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2022 4th International Conference on Industrial Artificial Intelligence (IAI)最新文献

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Research Hotspots and Dynamic Analysis of Knowledge Spillover in Modern Service Industry Based on CITESPACE Big Data Analysis 基于CITESPACE大数据分析的现代服务业知识溢出研究热点与动态分析
2022 4th International Conference on Industrial Artificial Intelligence (IAI) Pub Date : 2022-08-24 DOI: 10.1109/IAI55780.2022.9976611
W. Yumei, Luo Ruchuan, Zhou Yinuo
{"title":"Research Hotspots and Dynamic Analysis of Knowledge Spillover in Modern Service Industry Based on CITESPACE Big Data Analysis","authors":"W. Yumei, Luo Ruchuan, Zhou Yinuo","doi":"10.1109/IAI55780.2022.9976611","DOIUrl":"https://doi.org/10.1109/IAI55780.2022.9976611","url":null,"abstract":"The rapid and sustainable development of economy and society requires us to abandon the previous development mode and carry out the optimization and adjustment of industrial structure. In this paper, we use Citespace software and knowledge graph visualization technology to analyze the core journals in the database in terms of keyword analysis and literature co-citation analysis based on the database information of WOS, with “modern service industry” and “knowledge spillover” as the themes. Through the visual analysis of the knowledge map, we comprehensively study and discuss the current status of research on “modern service industry” and “modern service industry” related to knowledge spillover, as well as the research hotspots and development trends in various periods, so as to prepare for the next step of “knowledge spillover in modern service industry”. It will pave the way for the next research on “knowledge spillover in modern service industry”.","PeriodicalId":138951,"journal":{"name":"2022 4th International Conference on Industrial Artificial Intelligence (IAI)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133663459","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Multi-UAV Optimal Formation Control via Actor-Critic Reinforcement Learning Algorithm 基于actor - critical强化学习算法的多无人机最优编队控制
2022 4th International Conference on Industrial Artificial Intelligence (IAI) Pub Date : 2022-08-24 DOI: 10.1109/IAI55780.2022.9976741
Qiwei Lou, Yan Zhou, Xiaodong Li
{"title":"Multi-UAV Optimal Formation Control via Actor-Critic Reinforcement Learning Algorithm","authors":"Qiwei Lou, Yan Zhou, Xiaodong Li","doi":"10.1109/IAI55780.2022.9976741","DOIUrl":"https://doi.org/10.1109/IAI55780.2022.9976741","url":null,"abstract":"In this paper, the multi-agent synchronous actor-critic algorithm is developed to solve the optimal formation control problem of the disturbed multi-unmanned aerial vehicle system. Based on the optimal control theory, the optimal formation problem is transformed to seek the optimal solutions of a set of coupled Hamilton-Jacobi-Bellman equations. The multi-agent reinforcement learning algorithm via actor/critic structure is adapted to approximate such solutions. The adaptive tuning laws are given for both critic and actor networks, which ensure the approximate convergence of the optimal value and optimal controller and the stability of the closed-loop formation error system. The simulation is provided to verify the effectiveness of the proposed theoretical results.","PeriodicalId":138951,"journal":{"name":"2022 4th International Conference on Industrial Artificial Intelligence (IAI)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133719844","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
An Improved Genetic Algorithm for Solving Tri-level Programming Problems 求解三层规划问题的改进遗传算法
2022 4th International Conference on Industrial Artificial Intelligence (IAI) Pub Date : 2022-08-24 DOI: 10.1109/IAI55780.2022.9976878
Kai Su, Zhili Lei, H. Niu
{"title":"An Improved Genetic Algorithm for Solving Tri-level Programming Problems","authors":"Kai Su, Zhili Lei, H. Niu","doi":"10.1109/IAI55780.2022.9976878","DOIUrl":"https://doi.org/10.1109/IAI55780.2022.9976878","url":null,"abstract":"When genetic algorithm is adopted to solve tri-level programming, many problems exist, such as controlling population size, jumping out of local optima, and avoiding low efficiency. An improved genetic algorithm with parallel strategy is proposed in this paper to solve tri-level programming, as well as elites reserving and fitness value crowding strategy. Simulations with numerical examples are done to prove correctness and effectiveness of the proposed algorithm.","PeriodicalId":138951,"journal":{"name":"2022 4th International Conference on Industrial Artificial Intelligence (IAI)","volume":"74 9","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114085421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Fault diagnosis study of pumping well schematic based on SCN-integrated learning 基于scn集成学习的抽油井原理图故障诊断研究
