A Study on Predicting Key Times in the Takeout System’s Order Fulfillment Process by Dongyi Hu, Wei Deng, Zilong Jiang, Yong Shi

“…This paper first proposes a time chain simulation method, which simulates the order fulfillment in segments with an incremental process by combining dynamic and static information in the data. …”
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Research on Industrial Process Fault Diagnosis Method Based on DMCA-BiGRUN by Feng Yu, Changzhou Zhang, Jihan Li

“…Finally, a bidirectional gated recurrent unit (BiGRU) is introduced to process sequences in both directions, which can effectively learn the long-range temporal dependencies of sequence data. …”
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A novel transformer-based dual attention architecture for the prediction of financial time series by Anita Hadizadeh, Mohammad Jafar Tarokh, Majid Mirzaee Ghazani

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Developing an explainable deep learning module based on the LSTM framework for flood prediction by Zhi Zhang, Dagang Wang, Yiwen Mei, Jinxin Zhu, Xusha Xiao

“…Our approach incorporates a simplified gated module, which is interposed between the input data and the LSTM network, providing a transparent view of the module’s pattern recognition process. …”
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A New Hybrid Intelligent Method for Accurate Short Term Electric Power Production Forecasting From Uncertain Renewable Energy Resources by Gholamreza Memarzadeh, Farshid Keynia, Faezeh Amirteimoury, Rasoul Memarzadeh, Hossein Noori

“…The proposed model integrates various techniques, including Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), Autoregressive Integrated Moving Average (ARIMA), Multi-Layer Perceptron (MLP), and Adaptive Neuro-Fuzzy Inference System (ANFIS). …”
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A Signal Processing-Guided Deep Learning Framework for Wind Shear Prediction on Airport Runways by Afaq Khattak, Pak-wai Chan, Feng Chen, Hashem Alyami, Masoud Alajmi

“…This study introduces a hybrid framework for short-term wind shear prediction based on data collected from Doppler LiDAR systems positioned near the central and south runways of the HKIA. …”
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Real-Time System Prediction for Heart Rate Using Deep Learning and Stream Processing Platforms by Abdullah Alharbi, Wael Alosaimi, Radhya Sahal, Hager Saleh

“…., artificial intelligence and stream processing technologies) allows healthcare sectors to consolidate and analyze massive health-based data to discover risks by making more accurate predictions. …”
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Data-driven dynamic friction models based on Recurrent Neural Networks by Gaëtan Cortes, Joaquin Garcia-Suarez

“…In this concise contribution, it is demonstrated that Recurrent Neural Networks (RNNs) based on Gated Recurrent Unit (GRU) architecture, possess the capability to learn the complex dynamics of rate-and-state friction (RSF) laws from synthetic data. …”
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Optimizing quantum convolutional neural network architectures for arbitrary data dimension by Changwon Lee, Israel F. Araujo, Dongha Kim, Junghan Lee, Siheon Park, Ju-Young Ryu, Ju-Young Ryu, Daniel K. Park, Daniel K. Park

“…The number of input qubits determines the dimensions (i.e., the number of features) of the input data that can be processed, restricting the applicability of QCNN algorithms to real-world data. …”
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Super-resolution of 3D medical images by generative adversarial networks with long and short-term memory and attention by Qiong Zhang, Yiliu Hang, Fang Wu, Shentao Wang, Yue Hong

“…Deep convolutional networks perform well in extracting spatial features, but are less capable for processing sequence data compared to recurrent convolutional networks. …”
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TREE: Bridging the gap between reconfigurable computing and secure execution by Sérgio Pereira, Tiago Gomes, Jorge Cabral, Sandro Pinto

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An Ultrawide Bandwidth Digital Backend System Based on PFB Algorithm for QTT by Hai-long Zhang, Ya-zhou Zhang, Shao-cong Guo, Xu Du, Na Wang, Jie Wang, Xin-chen Ye, Han Wu, Jian Li, Xin Pei, Qiao Meng

“…We developed the Ultra Wide bandwidth Low-frequency pulsar data process PIPEline, which realized the real-time processing and data packaging of massive pulsar signals. …”
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Evaluation of Single-Event Effect Current-Carrier Mapping Based on Experimental Data by Mengtian Bao, Ying Wang, Jianqun Yang, Xingji Li

“…Firstly, a special data fluctuate–collapse transform analysis method is proposed according to the temporal characteristics of the gate/drain current. …”
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Personalized Recommendation Model Based on Improved GRU Network in Big Data Environment by Hui Guo, Zheng Guo, Zhihong Liu

“…To address the diversity of user preferences and dynamic changes of interests in the personalized recommendation scenario, a personalized recommendation model based on the improved gated recurrent unit (GRU) network in a big data environment is proposed. …”
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Low‐power fast Fourier transform hardware architecture combining a split‐radix butterfly and efficient adder compressors by Guilherme Ferreira, Guilherme Paim, Leandro M. G. Rocha, Gustavo M. Santana, Renato H. Neuenfeld, Eduardo A. C. Costa, Sergio Bampi

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Real-time traffic enhancement scheduling for train communication networks based on TSN by Deqiang He, Zeqian Chen, Daliang Sun, Zhenzhen Jin, Yanjun Chen, Rui Ma, Chen Liang

“…Then, the K shortest path routing algorithm based on load balancing provides the optimal routing for the scheduling process. Finally, the adaptive switch queue selection mechanism is introduced to solve the aggregation flow conflict problem effectively, queue resources are properly allocated, and the gate control list (GCL) of each frame in the queue is obtained. …”
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Squeeze-Excitation Transformer With Residual Bi-GRU Model for Distributed UWB Based Continuous Gesture Recognition and its Application to Human-UAV Interactions by Chih-Lyang Hwang, Felix Gunawan, Chih-Han Chen

“…It presents distinguished improvements in processing continuous data streams for real-time applications. …”
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Mining Travel Time of Airport Ferry Network Based on Historical Trajectory Data by Cong Ding, Jun Bi, Dongfan Xie, Xiaomei Zhao, Yi Liu

“…Then, this paper uses big data processing technology to identify the travel time between regional connection nodes by data fusion through the temporal and spatial relationship between flight schedule and ferry vehicle GPS travel trajectory. …”
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Intelligent analysis algorithm for power engineering data based on improved BiLSTM by Yuanyuan Xu, Jiapeng Yang, Xin Cai

“…Abstract Traditional BiLSTM (Bidirectional Long Short-Term Memory) has limited processing capabilities for long-time series, insufficient adaptability to the characteristics of power engineering data, and inadequate accuracy in predicting problems in specific application scenarios. …”
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Establishing a GRU-GCN coordination-based prediction model for miRNA-disease associations by Kai-Cheng Chuang, Ping-Sung Cheng, Yu-Hung Tsai, Meng-Hsiun Tsai

“…To improve the accuracy of prediction in this model, we introduced two labeling strategies, weight-based and majority-based definitions, to classify miRNA-disease associations. After preprocessing, data was trained with a novel model combining gated recurrent units (GRU) and graph convolutional network (GCN) to predict the level of miRNA-disease associations. …”
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