Fixed-Time Sliding Mode Control for Vehicle Platoon With Input Dead-Zone and Prescribed Performance by Yongqiang Jiang, Yiguang Wang, Xiaojie Li, Xiaoyan Zhan, Xubing Tang

“…Furthermore, Chebyshev neural network (CNN) is adopted to approximate unknown nonlinearities, and new adaptive mechanisms are designed to estimate IDZ slope and external disturbances. …”
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Multimodel Anomaly Identification and Control in Wet Limestone-Gypsum Flue Gas Desulphurization System by Xiaoli Li, Quanbo Liu, Kang Wang, Fuqiang Wang, Guimei Cui, Yang Li

“…In this article, based on process data sampled from 1000 MW unit flue gas desulphurization system in a coal-fired power plant, a multimodel control strategy with multilayer parallel dynamic neural network (MPDNN) is utilized to address the control problem in the context of different anomalies. …”
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Adaptive Fixed-Time Trajectory Tracking Control for Underactuated Hovercraft with Prescribed Performance in the Presence of Model Uncertainties by Mingyu Fu, Tan Zhang, Fuguang Ding, Duansong Wang

“…In addition, by combining the Lyapunov direct method and the adaptive radial basis function neural network (ARBFNN), the actual control laws are designed to ensure that the velocity tracking errors converge to a small region containing zero while handling model uncertainties and external disturbances effectively. …”
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Time Series Prediction Based on Complex-Valued S-System Model by Bin Yang, Wenzheng Bao, Yuehui Chen

“…The experiment results show that the predicted data are very close to the target ones and our method could obtain the better RMSE, MAP, MAPE, POCID, R2, and ARV performances than ARIMA, radial basis function neural network (RBFNN), flexible neural tree (FNT), ordinary differential equation (ODE), and S-system.…”
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Steganographer identification of JPEG image based on feature selection and graph convolutional representation by Qianqian ZHANG, Yi ZHANG, Hao LI, Yuanyuan MA, Xiangyang LUO

“…Aiming at the problem that the feature dimension of JPEG image steganalysis is too high, which leads to the complexity of distance calculation between users and a decrease in the identification performance of the steganographer, a method for steganographer recognition based on feature selection and graph convolutional representation was proposed.Firstly, the steganalysis features of the user’s images were extracted, and the feature subset with highseparability was selected.Then, the users were represented as a graph, and the features of users were obtained by training the graph convolutional neural network.Finally, because inter-class separability and intra-class aggregation were considered, the features of users that could capture the differences between users were learned.For steganographers who use JPEG steganography, such as nsF5, UED, J-UNIWARD, and so on, to embed secret information in images, the proposed method can reduce the feature dimensions and computing.The identification accuracy of various payloads can reach more than 80.4%, and it has an obvious advantage at the low payload.…”
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ARM-Cortex M3-Based Two-Wheel Robot for Assessing Grid Cell Model of Medial Entorhinal Cortex: Progress towards Building Robots with Biologically Inspired Navigation-Cognitive Maps by J. Cuneo, L. Barboni, N. Blanco, M. del Castillo, J. Quagliotti

“…It is considered that the results of this work provide an insight into achieving an enhanced embedded systems design for emulating and understanding mathematical neural network models to be used as biologically inspired navigation system for robots.…”
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Sizing Control and Hardware Implementation of a Hybrid Wind-Solar Power System, Based on an ANN Approach, for Pumping Water by Ons Zarrad, Mohamed Ali Hajjaji, Aymen Jemaa, Mohamed Nejib Mansouri

“…The first contribution of our work is the utilization of an artificial neural network controller to command, at fixed atmospheric conditions, the maximum power point. …”
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Real-Time Resource Allocation Algorithm for the Quasi-Two-Dimensional Mobile Delay/Disrupt Tolerant Networking by Ying Wang, Yonghui Zhang

“…However, schemes based on neural network and genetic algorithms are of computational complexity that is not applied to real-time applications. …”
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Charbonnier Quasi Hyperbolic Momentum Spline Based Incremental Strategy for Nonlinear Distributed Active Noise Control by Rajapantula Kranthi, Vasundhara, Asutosh Kar, Mads Grasboll Christensen

“…In such environments, functional link neural network (FLN) and adaptive exponential FLN techniques improve the performance of distributed active noise control systems. …”
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Graph-Based Node Finding in Big Complex Contextual Social Graphs by Keshou Wu, Guanfeng Liu, Junwen Lu

“…Targeting this challenging problem, we propose a recurrent neural network- (RNN-) based Monte Carlo Tree Search algorithm (RN-MCTS), which automatically balances exploring new possible matches and extending existing matches. …”
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Prediction of optimal growth parameters of barley seedling based on Kalman filter and multilayer perceptron by Yunlong HUANG, Zhengquan LI, Yujia SUN

