Innovation of Teaching Method of Digital Media Art Based on Convolutional Neural Network by Yumei Liu

“…In order to improve the effect of digital media art teaching, this study combines the neural network algorithm to carry out the innovation of digital media art teaching resource management and teaching method innovation. …”
Get full text

Children Tracking System Based on ZigBee Wireless Network and Neural Network by Nadia Ahmed, Sadik Kamel Gharghan, Ammar Hussein Mutlag, M. G. M. Abdolrasol

Subjects: Get full text

Application of Quantum Recurrent Neural Network in Low-Resource Language Text Classification by Wenbin Yu, Lei Yin, Chengjun Zhang, Yadang Chen, Alex X. Liu

Subjects: “…quantum recurrent neural network…”
Get full text

Application of Artificial Neural Network for Damage Detection in Planetary Gearbox of Wind Turbine by Marcin Strączkiewicz, Tomasz Barszcz

“…To overcome this obstacle, it is proposed to detect a fault development with Artificial Neural Network (ANN) and further observation of linear regression parameters calculated on the estimation error between healthy and unknown condition. …”
Get full text

Determining the Thermal Conductivity of Clay during the Freezing Process by Artificial Neural Network by Xiuling Ren, Yanhui You, Qihao Yu, Guike Zhang, Pan Yue, Mingyang Jin

“…By measuring the thermal conductivity of clay using a transient hot-wire method in the laboratory, the influential factors of the thermal conductivity of soils during the freezing process were analyzed, and a predictive model of thermal conductivity was developed with an artificial neural network (ANN) technology. The results show that the variation of thermal conductivity can be divided into three stages with decreasing temperature, positive temperature stage, transition stage, and negative temperature stage. …”
Get full text

Utilizing Artificial Neural Network for Load Prediction Caused by Fluid Sloshing in Tanks by Hossein Goudarzvand Chegini, Gholamreza Zarepour

“…The backpropagation of the error algorithm was then used to apply the two multilayer feed-forward neural networks and the recurrent neural network. The findings of the SPH process are employed in the training and testing of neural networks. …”
Get full text

Optimization of power system load forecasting and scheduling based on artificial neural networks by Jiangbo Jing, Hongyu Di, Ting Wang, Ning Jiang, Zhaoyang Xiang

Subjects: “…Artificial neural networks…”
Get full text

Wavelet Denoising of Vehicle Platform Vibration Signal Based on Threshold Neural Network by Mingzhu Li, Zhiqian Wang, Jun Luo, Yusheng Liu, Sheng Cai

“…A method to denoise the VPVS is proposed based on the wavelet coefficients thresholding and threshold neural network (TNN). According to the characteristics of VPVS, a novel thresholding function is constructed, and then its optimized threshold is selected through unsupervised learning of TNN. …”
Get full text

Application of Correlation Analysis-Neural Network Model in Water Consumption Prediction in Ningxia by DOU Miao, LI Jinyan, CUI Lanbo, WEI Yimin, SU Huiyan, LI Chaochao

Subjects: “…multi-layer perceptron neural network…”
Get full text

Graph Neural Networks in Brain Connectivity Studies: Methods, Challenges, and Future Directions by Hamed Mohammadi, Waldemar Karwowski

Subjects: “…graph neural networks (GNNs)…”
Get full text

A multiobjective continuation method to compute the regularization path of deep neural networks by Augustina Chidinma Amakor, Konstantin Sonntag, Sebastian Peitz

“…Sparsity is a highly desired feature in deep neural networks (DNNs) since it ensures numerical efficiency, improves the interpretability (due to the smaller number of relevant features), and robustness. …”
Get full text

Relationship between Cognitive Learning Psychological Classification and Neural Network Design Elements by Xing Yang, Tingjun Yong, Meihua Li, Wenying Wang, Huichun Xie, Jinping Du

“…This article first analyzes the research background of the design elements of cognitive psychology and neural networks at home and abroad, roughly understands the research status and research background of these two courses at home and abroad, and discusses the application of cognitive psychology to neural networks. …”
Get full text

Optimalisasi Hyper Parameter Convolutional Neural Networks Menggunakan Ant Colony Optimization by Fian Yulio Santoso, Eko Sediyono, Hindriyanto Dwi Purnomo

Subjects: Get full text

Neural Network L1 Adaptive Control of MIMO Systems with Nonlinear Uncertainty by Hong-tao Zhen, Xiao-hui Qi, Jie Li, Qing-min Tian

“…The auxiliary compensation controller is designed to approximate the unknown nonlinear functions by MIMO RBF neural networks to suppress the influence of uncertainties. …”
Get full text

High-Performance Inverse Artificial Neural Network Controller for Asynchronous Motor Control by Benyekhlef Kada, Mourad Hebali, Ibrahim Farouk Bouguenna, Benaoumeur Ibari, Menouer Bennaoum

“…These inverse artificial neural networks have been learned from conventional control system (PI controller and vector control) data using MATLAB software. …”
Get full text

Neural network as a mirror of social attitudes: analysis of distortions in generative images by A. G. Tertyshnikova, U. O. Pavlova, M. D. Starovoytova

“…The article is devoted to the consideration of neural network generative technologies as a marker of social stereotypes and attitudes. …”
Get full text

DIAGNOSIS AND PREDICTION OF CHOLECYSTITIS DEVELOPMENT ON THE BASIS OF NEURAL NETWORK ANALYSIS OF RISK FACTORS by V. A. Lazarenko, A. E. Antonov

Subjects: “…artificial neural network…”
Get full text

Study on the Bearing Fault Diagnosis based on Feature Selection and Probabilistic Neural Network by Liu Yunzhe, Hu Jinhai, Ren Litong, Yao Kaixiang, Duan Jinfeng, Chen Lin

“…The bearing simulation fault experiment data is applied for verification,the results prove that compared with diagnosis techniques of BP neural network and support vector machines,the PNN is higher in the respect of diagnosis accuracy grade. …”
Get full text

Electromagnetic signal modulation recognition technology based on lightweight deep neural network by Sicheng ZHANG, Yun LIN, Ya TU, Shiwen Mao

“…In response to the trend that in the 6th generation wireless (6G) era,mobile communications and artificial intelligence will be closely integrated,and a huge number of edge intelligent signal processing nodes will be deployed,an efficient and intelligent electromagnetic signal recognition model was proposed,which could be deployed on resource-constrained edge devices.The constellation diagram of electromagnetic signal was firstly drawn to visualize electromagnetic signal as a two-dimensional image,and color the constellation diagram according to the normalized point density to achieve feature enhancement.Then,a binary deep neural network was adopted to recognize the colored constellation diagrams.It was shown that the approach can guarantee a high recognition accuracy,which significantly reduced the model storage and calculation costs.For verification,the proposed approach was applied to the problem of electromagnetic signal modulation recognition.The experiment uses eight commonly used digital modulation signals and selects additive white Gaussian noise as the channel environment.The experimental results show that the scheme can achieve a comprehensive recognition rate of 96.1% under the noise condition of -6～6 dB,while the size of the network model is only 166 KB.Further,the execution time,when executed on a Raspberry Pi 4B,is only 290 ms.Compared to a full-precision network of the same scale,the accuracy is increased by 0.6%,the model is reduced to <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML"> <mfrac> <mtext>1</mtext> <mrow> <mtext>26</mtext><mo>.…”
Get full text

Image Edge Detection Algorithm Based on Fuzzy Radial Basis Neural Network by Lin Feng, Jian Wang, Chao Ding

Get full text