems
Index
Back Cover

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