“…In order to improve the quality and planting efficiency of barley seedlings in the growth chamber, the Kalman filter algorithm was firstly used to process the data collected by the sensor, which effectively reduced the influence of environmental factors and the error of the sensor itself, improved the accuracy of the collected data, and ensured the precise control in the growth chamber and accurate test data.Then multiple nonlinear regression, radial basis function and multilayer perceptron neural network were used to analyze the average growth height, seedling weight and seed weight of barley seeds about 160 hours after germination under different conditions.The drying ratio was analyzed and compared.The results show that the multi-layer perceptron network model fits the data best.Using this model to predict the average height of barley seedlings and the ratio of seedling weight of barley seedlings in the optimal environment is basically consistent with the actual planting effect, which provides a certain reference for the planting of barley seedlings in the growth chamber.…”
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Parallel LSTM-Based Regional Integrated Energy System Multienergy Source-Load Information Interactive Energy Prediction by Bo Wang, Liming Zhang, Hengrui Ma, Hongxia Wang, Shaohua Wan

“…Then, based on the long short-term memory depth neural network time series prediction, parallel long short-term memory multitask learning model is established to achieve horizontal interaction among multienergy systems and based on user-driven behavioral data to achieve vertical interaction between source and load. …”
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Exploring Coevolution of Emotional Contagion and Behavior for Microblog Sentiment Analysis: A Deep Learning Architecture by Qi Zhang, Zufan Zhang, Maobin Yang, Lianxiang Zhu

“…Next, a CNN-BiLSTM-Attention network (the convolutional neural network and bidirectional long short-term memory network with a multihead attention mechanism) is designed to analyze the sentiment analysis of target and similar microblogs. …”
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Prescribed Performance Tracking Control for Nonlinear Stochastic Time-Delay Systems with Multiple Constraints by Man Zhang, Ru Chang, Ying Wang

“…The error feedback controller was constructed by combining the backstepping technique, the dynamic surface technique, the neural network approximation technique, and the adaptive control method. …”
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LIFE PREDICTION OF ROLLING BEARING BASED ON MULTI-RESOLUTION SINGULAR VALUE DECOMPOSITION AND ECNN-LSTM by XIONG Jun, CHEN Lin, WANG ShangQing

“…Secondly,a high-efficiency channel attention mechanism module was added to the two-layer one-dimensional convolutional neural network structure,and the convolution kernel was adaptively adjusted for multi-channel interaction without dimension reduction,so as to fully extract bearing degradation characteristics and establish effective life degradation indicators. …”
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Date recognition based on multi feature extraction by Min WANG, Jia WU, Shuo SUN, Sheng LI, Kang WANG

“…Drug production date and expiration date are important indicators to measure the safety and effectiveness of drugs.The production date and validity period of liquid drugs in vertical bags are printed with numbers of 0～9.The recognition of the drug date of the hospital needs to meet the requirements of high speed and accuracy.The conventional template matching method and neural network recognition method have large amount of calculation and complex training.A drug date recognition method was proposed based on multi feature extraction.The combination of vertical line feature and three features for fine feature extraction of different digital characters has advantages of small amount of calculation and fast recognition speed.Compared with the recognition method of single extracted feature, it can effectively distinguish 10 different numbers, especially suitable for numbers of similar shape.It can provide patients with safe drug use guarantee, improve the management mode of the medical staff, improve the work efficiency, so as to improve the level of the pharmaceutical service of the hospital.…”
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An Improved Gesture Segmentation Method for Gesture Recognition Based on CNN and YCbCr by Yan Luo, Gaoxiang Cui, Deguang Li

“…In order to enhance the features of gesture recognition, firstly, the hand skin color is filtered through YCbCr color space to separate the gesture region to be recognized, and the Gaussian filter is used to process the noise of gesture edge; secondly, the morphological gray open operation is used to process the gesture data, the watershed algorithm based on marker is used to segment the gesture contour, and the eight-connected filling algorithm is used to enhance the gesture features; finally, the convolution neural network is used to recognize the gesture data set with fast convergence speed. …”
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Sinkhole attack detection based on fusion of ACO and P2P trust model in WSN by Wumaier HENIGULI

“…The analysis shows that the proposed algorithm need less matching search times in matching process than binary search algorithm and the rules matching based neural network（RMNN）algorithm，which indicates that it has improved the efficiency of the algorithm. …”
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Noise and Synchronization Analysis of the Cold-Receptor Neuronal Network Model by Ying Du, Rubin Wang, Jingyi Qu

“…This paper analyzes the dynamics of the cold receptor neural network model. First, it examines noise effects on neuronal stimulus in the model. …”
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Research on geomagnetic indoor high-precision positioning algorithm based on generative model by Shuai MA, Ke PEI, Huayan QI, Hang LI, Wen CAO, Hongmei WANG, Hailiang XIONG, Shiyin LI

“…Aiming at the current bottleneck of constructing a fine geomagnetic fingerprint library that required a lot of labor costs, two generative models called the conditional variational autoencoder and the conditional confrontational generative network were proposed, which could collect a small number of data samples for a given location, and generate pseudo-label fingerprints.At the same time, in order to solve the problem of low positioning accuracy of single-point geomagnetic fingerprints, a geomagnetic sequence positioning algorithm based on attention mechanism of convolutional neural network-gated recurrent unit was designed, which could effectively use the spatial and temporal characteristics of fingerprints to achieve precise positioning.In addition, a real-time, portable mobile terminal data collection and positioning system was also designed and built.The actual test shows that the proposed model can effectively construct the available geomagnetic fingerprint database, and the average error of the proposed algorithm can reach 0.16 m.…”
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