Operational strategies to the mechanical performance assessment of concrete with the neural network and artificial intelligence by Hadi Faghihmaleki, Mehdi Ghadiri

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SPICE-Level Demonstration of Unsupervised Learning With Spintronic Synapses in Spiking Neural Networks by Salah Daddinounou, Anteneh Gebregiorgis, Said Hamdioui, Elena-Ioana Vatajelu

“…Spiking Neural Networks (SNNs) are Artificial Neural Networks which promise to mimic the biological brain processing with unsupervised online learning capability for various cognitive tasks. …”
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Application of Neural Network in the Stability of Biped Robot and Embedded Control of Walking Mode by Jianrui Zhang, Zhaohui Yuan, Huan Geng, Sheng Dong, Fuli Zhang, Jingchao Li

“…This article aims to study the application of neural networks in the stability of biped robots and the embedded control of walking mode. …”
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Adaptive Control Using Neural Networks and Approximate Models for Nonlinear Dynamic Systems by Khadija El Hamidi, Mostafa Mjahed, Abdeljalil El Kari, Hassan Ayad

“…In this research, a comparative study of two recurrent neural networks, nonlinear autoregressive with exogenous input (NARX) neural network and nonlinear autoregressive moving average (NARMA-L2), and a feedforward neural network (FFNN) is performed for their ability to provide adaptive control of nonlinear systems. …”
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Research for Pedestrian Steel Bridge Design of Neural Network in Structural Model Updating by Rui Zhao, Yuhang Wu, Zehua Feng

“…A reasonable neural network structure is very important for its performance. …”
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On Global Exponential Stability of Discrete-Time Hopfield Neural Networks with Variable Delays by Qiang Zhang, Xiaopeng Wei, Jin Xu

“…Global exponential stability of a class of discrete-time Hopfield neural networks with variable delays is considered. By making use of a difference inequality, a new global exponential stability result is provided. …”
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Battery Energy Forecasting in Electric Vehicle Using Deep Residual Neural Network by Mohamad Reda A. Refaai, Jyothilal Nayak Bharothu, T. V. V. Pavan Kumar, Chodagam Srinivas, M. Sudhakar, Anirudh Bhowmick

“…TCN, a new machine learning technique, combines the advantages of residual neural networks (ResNet) with the computing efficiency of neural networks to produce a technique that is both efficient and effective. …”
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Detection of weeds in vegetables using image classification neural networks and image processing by Huiping Jin, Kang Han, Kang Han, Hongting Xia, Bo Xu, Xiaojun Jin

Subjects: “…image classification neural networks…”
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Distributed Data Mining Based on Deep Neural Network for Wireless Sensor Network by Chunlin Li, Xiaofu Xie, Yuejiang Huang, Hong Wang, Changxi Niu

“…Rising to these challenges, this paper proposes a distributed data mining method based on deep neural network (DNN), by dividing the deep neural network into different layers and putting them into sensors. …”
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Randomized radial basis function neural network for solving multiscale elliptic equations by Yuhang Wu, Ziyuan Liu, Wenjun Sun, Xu Qian

Subjects: “…randomized radial basis function neural network…”
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Early Warning Model of Sports Injury Based on RBF Neural Network Algorithm by Fuxing He

“…In this paper, we use a neural network to realize big data analysis of sports injury data. …”
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Efficient Lane Detection Technique Based on Lightweight Attention Deep Neural Network by Zhiting Yao, Xiyuan Chen

“…This paper proposed an improved attention deep neural network (DNN), a lightweight semantic segmentation architecture catering for efficient computation in low memory, which contains two branches worked in different resolution. …”
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Hourly Forecasting of Solar Photovoltaic Power in Pakistan Using Recurrent Neural Networks by Sohrab Khan, Faheemullah Shaikh, Mokhi Maan Siddiqui, Tanweer Hussain, Laveet Kumar, Afroza Nahar

“…This paper suggests recurrent neural networks (RNNs) as the best-performing forecasting model for PV power output. …”
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Finite-Time Synchronization for Complex-Valued Recurrent Neural Networks with Time Delays by Ziye Zhang, Xiaoping Liu, Chong Lin, Bing Chen

“…This paper focuses on the finite-time synchronization analysis for complex-valued recurrent neural networks with time delays. First, two kinds of common activation functions appearing in the existing references are combined together and more general assumptions are given. …”
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Gender and Handedness Prediction from Offline Handwriting Using Convolutional Neural Networks by Ángel Morera, Ángel Sánchez, José Francisco Vélez, Ana Belén Moreno

“…Our solution is based on convolutional neural networks since these models had proven better capabilities to extract good features when compared to hand-crafted ones. …”
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Schizophrenia recognition based on three-dimensional adaptive graph convolutional neural network by Guimei Yin, Jie Yuan, Yanjun Chen, Guangxing Guo, Dongli Shi, Lin Wang, Zilong Zhao, Yanli Zhao, Manjie Zhang, Yuan Dong, Bin Wang, Shuping Tan

Subjects: “…Graph convolutional neural network…”
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Fuzzy Neural Network-Based Evaluation Algorithm for Ice and Snow Tourism Competitiveness by Ying Zhao, Qinghua Zhu, Jiujun Bai

“…Based on the construction of cloud fuzzy neural network model, the above method is used for experimental comparison analysis, and experiments are conducted through University of California Irvine (UCI) dataset and engineering examples to compare with the traditional cloud model, fuzzy neural network, and BP neural network to analyze the operation efficiency, accuracy rate, and several rules of the algorithm. …”
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Construction of Cognitive Model of Family Education Decision-Making Based on Neural Network by Wenwen Yao, Ying Zhen, Yu Zhang

“…This paper constructs a cognitive model of family training decision-making principally based totally on neural network. Through the assessment of relevant data, they have an effect of the cognitive model of family coaching decision-making mainly based totally on neural neighborhood evaluated from the accuracy, root suggest rectangular error RMSE, and AUC curve. …”
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Improved AHP Model and Neural Network for Consumer Finance Credit Risk Assessment by Yafeng Xi, Qiu Li

“…The data are input into the AHP-LSTM neural network, and the index data are fused with the AHP so as to obtain the risk level and serve as the expected output of the LSTM neural network. …”
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Dendrites endow artificial neural networks with accurate, robust and parameter-efficient learning by Spyridon Chavlis, Panayiota Poirazi

“…Abstract Artificial neural networks (ANNs) are at the core of most Deep Learning (DL) algorithms that successfully tackle complex problems like image recognition, autonomous driving, and natural language processing. …”
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