作者机构：
[Zhaoyu Liu; Caidie Yi; Ziyi Zhu; Zengyang He; Yiye Wu; Chengjuan Yang] School of Management, Wuhan Polytechnic University, Wuhan, Hubei, China
会议名称：
2025 IEEE International Conference on Electronics, Energy Systems and Power Engineering (EESPE)
会议时间：
17 March 2025
会议地点：
Shenyang, China
会议论文集名称：
2025 IEEE International Conference on Electronics, Energy Systems and Power Engineering (EESPE)
关键词：
Fiscal prediction;Adaptive-Lasso regression;Grey neural network;Combined prediction model
摘要：
The widespread application of data mining technology and the rapid development of machine learning techniques provide a simple and efficient method for predicting local fiscal revenue. The current main model for fiscal revenue prediction involves using data mining techniques for reasonable selection and analysis of data, followed by training neural networks to construct prediction models. This paper proposes a fiscal revenue prediction model based on data mining and grey neural networks, selecting 12 influencing factors that affect fiscal revenue. The Adaptive-Lasso method is used for variable coefficient estimation, and least angle regression is employed to solve the problem, eliminating some variables with lesser impact. The remaining variables are then subjected to GM (1,1) grey prediction to obtain their predicted values, and the prediction accuracy is evaluated with a grading system. Finally, historical data is used to train a BP neural network, constructing a grey neural network combined prediction model, where the grey predicted values are substituted into the trained grey neural network to yield future fiscal revenue predictions. Experimental results indicate that due to the high fault tolerance and adaptability of neural networks, the predicted values fit well with the actual values, with the two curves nearly overlapping. The grey neural network prediction results constructed in this paper are highly reliable.
作者机构：
[Yang, Jinlei; Guan, Lu; Huang, Ronghua; Bao, Yongcheng] Jiangsu Integr Transport Technol Co Ltd, Nanjing 211100, Peoples R China.;[Guan, Lu] Wu Han Polytech Univ, Wuhan 430048, Peoples R China.;[Chen, Leilei] Southeast Univ, Key Lab Safety & Risk Management Transport Infras, Nanjing 210018, Peoples R China.
会议名称：
9th International Conference on Intelligent IoT as a Service
会议时间：
OCT 27-29, 2023
会议地点：
Nanjing, PEOPLES R CHINA
会议主办单位：
[Huang, Ronghua;Guan, Lu;Bao, Yongcheng;Yang, Jinlei] Jiangsu Integr Transport Technol Co Ltd, Nanjing 211100, Peoples R China.^[Guan, Lu] Wu Han Polytech Univ, Wuhan 430048, Peoples R China.^[Chen, Leilei] Southeast Univ, Key Lab Safety & Risk Management Transport Infras, Nanjing 210018, Peoples R China.
会议论文集名称：
Lecture Notes of the Institute for Computer Sciences Social Informatics and Telecommunications Engineering
关键词：
IoT and 3D Visualization;Road maintenance base;Intelligent application
摘要：
In the field of "new infrastructure" intelligent management and control, the Internet of Things and 3D visualization of these two technologies are developing more and more rapidly, and complement each other, which has also aroused the keen attention of road maintenance base managers. This paper will take a road maintenance base as the research object, to explore the practical application of Internet of Things 3D visualization technology in this particular scene. According to the needs of the whole project, through real-time monitoring and data collection of each business data in the intelligent road maintenance base, we analyze the different operational efficiency, energy consumption and output analysis under the traditional mode and the new mode of applying IoT 3D visualization technology, so as to provide a new solution for the intelligent operation and control of the road maintenance base in the future by using IoT 3D visualization technology.
