Target detection technology of coal mine wheeled robot combining improved CNN and self attention mechanism by Junfei TANG, Hailong XING, Su LI, Taotao ZHANG, Heng LIU, Shiyu YAO

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A DQN-Based Algorithm for Operational Optimization of Freight Trains in Long Steep Downhill Sections by HE Zhiyu, LI Yinan, LI Hui, JI Zhijun

“…This study proposes a deep Q-network (DQN) based intelligent curve generation algorithm for operational optimization in these sections. …”
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An adaptive hierarchical hybrid kernel ELM optimized by aquila optimizer algorithm for bearing fault diagnosis by Hao Yan, Liangliang Shang, Wan Chen, Mengyao Jiang, Tianqi lu, Fei Li

“…Subsequently, the hierarchical hybrid kernel extreme learning machine (HHKELM) is refined through an enhanced Aquila Optimizer (AO) algorithm, which iteratively optimizes the kernel hyperparameter combination. …”
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Simulation of incremental update of electronic document information based on big data technology by Zhiyuan Jin, Qi Zhang, Tiejun Pan

“…To address this issue, this research investigates related incremental update models based on big data technology and deep learning algorithms. The feedforward neural network can learn data features quickly and is suitable for incremental update model construction. …”
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Neural Network for Underwater Fish Image Segmentation Using an Enhanced Feature Pyramid Convolutional Architecture by Guang Yang, Junyi Yang, Wenyao Fan, Donghe Yang

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HybridFormer: a convolutional neural network-Transformer architecture for low dose computed tomography image denoising by Shanaz Sharmin Jui, Zhitao Guo, Rending Jiang, Jiale Liu, Bohua Li

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Research on High-Precision Motion Planning of Large Multi-Arm Rock Drilling Robot Based on Multi-Strategy Sampling Rapidly Exploring Random Tree* by Qiaoyu Xu, Yansong Lin

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Object Detection Algorithm Based on Feature Enhancement and Anchor-object Matching by LI Cheng-yan, ZHAO Shuai, CHE Zi-xuan

“…In the detector part of the algorithm, the Anchor-object matching method combined with the SSD multi-layer feature map is used to construct the corresponding Anchor package for each detection target. …”
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Research on Point Cloud Registration and Stitching Fusion Algorithm Based on GCN-PRFNet by Wenhao Zeng, Gongbing Su, Zixuan Su, Rui Li, Jun Chen

“…., the accuracy of point cloud registration and stitching in robot navigation directly affects the accuracy of map construction. Many researchers have proposed various algorithms for deep learning-based point cloud registration and stitching methods with good performance, and although there are end-to-end methods that have made progress, they still have limitations in local feature fusion efficiency and geometric detail retention. …”
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Dance video action recognition algorithm based on improved hypergraph convolutional networks by Ni Zhen, Yiyi Jiang

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Heterogeneous Graph Neural-Network-Based Scheduling Optimization for Multi-Product and Variable-Batch Production in Flexible Job Shops by Yuxin Peng, Youlong Lyu, Jie Zhang, Ying Chu

“…In view of the Flexible Job-shop Scheduling Problem (FJSP) under multi-product and variable-batch production modes, this paper presents an intelligent scheduling approach based on a heterogeneity-enhanced graph neural network combined with deep reinforcement learning. By constructing a heterogeneity-enhanced incidence graph to dynamically represent the scheduling state, the proposed method effectively captures both the dependencies among operations and the interaction features between operations and machines. …”
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A new method for determining factors Influencing productivity of deep coalbed methane vertical cluster wells by HUANG Li, XIONG Xianyue, WANG Feng, SUN Xiongwei, ZHANG Yixin, ZHAO Longmei, SHI Shi, ZHANG Wen, ZHAO Haoyang, JI Liang, DENG Lin

“…This method centered on the initial meter gas production index and integrated multiple machine-learning algorithms. The results showed that: 1） The Beggs & Bill model and Gray model exhibited poor applicability for predicting the bottom-hole flowing pressure of deep CBM wells, while the single-phase gas model demonstrated reduced overall error as water production declined. …”
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Question-matching approach based on gradual machine learning by Xuejian HE, Anqi CHEN, Zhiqiang GUO, Zhiru WANG, Qun CHEN

“…In addition, our work on the GML solution is orthogonal to existing deep learning-based question-matching algorithms because our solution can easily accommodates and leverages other deep language models.…”
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Energy consumption reduction method for green buildings based on human thermal discomfort posture recognition algorithm by Shijiu Song, Li Zhou

“…The aim of this study is to improve the accuracy of human thermal discomfort pose recognition algorithms. This study first extracts human key points on the ground of bone key points, then normalizes the data, and finally constructs a human thermal uncomfortable posture recognition algorithm on the ground of deep learning technology. …”
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Research on High Arch Dam Deformation Monitoring Model with Deep Capturing Related Features in Factor-time Dimensions by XUE Jianghan, ZHANG Pengtao, TIAN Jichen, LU Xiang, CHEN Jiankang, Guo Yinju

“…However, at the present stage, the dam prediction model based on machine learning mostly adopts the means of data preprocessing, using optimization algorithm, and using the model's characteristics to stack multiple models, lacking in in-depth consideration of the physical mechanism of dam deformation. …”
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River total dissolved gas prediction using a hybrid greedy-stepwise feature selection and bidirectional long short-term memory model by Khabat Khosravi, Salim Heddam, Changhyun Jun, Sayed M. Bateni, Dongkyun Kim, Essam Heggy

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A Capsule Decision Neural Network Based on Transfer Learning for EEG Signal Classification by Wei Zhang, Xianlun Tang, Xiaoyuan Dang, Mengzhou Wang

“…A kind of capsule decision neural network (CDNN) based on transfer learning is proposed. In order to solve the problem of feature distortion caused by EEG feature extraction algorithm, a deep capsule decision network was constructed. …”
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Research on productivity prediction method of infilling well based on improved LSTM neural network: A case study of the middle-deep shale gas in South Sichuan by GUAN Wenjie, PENG Xiaolong, ZHU Suyang, YANG Chen, PENG Zhen, MA Xiaoran

“…Example studies show that the GWO-optimised LSTM neural network model achieves rapid convergence with a preset learning rate of 0.002 and 450 iterations, ultimately reaching a performance index of 0.923. …”
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Automatic Differentiation‐Based Full Waveform Inversion With Flexible Workflows by Feng Liu, Haipeng Li, Guangyuan Zou, Junlun Li

“…Abstract Full waveform inversion (FWI) is able to construct high‐resolution subsurface models by iteratively minimizing discrepancies between observed and simulated seismic data. …”
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Heterogeneous Multi-Agent Task Planning Method in Complex Marine Environment by Shoumin Wang, Ning Niu, Zhichao Wang, Yaxuan Lv, Jing Zhang

“…To enable collaborative scouting / strike / assessment of underwater time-sensitive targets by heterogeneous multi-agent systems, in this study a heterogeneous multi-agent collaborative decision-making method is proposed based on deep reinforcement learning. The method integrates two core learning frameworks one for heterogeneous multi-agent task allocation and one for single-agent multi-task learning. …”
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