Construction and application of a TCN-LSTM-SVM-based time series prediction model for water inflow in coal seam roofs by Xuan LIU, Yadong JI, Kaipeng ZHU, Chunhu ZHAO, Kai LI, Chaofeng LI, Chenhan YUAN, Panpan LI, Pengzhen YAN

“…First, by raw data processing using the TCN framework, this model extracted the dependency between mining footage and water inflow and its dynamic characteristics. …”
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Adaptive deep SVM for detecting early heart disease among cardiac patients by S. N. Netra, N. N. Srinidhi, E. Naresh

“…The accuracy of the designed framework is 96.07%, which is enhanced than the other existing frameworks like CNN-LSTM, DCNN, Adaboost and SVM, respectively. …”
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Reducing False Alarm in Target Sidelobes Using Time-Varying Trajectories in Range-Doppler Diagram With Conditional 3D-DCNN by Jiyeon Choi, Daegun Oh, Youngwook Kim

“…This approach simplifies previous two-step processes into a one-step solution, offering a more efficient framework for drone surveillance systems.…”
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Data-driven personalized marketing strategy optimization based on user behavior modeling and predictive analytics: Sustainable market segmentation and targeting. by Bin Sun

“…In this study, we propose a novel framework called DP-GCN (Deterministic Policy Graph Convolutional Network), which integrates multi-level Graph Convolutional Networks (GCNs) with Deep Deterministic Policy Gradient (DDPG) reinforcement learning to model heterogeneous information networks composed of users, products, and search queries. …”
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A malware classification method based on directed API call relationships. by Cuihua Ma, Zhenwan Li, Haixia Long, Anas Bilal, Xiaowen Liu

“…While some approaches consider the structure of API calls, they typically rely on the Graph Convolutional Network (GCN) framework, which tends to neglect the sequential nature of API interactions. …”
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Spatially-Coupled QLDPC Codes by Siyi Yang, Robert Calderbank

“…This algebraic framework facilitates the construction of new code families. …”
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Application of Artificial Intelligence Technology in Computer Network Security Communication by Fulin Li

“…In order to cope with the frequent challenges of network security issues, a method of applying artificial intelligence technology to computer network security communication is proposed. First, within the framework of computer network communication, an intelligent protocol reverse analysis method is proposed. …”
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A Multi-Task Spatiotemporal Graph Neural Network for Transient Stability and State Prediction in Power Systems by Shuaibo Wang, Xinyuan Xiang, Jie Zhang, Zhuohang Liang, Shufang Li, Peilin Zhong, Jie Zeng, Chenguang Wang

“…To address these challenges, this paper presents a multi-task learning framework based on spatiotemporal graph convolutional networks that efficiently performs both tasks. …”
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A Deep Neural Network-Based Approach to Media Hotspot Discovery by Pan Luo

“…Finally, the text feature representation method based on graph convolutional neural network is combined with the clustering algorithm based on the moving range density maximum selection method to build a deep learning-based media hotspot discovery framework. …”
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ResnetCPS for Power Equipment and Defect Detection by Xingyu Yan, Lixin Jia, Xiao Liao, Wei Cui, Shuangsi Xue, Dapeng Yan, Hui Cao

“…The proposed framework facilitates weight sharing across different layers within the convolutional network, establishing connections between pertinent channels across layers and leveraging the scale invariance inherent in image datasets. …”
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Multi-scale U-like network with attention mechanism for automatic pancreas segmentation. by Yingjing Yan, Defu Zhang

“…Then We use a cascaded framework to increase the accuracy of segmentation results. …”
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Quantum‐inspired Arecanut X‐ray image classification using transfer learning by Praveen M. Naik, Bhawana Rudra

“…A comparative analysis of transfer learning‐based classification, employing both a traditional convolutional neural network (CNN) and an advanced quantum convolutional neural network (QCNN) approach is conducted. …”
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Predicting sport event outcomes using deep learning by Jianxiong Gao, Yi Cheng, Jianwei Gao

“…In this study, we present a deep learning framework that combines a one-dimensional convolutional neural network (1D CNN) with a Transformer architecture to improve prediction accuracy. …”
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Study on the Strategy of Playing Doudizhu Game Based on Multirole Modeling by Shuqin Li, Saisai Li, Hengyang Cao, Kun Meng, Meng Ding

“…This paper proposes a multirole modeling-based card-playing framework. This framework includes three parts: role modeling, cards carrying, and decision-making strategies. …”
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Energy consumption analysis and prediction in exercise training based on accelerometer sensors and deep learning by Zhangjian Guo, Tongling Wang, Shuxun Chi, Li Huang

“…Additionally, by analyzing the relationship between the X, Y, and Z-axis accelerations, overall magnitude, and energy consumption, a multidimensional feature analysis framework is proposed to enhance the model’s comprehensive understanding of motion data. …”
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Quantifying Visual Navigation in Campus Open Spaces Using a Computer Vision Model by Nabil Mohareb, Abdelaziz Ashraf

“…This study presents a framework specifically designed to measure and quantify visual experiences within academic campus environments. …”
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Attention-Driven Hybrid Ensemble Approach With Bayesian Optimization for Accurate Energy Forecasting in Jeju Island’s Renewable Energy System by Muhammad Ali Iqbal, Joon-Min Gil, Soo Kyun Kim

“…To address these challenges, we propose a Attention-driven Bayesian-Optimized Hybrid Ensemble Framework (ABHEF), evaluated on Jeju Island’s energy mix data. …”
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Predictive power demand for energy management of hybrid electric tractors by Christian Varlese, Johannes Konrad, Thomas Volf, Dominik Brunner, Christoph Hametner, Peter Hofmann

“…Based on the real-data framework, the characteristics of the farming cycles and relevant prediction features were constructed and selected. …”
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ADHD detection from EEG signals using GCN based on multi-domain features by Ling Li, Xueyang Guo, Zihan Yang, Yanping Zhao, Xu Liu, Junxian Yang, Yanyan Chen, Xinxian Peng, Lina Han

“…While many researchers have explored automated ADHD detection methods, developing accurate, rapid, and reliable approaches remains challenging.MethodsThis study proposes a graph convolutional neural network (GCN)-based ADHD detection framework utilizing multi-domain electroencephalogram (EEG) features. …”
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Joint fusion of sequences and structures of drugs and targets for identifying targets based on intra and inter cross-attention mechanisms by Xin Zeng, Guang-Peng Su, Wen-Feng Du, Bei Jiang, Yi Li, Zi-Zhong Yang

“…Results We propose MM-IDTarget, a novel deep learning framework that employ a multimodal fusion strategy based on the intra and inter cross-attention mechanisms. …”
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