Routing lookup algorithm based on parallel BP neural network by Xiao-bo XU, Kang-feng ZHENG, Dan LI, Yi-xian YANG, IUXin-xin N

Subjects: “…neural network…”
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Transverse-layer partitioning of artificial neural networks for image classification by N.A. Vershkov, M.G. Babenko, N.N. Kuchukov, V.A. Kuchukov, N.N. Kucherov

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Intrusion detection scheme based on neural network in vehicle network by Yi-liang LIU, Ya-li SHI, Hao FENG, Liang-min WANG

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Convolutional Neural Networks for Software Defect Categorization: An Empirical Validation by Ruchika Malhotra, Madhukar Cherukuri

“…Leveraging the prevailing advancements in computational power and storage capacity, the study present a novel defect categorization model built upon Convolutional Neural Networks (CNNs). Extensive experiments were carried out on defect datasets from five Android operating system application modules, leading to the creation of 60 SDC models (5 datasets x 4 feature sets x 3 approaches). …”
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THE USE OF NEURAL NETWORKS TO FORECAST THE NUMBER OF ROAD ACCIDENTS IN POLAND by Piotr GORZELANCZYK

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Speech Separation Using Convolutional Neural Network and Attention Mechanism by Chun-Miao Yuan, Xue-Mei Sun, Hu Zhao

“…By analyzing the characteristics of the convolutional neural network and attention mechanism, it can be found that the convolutional neural network can effectively extract low-dimensional features and mine the spatiotemporal structure information in the speech signals, and the attention mechanism can reduce the loss of sequence information. …”
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Nonlinear Autoregressive Neural Network for Antimicrobial Waste Water Treatment by Anwer Mustafa Hilal, Mashael M. Asiri, Shaha Al-Otaibi, Faisal Mohammed Nafie, Amal Al-Rasheed, Mohammed Rizwanullah, Ishfaq Yaseen, Abdelwahed Motwakel

“…In addition, the proposed method use the learning under supervision technique of a nonlinear autoregressive for estimating the CO2 concentration and flows in units of rate of a reaction characteristics, an exogenous (NARX) neural network model with two activation functions was used (Log-sigmoid and hyperbolic tangent) and for both the findings of a TC and SMX absorption simulations showed the random forest performed support vector tree and nonlinear autoregressive exogenous neural networks and machine learning methods. …”
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Pansharpening Techniques: Optimizing the Loss Function for Convolutional Neural Networks by Rocco Restaino

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Assessment of Artificial Neural Networks for Hourly Solar Radiation Prediction by Tamer Khatib, Azah Mohamed, K. Sopian, M. Mahmoud

“…This paper presents an assessment for the artificial neural network (ANN) based approach for hourly solar radiation prediction. …”
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Neuromorphic, physics-informed spiking neural network for molecular dynamics by Vuong Van Pham, Temoor Muther, Amirmasoud Kalantari Dahaghi

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Scalable Low Power Accelerator for Sparse Recurrent Neural Network by Panshi JIN, Junjie LI, Jingyi WANG, Pengchong LI, Lei XING, Xiaodong LI

“…The use of edge computing devices in bank outlets for passenger flow analysis, security protection, risk prevention and control is increasingly widespread, among which the performance and power consumption of AI reasoning chips have become a very important factor in the selection of edge computing devices.Aiming at the problems of recurrent neural network, such as high power consumption, weak reasoning performance and low energy efficiency, which were caused by data dependence and low data reusability, this paper realized a sparse RNN low-power accelerator with scalable voltage by using FPGA, and verifies it on the edge design and calculation equipment.Firstly, the sparse -RNN was analyzed and the processing array was designed by network compression.Secondly, due to the unbalanced workload of sparse RNN, it introduced voltage scaling method to maintain low power consumption and high throughput.Experiments show that this method could significantly improve the RNN reasoning speed of the system and reduce the processing power consumption of the chip.…”
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Application of Optimized BP Neural Network In Financial Alert System by Qiaoyi Gao

“…Based on this, main body of a book studies and analyzes the request of optimized BP neural network in financial alert system. Based on the financial early warning and a brief analysis of the development requirements of BP neural network, this paper establishes a financial early warning model for BP neural network. …”
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Estimation of Approximating Rate for Neural Network inLwp Spaces by Jian-Jun Wang, Chan-Yun Yang, Jia Jing

“…The results obtained are helpful in understanding the approximation capability and topology construction of the sigmoidal neural networks.…”
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Study on Ductility of Ti Aluminide Using Artificial Neural Network by R. K. Gupta, Rama Mehta, Vijaya Agarwala, Bhanu Pant, P. P. Sinha

“…Using the reported data, the present paper aims to optimize the experimental conditions through computational modeling using artificial neural network (ANN). Ductility database were prepared, and three parameters, namely, alloy type, grain size, and heat treatment cycle were selected for modeling. …”
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Efficient Artificial Neural Network for Smart Grid Stability Prediction by Saeed Mohsen, Mohit Bajaj, Hossam Kotb, Mukesh Pushkarna, Sadam Alphonse, Sherif S. M. Ghoneim

“…From this perspective, this process is too much time consuming, thus it should predict a smart grid stability via artificial intelligence (e.g., neural networks). Recent advances in the accuracy of neural network have effective solutions to solving the smart grid stability prediction issues, but it remains necessary to develop high performance neural networks that give higher accuracy. …”
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Improving deep convolutional neural networks with mixed maxout units by Hui-zhen ZHAO, Fu-xian LIU, Long-yue LI, Chang LUO

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Neural network decoder for near-term surface-code experiments by Boris M. Varbanov, Marc Serra-Peralta, David Byfield, Barbara M. Terhal

“…Neural network decoders can achieve a lower logical error rate compared to conventional decoders, like minimum-weight perfect matching, when decoding the surface code. …”
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Adversarial attack and defense on graph neural networks: a survey by Jinyin CHEN, Dunjie ZHANG, Guohan HUANG, Xiang LIN, Liang BAO

Subjects: “…graph neural networks…”
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An emotional neural network based approach for wind power prediction by Guoling ZHANG

Subjects: “…emotional neural network…”
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Adaptive Neural Network Motion Control of Manipulators with Experimental Evaluations by S. Puga-Guzmán, J. Moreno-Valenzuela, V. Santibáñez

“…With the aim of estimating the desired torque, a two-layer neural network is used. Then, adaptation laws for the neural network weights are derived. …”
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