2022 4th International Conference on Industrial Artificial Intelligence (IAI) Pub Date : 2022-08-24 DOI: 10.1109/IAI55780.2022.9976845
Baojun Zhao, C. Zang, Tianwei Dong, Feifei Chai, Peng Zeng
{"title":"Fault diagnosis study of pumping well schematic based on SCN-integrated learning","authors":"Baojun Zhao, C. Zang, Tianwei Dong, Feifei Chai, Peng Zeng","doi":"10.1109/IAI55780.2022.9976845","DOIUrl":"https://doi.org/10.1109/IAI55780.2022.9976845","url":null,"abstract":"With the bad oil exploitation environment, the safe operation of pumping wells is also affected to a certain extent. Once a fault occurs, it will bring great losses. Therefore, the realization of rapid and accurate diagnosis of pumping wells is of great significance for reducing losses, avoiding safety accidents and ensuring oil field production. In this paper, a new model of SCN- integrated learning is proposed to train and classify the data. The indicator diagram data is standardized by Z-score. The Gray Level Co-occurrence Matrix (GLCM) is used to extract the feature vector, and the feature vector is input into the SCN- integrated learning model for training. Through the comparison with SCN, the accuracy of this method is improved by 7.3%, and the final accuracy reaches 97.93%, which verifies the effectiveness and accuracy of this method.","PeriodicalId":138951,"journal":{"name":"2022 4th International Conference on Industrial Artificial Intelligence (IAI)","volume":"2014 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128303607","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A Fault Detection Method and System for Highway Tunnel dome light Based on Improved YOLO with Locatization Loss Function 基于改进YOLO定位损失函数的公路隧道顶灯故障检测方法及系统
2022 4th International Conference on Industrial Artificial Intelligence (IAI) Pub Date : 2022-08-24 DOI: 10.1109/IAI55780.2022.9976730
Lizhen Dai, Cailing Tang, Gang Yang, Hui Yang, Jiang Luo, Zhaozhang Chen
{"title":"A Fault Detection Method and System for Highway Tunnel dome light Based on Improved YOLO with Locatization Loss Function","authors":"Lizhen Dai, Cailing Tang, Gang Yang, Hui Yang, Jiang Luo, Zhaozhang Chen","doi":"10.1109/IAI55780.2022.9976730","DOIUrl":"https://doi.org/10.1109/IAI55780.2022.9976730","url":null,"abstract":"Sufficient light intensity in the tunnel plays an extremely important role in ensuring the safety of driving in the tunnel. Tunnel dome light is the basic facility to ensure tunnel lighting. The traditional fault detection method is manual inspection, and the discovery of the problem is not timely. In this paper, a tunnel dome light fault detection method and system based on video monitoring is proposed. Constructing a tunnel dome light detection data set. The original positioning loss function in YOLOv5 is changed from CIOD_Loss function to SCALoss function, which is composed of side overlap (SO), corner distance (CD) and aspect ratio (AR) loss. So that the network can generate more penalties for low overlap positioning frames, and the network model has better positioning performance and faster convergence speed, it is more suitable for the dense and small target such as tunnel headlight. After improving the model, the recognition accuracy is improved by 13.1 %, and the positioning loss is also reduced. So that it can quickly and accurately locate the target to be detected. Finally, the fault lamp detection model is constructed to locate the specific location of the fault lamp. The experiment shows that the model has good performance, and it can effectively detect the state of tunnel dome light in real time and detect abnormal working conditions.","PeriodicalId":138951,"journal":{"name":"2022 4th International Conference on Industrial Artificial Intelligence (IAI)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121930900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Linear Algebra Based Swing-Up Control of the Pendubot 基于线性代数的悬浮器摆动控制
2022 4th International Conference on Industrial Artificial Intelligence (IAI) Pub Date : 2022-08-24 DOI: 10.1109/IAI55780.2022.9976523
Cui Wei, P. Albertos, Tianyou Chai
