本期由北京科技大学罗熊教授，英国赫尔大学程永强教授，中南大学廖志芳教授， 三位客座编辑组建了"Machine Learning-Guided Intelligent Modeling with Its Industrial Applications" 特刊。
本期特刊精选了16篇文章，汇集了机器学习在工业应用方面的最新进展，希望能为相关领域学者提供新的思路和参考，欢迎阅读。
机器学习引导下的智能建模及其工业应用特刊介绍
Title:
Introduction to the Special Issue on Machine Learning-Guided Intelligent Modeling with Its Industrial Applications
Authors:
Xiong Luo, Yongqiang Cheng, Zhifang Liao
Citation:
Luo X, Cheng Y, Liao Z. Introduction to the special issue on machine learning-guided intelligent modeling with its industrial applications. Comput Model Eng Sci. 2024;141(1):7-11 https://doi.org/10.32604/cmes.2024.056214
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基于图像指纹和注意力机制的电力系统负荷估算算法
Title:
An Image Fingerprint and Attention Mechanism Based Load Estimation Algorithm for Electric Power System
Authors:
Qing Zhu, Linlin Gu, Huijie Lin
Citation:
Zhu Q, Gu L, Lin H. An image fingerprint and attention mechanism based load estimation algorithm for electric power system. Comput Model Eng Sci. 2024;140(1):577-591 https://doi.org/10.32604/cmes.2023.043307
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CAW-YOLO：基于跨层融合和加权感受野的遥感小目标检测YOLO算法
Title:
CAW-YOLO: Cross-Layer Fusion and Weighted Receptive Field-Based YOLO for Small Object Detection in Remote Sensing
Authors:
Weiya Shi, Shaowen Zhang, Shiqiang Zhang
Citation:
Shi W, Zhang S, Zhang S. CAW-YOLO: cross-layer fusion and weighted receptive field-based YOLO for small object detection in remote sensing. Comput Model Eng Sci. 2024;139(3):3209-3231 https://doi.org/10.32604/cmes.2023.044863
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基于空间和频域自适应嵌入机制的异质性图神经网络
Title:
Heterophilic Graph Neural Network Based on Spatial and Frequency Domain Adaptive Embedding Mechanism
Authors:
Lanze Zhang, Yijun Gu, Jingjie Peng
Citation:
Zhang L, Gu Y, Peng J. Heterophilic graph neural network based on spatial and frequency domain adaptive embedding mechanism. Comput Model Eng Sci. 2024;139(2):1701-1731 https://doi.org/10.32604/cmes.2023.045129
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基于机器学习的知识图谱构建综述
Title:
A Survey of Knowledge Graph Construction Using Machine Learning
Authors:
Zhigang Zhao, Xiong Luo, Maojian Chen, Ling Ma
Citation:
Zhao Z, Luo X, Chen M, Ma L. A survey of knowledge graph construction using machine learning. Comput Model Eng Sci. 2024;139(1):225-257 https://doi.org/10.32604/cmes.2023.031513
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基于改进深度森林的用户购买意图预测
Title:
User Purchase Intention Prediction Based on Improved Deep Forest
Authors:
Yifan Zhang, Qiancheng Yu, Lisi Zhang
Citation:
Zhang Y, Yu Q, Zhang L. User purchase intention prediction based on improved deep forest. Comput Model Eng Sci. 2024;139(1):661-677 https://doi.org/10.32604/cmes.2023.044255
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基于ANP-EWM融合健康度的冷凝器劣化演变趋势研究
Title:
Research on Condenser Deterioration Evolution Trend Based on ANP-EWM Fusion Health Degree
Authors:
Hong Qian, Haixin Wang, Guangji Wang, Qingyun Yan
Citation:
Qian H, Wang H, Wang G, Yan Q. Research on condenser deterioration evolution trend based on ANP-EWM fusion health degree. Comput Model Eng Sci. 2024;139(1):679-698 https://doi.org/10.32604/cmes.2023.043377
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基于退化类型自适应和深度卷积神经网络（CNN）的退化图像分类模型
Title:
A Degradation Type Adaptive and Deep CNN-Based Image Classification Model for Degraded Images
Authors:
Huanhua Liu, Wei Wang, Hanyu Liu, Shuheng Yi, Yonghao Yu, Xunwen Yao
Citation:
Liu H, Wang W, Liu H, Yi S, Yu Y, Yao X. A degradation type adaptive and deep cnn-based image classification model for degraded images. Comput Model Eng Sci. 2024;138(1):459-472 https://doi.org/10.32604/cmes.2023.029084
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基于强化学习的人机协作角色动态分配在幕墙安装中的应用
Title:
Role Dynamic Allocation of Human-Robot Cooperation Based on Reinforcement Learning in an Installation of Curtain Wall
Authors:
Zhiguang Liu, Shilin Wang, Jian Zhao, Jianhong Hao, Fei Yu
Citation:
Liu Z, Wang S, Zhao J, Hao J, Yu F. Role dynamic allocation of human-robot cooperation based on reinforcement learning in an installation of curtain wall. Comput Model Eng Sci. 2024;138(1):473-487 https://doi.org/10.32604/cmes.2023.029729
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复杂环境下自动充电机器人避障路径规划的改进RRT∗算法
Title:
Improved RRT∗ Algorithm for Automatic Charging Robot Obstacle Avoidance Path Planning in Complex Environments
Authors:
Chong Xu, Hao Zhu, Haotian Zhu, Jirong Wang, Qinghai Zhao
Citation:
Xu C, Zhu H, Zhu H, Wang J, Zhao Q. Improved rrt∗ algorithm for automatic charging robot obstacle avoidance path planning in complex environments. Comput Model Eng Sci. 2023;137(3):2567-2591 https://doi.org/10.32604/cmes.2023.029152
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开源工业软件项目中的代码审查员智能预测
Title:
Code Reviewer Intelligent Prediction in Open Source Industrial Software Project
Authors:
Zhifang Liao, Bolin Zhang, Xuechun Huang, Song Yu, Yan Zhang
Citation:
Liao Z, Zhang B, Huang X, Yu S, Zhang Y. Code reviewer intelligent prediction in open source industrial software project. Comput Model Eng Sci. 2023;137(1):687-704 https://doi.org/10.32604/cmes.2023.027466
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STPGTN–考虑空间约束和瞬态测量数据的多分支参数识别方法
Title:
STPGTN–A Multi-Branch Parameters Identification Method Considering Spatial Constraints and Transient Measurement Data
Authors:
Shuai Zhang, Liguo Weng
Citation:
Zhang S, Weng L. STPGTN–A multi-branch parameters identification method considering spatial constraints and transient measurement data. Comput Model Eng Sci. 2023;136(3):2635-2654 https://doi.org/10.32604/cmes.2023.025405
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LF-CNN：深度学习引导的小样本遥感分类目标检测
Title:
LF-CNN: Deep Learning-Guided Small Sample Target Detection for Remote Sensing Classification
Authors:
Chengfan Li, Lan Liu, Junjuan Zhao, Xuefeng Liu
Citation:
Li C, Liu L, Zhao J, Liu X. LF-CNN: deep learning-guided small sample target detection for remote sensing classification. Comput Model Eng Sci. 2022;131(1):429-444 https://doi.org/10.32604/cmes.2022.019202
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机器学习增强的边界元方法：高斯求积点的预测
Title:
Machine Learning Enhanced Boundary Element Method: Prediction of Gaussian Quadrature Points
Authors:
Ruhui Cheng, Xiaomeng Yin, Leilei Chen
Citation:
Cheng R, Yin X, Chen L. Machine learning enhanced boundary element method: prediction of gaussian quadrature points. Comput Model Eng Sci. 2022;131(1):445-464 https://doi.org/10.32604/cmes.2022.018519
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基于一维卷积网络的工业恶意软件分类可转移特征
Title:
Transferable Features from 1D-Convolutional Network for Industrial Malware Classification
Authors:
Liwei Wang, Jiankun Sun, Xiong Luo, Xi Yang
Citation:
Wang L, Sun J, Luo X, Yang X. Transferable features from 1d-convolutional network for industrial malware classification. Comput Model Eng Sci. 2022;130(2):1003-1016 https://doi.org/10.32604/cmes.2022.018492
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精密惯性系统故障预测和定量异常测量的快速小样本建模方法
Title:
A Fast Small-Sample Modeling Method for Precision Inertial Systems Fault Prediction and Quantitative Anomaly Measurement
Authors:
Hongqiao Wang, Yanning Cai
Citation:
Wang H, Cai Y. A fast small-sample modeling method for precision inertial systems fault prediction and quantitative anomaly measurement. Comput Model Eng Sci. 2022;130(1):187-203 https://doi.org/10.32604/cmes.2022.018000
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CMES期刊简介
版权声明
本文由泰克赛思南京办公室负责编译。详细内容请以英文原版为准。如需转载，请于公众号后台留言咨询。
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