Complexity

Neural Network for Complex Systems: Theory and Applications


Publishing date
01 Dec 2017
Status
Published
Submission deadline
14 Jul 2017

Lead Editor

1South China University of Technology, Guangzhou, China

2Kunming University of Science and Technology, Kunming, China

3Queen Mary University of London, London, UK

4Imperial College London, London, UK

5National Institute of Advanced Industrial Science and Technology, Tokyo, Japan


Neural Network for Complex Systems: Theory and Applications

Description

Over the last few decades, neural network (NN) has seen successful development that has wide applications due to the effort of industrial and academic communities. With the powerful approximation ability of NN, it has been evolved into many promising fields, such as modeling and identification of complex and nonlinear systems and optimization and automatic control.

Specifically, the state-of-the-art deep learning NN, allows richer intermediate representations to be learnt, eliminating the effort of feature engineering. For different theories and applications, the design philosophy of NN architecture can be different. Nevertheless, generally NN can be expressed as a weighted sum of several kernel functions, of which the weights can be tuned to approximate an arbitrary smooth or continuous nonlinear function. However, to reveal the fundamental representations and behaviors of NN as a complex system while it is applied into real-world control applications is still a problem to be explored. Understanding this problem could not only promote better understanding of the underlying mechanisms of NN, but also provide a possibility to design a universal NN solution in various real-world applications.

The main focus of this special issue will be on NN theory and analysis as well as its potential engineering applications in complex systems. Authors are invited to present theories, algorithms, and frameworks aimed at bringing about advanced techniques of NN for modeling, identification, control, and optimization of complex systems. We also encourage authors to introduce new results for synthesizing NN into complex psychical systems, such as, hypersonic flight vessels, robots, and industrial process.

Potential topics include but are not limited to the following:

  • Convergence and stability analysis of neural network
  • Neural network for optimization
  • Neural network based system identification
  • Neural network based observer design
  • Theory and applications of recurrent neural network
  • Theory and applications of deep learning neural networks
  • Neural models of perception, action, and cognition
  • Neural network control for mobile robots, flight vessels, autonomous underwater vehicles, and other robotic systems
  • Neural network modeling and control for sustainable energy plants

Articles

  • Special Issue
  • - Volume 2018
  • - Article ID 3141805
  • - Editorial

Neural Network for Complex Systems: Theory and Applications

Chenguang Yang | Jing Na | ... | Junpei Zhong
  • Special Issue
  • - Volume 2018
  • - Article ID 1627185
  • - Research Article

Visual Semantic Navigation Based on Deep Learning for Indoor Mobile Robots

Li Wang | Lijun Zhao | ... | Chenguang Yang
  • Special Issue
  • - Volume 2018
  • - Article ID 4356767
  • - Research Article

Parallel Excitatory and Inhibitory Neural Circuit Pathways Underlie Reward-Based Phasic Neural Responses

Huanyuan Zhou | KongFatt Wong-Lin | Da-Hui Wang
  • Special Issue
  • - Volume 2018
  • - Article ID 5082401
  • - Research Article

Adaptive Neural Networks Control Using Barrier Lyapunov Functions for DC Motor System with Time-Varying State Constraints

Lei Ma | Dapeng Li
  • Special Issue
  • - Volume 2018
  • - Article ID 3039061
  • - Research Article

Application of Federal Kalman Filter with Neural Networks in the Velocity and Attitude Matching of Transfer Alignment

Lijun Song | Zhongxing Duan | ... | Zhe Li
  • Special Issue
  • - Volume 2018
  • - Article ID 3891624
  • - Research Article

Gender and Handedness Prediction from Offline Handwriting Using Convolutional Neural Networks

Ángel Morera | Ángel Sánchez | ... | Ana Belén Moreno
  • Special Issue
  • - Volume 2017
  • - Article ID 5067145
  • - Research Article

Dynamic Traffic Congestion Simulation and Dissipation Control Based on Traffic Flow Theory Model and Neural Network Data Calibration Algorithm

Li Wang | Shimin Lin | ... | Zhifu Li
  • Special Issue
  • - Volume 2017
  • - Article ID 8395252
  • - Research Article

Fault Diagnosis Method of Check Valve Based on Multikernel Cost-Sensitive Extreme Learning Machine

Jun Ma | Jiande Wu | Xiaodong Wang
  • Special Issue
  • - Volume 2017
  • - Article ID 2513815
  • - Research Article

RBF Nonsmooth Control Method for Vibration of Building Structure with Actuator Failure

Jianhui Wang | Chunliang Zhang | ... | Li Zhang
  • Special Issue
  • - Volume 2017
  • - Article ID 5392539
  • - Research Article

Structure Optimization of a Vibration Suppression Device for Underwater Moored Platforms Using CFD and Neural Network

Zhaoyong Mao | Fuliang Zhao
Complexity
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 Journal metrics
Acceptance rate43%
Submission to final decision64 days
Acceptance to publication35 days
CiteScore3.200
Impact Factor2.462
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