期刊：
2024 IEEE International Conference on Signal, Information and Data Processing (ICSIDP),2024年:1-5
作者机构：
[Sheng Chen] Zhuhai Beijing Institute of Technology,Beijing Institute of Technology,Zhuhai,China;[Wei Chen; Huanlong Zhao] Wuhan Polytechnic University,School of Electronic and Electrical Engineering,Hubei,China
会议名称：
2024 IEEE International Conference on Signal, Information and Data Processing (ICSIDP)
会议时间：
22 November 2024
会议地点：
Zhuhai, China
会议论文集名称：
2024 IEEE International Conference on Signal, Information and Data Processing (ICSIDP)
摘要：
When performing object tracking tasks, precisely tracking the desired target is the optimization goal of the tracking algorithm. Generally, deep learning models with larger model sizes and higher computational costs tend to have stronger computational capabilities. However, uncontrolled increases in model size and computational cost can make the algorithm difficult to use in practice. Therefore, to find a suitable balance between increasing computational cost and improving computational performance, this paper introduces a lightweight object tracking method that introduces a CNN attention mechanism. Based on SiamRPN++, this algorithm employs a more concise corner prediction head and uses depthwise separable convolution to replace general convolution, significantly reducing the computational cost of ResNet-50. Moreover, symmetric point-wise expansion (PE) and point-wise linear projection (PLP) are utilized to maximize computational performance while minimizing computational cost. Additionally, the Squeeze-and-Excitation (SE) network is employed to introduce an attention mechanism to each convolutional module. These strategies effectively make the algorithm lightweight and improve its computational efficiency.
作者机构：
[Zhao, YuDan; Ni, Ying; Xia, Peng] Wuhan Polytech Univ, Sch Elect & Elect Engn, Wuhan 430023, Hubei, Peoples R China.;[Zeng, Wu; Zeng, W] Wuhan Polytech Univ, Sch Math & Comp Sci, Wuhan 430023, Hubei, Peoples R China.;[Tan, RuoChen] Univ Calif San Diego, Comp Sci & Engn, San Diego, CA 92093 USA.
会议名称：
1st International Artificial Intelligence Conference-IAIC
会议时间：
NOV 25-27, 2023
会议地点：
Nanjing, PEOPLES R CHINA
会议主办单位：
[Zhao, YuDan;Ni, Ying;Xia, Peng] Wuhan Polytech Univ, Sch Elect & Elect Engn, Wuhan 430023, Hubei, Peoples R China.^[Zeng, Wu] Wuhan Polytech Univ, Sch Math & Comp Sci, Wuhan 430023, Hubei, Peoples R China.^[Tan, RuoChen] Univ Calif San Diego, Comp Sci & Engn, San Diego, CA 92093 USA.
会议论文集名称：
Communications in Computer and Information Science
关键词：
Data Visualization;Hydrological Data;Digital Twin
摘要：
In the context of digital transformation, cities and enterprises are striving to build a digital industrial chain, cultivate a digital ecosystem, and support high-quality economic development. Therefore, the use of visualization technology to assist decision-makers in rational planning has become a hot spot. Taking wuhan city as an example, combined with 3D modeling technology, it is aimed at smart cities and based on digital twins to create multiple scenarios for hydrological data application services and improve hydrological information services. First, we collected the data released by the china hydrology and water resources station; then, we visualized the hydrological data of the yangtze river Hankou station by using methods such as view juxtaposition and 3D interaction; after that, we constructed a 3D scene based on the real scene of the yangtze river Hankou basin, and used algorithms to the water body model is optimized; finally, the interaction between data and scenes is designed, various functions are realized by using high-level programming language design, and the water level changes in the flood season are simulated to help analyze and understand data more clearly, and assist decision makers in making decisions.
期刊：
2024 20th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD),2024年:1-6
作者机构：
[Tianyu Liu; Fangxiu Wang; Yangcheng Xu; Yihua Tao; Wen Zhang; Chen Su] School of Mathematics and Computer Science, Wuhan Polytechnic University,Wuhan,Hubei,430023
会议名称：
2024 20th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)
会议时间：
27 July 2024
会议地点：
Guangzhou, China
会议论文集名称：
2024 20th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)
摘要：
In response to the problem that the existing triple integral calculator is unable to calculate the double integral, this paper improves the triple integral calculator. Firstly, the input modes for users to calculate the dual and triple integrals are introduced respectively. Secondly, a method is designed to transform the dual integral input mode into an equivalent triple integral input mode. Finally, the method of calculating the dual integral with the triple integral calculator is designed. The experimental results show that the improved triple integral calculator is capable of calculating double integrals.
期刊：
Proceedings of the 2nd International Conference on Educational Knowledge and Informatization,2024年:88-94
作者机构：
[Ying Cao] Wuhan Polytechnic University, China
会议名称：
EKI '24: Proceedings of the 2nd International Conference on Educational Knowledge and Informatization
会议论文集名称：
Educational Knowledge and Informatization
摘要：
The increasing popularity of Virtual Reality (VR) has provoked scholars’ interest to explore its potential in creating immersive and visual learning environments for various education purposes, but little empirical evidence can be adduced to verify the educational values of VR in interpreting teaching and training. The current study investigated the potentials and possible constraints of VR-assisted interpreting teaching in universities by comparing students’ performance in VR-assisted and traditional face-to-face teaching modes respectively. This study adopts a competence-based approach and uses mainly quantitative methods by selecting twenty undergraduates and randomly dividing them into two groups, namely experimental group (adopting VR assisted training mode) and control group (adopting face-to-face training mode), in dialogue interpreting training. This study evaluates students’ interpreting quality in terms of product (i.e. accuracy and adequacy) and service (i.e. equivalency and interaction). In addition, the experimental group students are required to complete a post-test questionnaire measuring student's perception, acceptance and evaluation of VR-assisted training mode. The author concludes that VR-assisted training mode does not notably improve students’ interpreting product quality, however, it excels face-to-face training mode in improving student's interpreting service quality by strengthening their interactive and self-evaluation capabilities, and most importantly stimulating their interests in interpreting learning. This study also proposes a hybrid training mode by incorporating VR tools into traditional training mode. Hopefully, this article can inspire interpreter trainers to take advantage of the numerous benefits of VR-assisted interpreting training despites the possible limitations, such as motion sickness, technical difficulties, time-consuming and complex tools in its alignment with training goals.
期刊：
E3S Web of Conferences,2024年520:02022 ISSN：2555-0403
作者机构：
[Guoqiang Hao; Zhen Huang; Wei Chen; Qiang Lv] School of Electrical and Electronic Engineering, Wuhan Polytechnic University;[Feng Zheng] KINGDREAM PUBLIC LIMITED COMPANY
会议名称：
第四届环境资源与能源工程国际学术会议
会议时间：
2024-02-23
会议地点：
中国广东珠海
关键词：
Stacking;domain;Estimation of Stacked Fusion Model of Young's Modulus;Measurement of Rock Deformation Parameters;Fusion;Model
摘要：
Rock Young’s modulus is an essential parameter for formation stress characterization and oil and gas reservoir evaluation work and plays an important role in oil drilling-related engineering type work. Aiming at the problems of doubtful confidence in Young’s modulus measurements, time-consuming computation, and high measurement cost in oil drilling, this paper proposed Young’s modulus estimation method based on the Stacking fusion model. The method first processed the downhole vibration data to obtain its time-domain feature data and then used the time-domain feature data as the input to the fusion model while used the rock Young’s modulus data as the model output. The model learner used consists of three base learners, ANN, XGBoost, and CatBoost, with MLR as the model meta-learner. The mapping relationship between the time-domain features and Young’s modulus was established by this method, and the prediction and estimation of Young’s modulus parameters of the rock were finally realized. The results showed that the average absolute error (MAE) of the fused Stacking model was 0.2502 and the goodness-of-fit (R2) was 0.9691. Compared with other single models, the fused model based on Stacking had the advantage of being able to combine each single model, which provided a new method for estimation and prediction of Young’s modulus of rocks.
作者机构：
chool of Modern Industry for Selenium Science and Engineering,Wuhan Polytechnic University;ational R&D Center for Se-rich Agricultural Products Processing,Hubei Engineering Research Center for Deep Processing of Green Se-rich Agricultural Products,Wuhan Polytechnic University
会议名称：
2024社会发展与科技创新交流会
会议时间：
2024-04-20
会议地点：
线上会议
关键词：
Food translation;cross-disciplinary;teaching practice
摘要：
Relying on the practical course system of food and translation majors,this course combines the characteristics of the professional courses of the two majors,including the knowledge of food,which is stronger in professional nature,and the knowledge of translation,which is more prominent in practical ability,to cultivate cross-disciplinary talents in food and translation. This paper takes "Food and English Translation" course as an example,analyzes the potential connection between food and translation,creates teaching situations by using modern teaching methods,and promotes the cultivation mode of interdisciplinary composite talents and the innovation of in-depth integration of disciplines and specialties. In order to break down the barriers between disciplines and specialties and strengthen the construction of interdisciplinary innovative talents,we summarize the basic construction and practical experience of the general elective course of interdisciplinary cross-fertilization.
摘要：
Blockchain is a decentralized distributed ledger, through a unique chain block structure to verify and store data, so as to ensure the privacy and security of all kinds of information, but the blockchain personal identity authentication link is not complete, relying only on the key can operate personal accounts there are serious security problems. Therefore, a signature scheme is proposed, which takes face biometric as input, uses convolutional neural network (CNN) facenet to encode the face feature information, and then uses homomorphic encryption scheme to encrypt the face encoding and compare it with the face template in the database. At the same time, in order to ensure the authenticity and security of opeation, the user's rPPG signal are detected in real time during the authentication in considred successfully. Finally, using the information mixing algorithm, biometric and RSA key are fused to form a combined key for signature. The experiment shows that, under the condition of obtaining biometric information, the user's identity is verified correctly, and the contract is signed correctly within 2 s. In the whole scheme, the template creation time is 5.62 s, the encryption time of the input biometric information is 0.52 s, the heart rate detection time (including the camera time) is 5.59 s, and the user can be fully identified within four times, with an accuracy of 98%. The scheme improves the security of the blockchain transaction and signing process.
作者机构：
[Zhao, Jiemei; Chen, Binbin] Wuhan Polytech Univ, Sch Math & Comp Sci, Wuhan, Peoples R China.
会议名称：
2024 39th Youth Academic Annual Conference of Chinese Association of Automation (YAC)
会议时间：
07 June 2024
会议地点：
Dalian, China
会议主办单位：
[Chen, Binbin;Zhao, Jiemei] Wuhan Polytech Univ, Sch Math & Comp Sci, Wuhan, Peoples R China.
会议论文集名称：
2024 39th Youth Academic Annual Conference of Chinese Association of Automation (YAC)
关键词：
bipartite consensus;multi-agent systems;nonlinear dynamics;adaptive control
摘要：
This paper focuses on the problem of second-order bipartite consensus in nonlinear multi-agent systems concerning leader-following. A novel definition of the Lipschitz condition is proposed to solve the nonlinear term in the leader following the bipartite consensus problem. In addition, a procedure for adaptive output feedback control is proposed, which can continuously adjust the output of the controller to achieve stability. By utilizing the linear matrix inequality technique, a sufficient condition is proposed to ensure that the considered nonlinear multi-agent systems implement leader-following bipartite consensus. Finally, the validity and feasibility of the theoretical result are demonstrated through numerical simulations.
通讯机构：
[Wang, FX ] W;Wuhan Polytech Univ, Sch Math & Comp Sci, Wuhan, Peoples R China.
会议名称：
2024 39th Youth Academic Annual Conference of Chinese Association of Automation (YAC)
会议时间：
07 June 2024
会议地点：
Dalian, China
会议主办单位：
[Xu, Yangcheng;Wang, Fangxiu;Zhang, Wen;Tao, Yihua;Tin, Tianyu;Liu, Hui] Wuhan Polytech Univ, Sch Math & Comp Sci, Wuhan, Peoples R China.
会议论文集名称：
2024 39th Youth Academic Annual Conference of Chinese Association of Automation (YAC)
关键词：
integration of arc length curves;definite integrals;input patterns
摘要：
To address the limitation of existing definite integral calculators in computing the integral of arc length curves, a novel methodology is introduced herein. This approach entails the conversion of the integral input format for arc length curves into the established format for definite integrals. Initially, a delineation of four distinct input formats for definite integrals and thirteen formats for arc length curve integrals is presented. Subsequently, a systematic method is devised to translate the integral input format specific to arc length curves into the standardized definite integral format. Lastly, a computational technique leveraging a definite integral calculator is outlined for the computation of arc length curve integrals. Empirical findings substantiate the efficacy of the enhanced definite integral calculator in accurately computing arc length curve integrals.
摘要：
This article analyzes the image features of various weather phenomena, collects and constructs a weather image dataset, and builds a convolutional neural network model based on deep learning methods for weather phenomenon recognition. Firstly, this article constructs a dataset of five common weather types, including sunny, rainy, snowy, foggy, and thunderstorm weather, which includes multiple weather types and is closer to real production and living conditions. Each category has 10000 annotated weather images. Secondly, in response to some issues with existing weather image classification methods, such as low recognition accuracy and slow model training speed, a ResNet50 based transfer learning model was constructed by introducing transfer learning on the basis of convolutional neural networks. This model has higher classification accuracy and faster recognition speed compared to traditional image recognition methods.
摘要：
With the continuous development of artificial intelligence technology, deep learning methods have been widely used in smart agriculture. With the continuous progress of object detection algorithms, it is a future trend to introduce computer vision methods into smart agriculture. This paper proposes an improved YOLOv8 network model for detecting whether apple is still in a healthy state in smart agriculture systems. By introducing a better backbone network EfficientNet, features can be extracted from the data efficiently. In addition, by introducing a novel WIOU calculation function, the rectangular box can be computed better. In this experiment, the average accuracy of the improved YOLOv8-Enet is mAP0.5 and mAP 0.5:0.95, which are 7.1% and 6.5% higher than that of YOLOv8-base, respectively. The proposed YOLOv8-Enet model can effectively detect apple surface defect and provide theoretical and technical support for future research on vision of smart agriculture
会议论文集名称：
2024 43rd Chinese Control Conference (CCC)
关键词：
Artificial potential field algorithm;COLREGS;Path planning;USV
摘要：
Path planning is a core issue of autonomous navigation for unmanned surface vehicles (USVs). To guarantee navigation safety, this paper proposes an Improved Artificial Potential Field (IAPF) algorithm for path planning of USVs. On the one hand, to solve the local optimal problem of artificial potential field (APF) algorithm, an adjustment factor is introduced in the repulsive potential field function. On the other hand, to ensure the collision avoidance safety in complex encounter scenarios, the International Regulations for Preventing Collisions at Sea (COLREGS) is utilized in the IAPF algorithm. The simulation experiments verify that the path planned via the IAPF algorithm is safer and more efficient than APF algorithm.
摘要：
With the acceleration of urbanization and the increase of traffic load, the quality and safety of concrete pavement are crucial to the reliability of transportation infrastructure. Traditional pavement monitoring methods are limited by time and space, making it difficult to achieve comprehensive and real-time monitoring of the pavement. This study introduces wireless sensor technology to build a real-time monitoring system, which selects various sensors such as temperature and humidity, pressure, strain, etc. through wireless sensor networks to transmit data in real time to the monitoring center. By analyzing sensor data, it can timely capture temperature and humidity changes and strain of the concrete pavement, so as to detect potential safety hazards in the pavement in time. The research results show that the proposed wireless sensor technology has good real-time performance and accuracy in concrete pavement monitoring. Compared with traditional methods, this technology can more comprehensively evaluate the quality and safety of the pavement, and is expected to provide scientific basis for urban traffic management, reduce maintenance costs, and improve road users' sense of security.
期刊：
2024 3rd International Symposium on Aerospace Engineering and Systems (ISAES),2024年:148-154
作者机构：
[Xin Gao; Xiaogang Zheng] School of Electrical and Electronic Engineering, Wuhan Polytechnic University,Wuhan,China;[Yongnan Rao] Chinese Academy of Sciences,Key Laboratory of Time Reference and Applications,Xi'[Yongnan Rao] an,China
会议名称：
2024 3rd International Symposium on Aerospace Engineering and Systems (ISAES)
会议时间：
22 March 2024
会议地点：
Nanjing, China
会议论文集名称：
2024 3rd International Symposium on Aerospace Engineering and Systems (ISAES)
关键词：
component;QMBOC Signal;Distortions;Bei Dou Satellite Navigation System;Signal Process
摘要：
This study examines the distortion characteristics of the QMBOC (Quadrature Multiplexed Binary Offset Carrier) modulation signal. The QMBOC ideal signal creation formula extends the digital and analog distortion model suited for QMBOC by mathematical modeling, based on the 2-OS distortion model and BOC distortion model. The legend is then generated using a simulation platform. The inconsistency in the weight proportion of the distortion of the in-phase and orthogonal components of the QMBOC signal is attributed to the γ power factor of the signal. The simulation results indicate that the primary signal distortion is primarily associated with the Q branch in the investigation and examination of the duty ratio and distortion value. Additionally, the simulation analysis of distortion also supports the corresponding experimental findings. This offers a theoretical backing for examining the distortion properties of QMBOC.
摘要：
Abstract A numerical analysis has been done to investigate the effects of different overload conditions on crack propagation behavior of AH32 steel. The tensile overload ratios, overload-underload, underload-overload and underload are investigated in this study. The residual stress distribution in the region near the crack tip under different overload ratios and overload conditions are all the results of plastic deformation of the material near the crack tip during fatigue crack propagation, which shows that applying tensile overload postpone the crack growth, while underload promote the crack growth. Furthermore, it is also observed that the crack closure level shows a fast increase with the increase of overload ratio. Finally, the mechanism of residual stress at the crack tip and the mechanism of plastic deformation at the crack tip controlling the transient crack growth behavior under variable amplitude loading are essentially the same.