{"title":"Linear Algebra Based Swing-Up Control of the Pendubot","authors":"Cui Wei, P. Albertos, Tianyou Chai","doi":"10.1109/IAI55780.2022.9976523","DOIUrl":"https://doi.org/10.1109/IAI55780.2022.9976523","url":null,"abstract":"The swing up control problem for the Pendubot refers to swinging up both of the two links to the top equilibrium point and balance them at that point. The balancing controller is usually designed based on the linearized model at the desired equilibrium. Therefore, the challenging task is to design a swing up controller that can bring the Pendubot within a neighborhood of the desired equilibrium in which it can be stabilized by the linear balancing controller. This paper presents a novel linear algebra based methodology for the swing up control of the Pendubot. By controlling the actuated link to converge to the top position while the unactuated one oscillates near that position, the Pendubot is eventually stabilized by the balancing controller once the switching condition is satisfied. Simulation and experimental results are provided and discussed, demonstrating the good performance of the proposed approach.","PeriodicalId":138951,"journal":{"name":"2022 4th International Conference on Industrial Artificial Intelligence (IAI)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125802321","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Design of Smart Home Control System Based on Raspberry Pi Design and Implementation 基于树莓派的智能家居控制系统设计与实现
2022 4th International Conference on Industrial Artificial Intelligence (IAI) Pub Date : 2022-08-24 DOI: 10.1109/IAI55780.2022.9976573
X. Liu, Zhao Zhang
{"title":"Design of Smart Home Control System Based on Raspberry Pi Design and Implementation","authors":"X. Liu, Zhao Zhang","doi":"10.1109/IAI55780.2022.9976573","DOIUrl":"https://doi.org/10.1109/IAI55780.2022.9976573","url":null,"abstract":"In this paper, using the Internet of Things technology, a new smart home control system with Raspberry Pi as the central control and integrated multi-platform is designed. This system adopts Python language development, and realizes multi-platform adaptive user-side applications through WeChat Mini Programs. The system uses the message queue telemetry transmission protocol to realize LAN communication between the sensor node and the central control device. WebSocket protocol is used to realize the full duplex communication between the client and the central control device. The system includes environmental monitoring, equipment control, scene control, and family management functions, supplemented by voice recognition and face recognition technology. An actual system is used to verify the effectiveness of the work in this paper.","PeriodicalId":138951,"journal":{"name":"2022 4th International Conference on Industrial Artificial Intelligence (IAI)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124712977","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Data-driven robust model predictive control technology for propylene distillation process 丙烯蒸馏过程数据驱动鲁棒模型预测控制技术
2022 4th International Conference on Industrial Artificial Intelligence (IAI) Pub Date : 2022-08-24 DOI: 10.1109/IAI55780.2022.9976769
Keshuai Ju, Renchu He, Liang Zhao
{"title":"Data-driven robust model predictive control technology for propylene distillation process","authors":"Keshuai Ju, Renchu He, Liang Zhao","doi":"10.1109/IAI55780.2022.9976769","DOIUrl":"https://doi.org/10.1109/IAI55780.2022.9976769","url":null,"abstract":"The distillation column is always affected by external disturbances during its operation. Using data-driven robust model predictive controller (DDRMPC), which based on the data-driven robust optimization (DDRO) method, can better handle the process uncertainty than the traditional robust model predictive control (TRMPC) because of the introduction of the machine learning method. A DDRMPC of propylene distillation column is proposed to hedge against the uncertainty of propylene content at the top of the column. Firstly, a linear state space model of the process is established based on the compartmental method and the dynamic mechanism model, and then the uncertainty set of principal component analysis and robust kernel density estimation is constructed by using the historical data. Certainty equivalent MPC (CEMPC), TRMPC and DDRMPC algorithms are constructed respectively. Finally, the performance of DDRMPC is analyzed through the case study of composition control.","PeriodicalId":138951,"journal":{"name":"2022 4th International Conference on Industrial Artificial Intelligence (IAI)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127714761","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Event-triggered tracking control for nonlinear system with output saturation 输出饱和非线性系统的事件触发跟踪控制
2022 4th International Conference on Industrial Artificial Intelligence (IAI) Pub Date : 2022-08-24 DOI: 10.1109/IAI55780.2022.9976665
Ningxi Liu, Dong Liu
{"title":"Event-triggered tracking control for nonlinear system with output saturation","authors":"Ningxi Liu, Dong Liu","doi":"10.1109/IAI55780.2022.9976665","DOIUrl":"https://doi.org/10.1109/IAI55780.2022.9976665","url":null,"abstract":"In this paper, a new event-triggered model-free adaptive control method for nonlinear systems subject to output saturation constraint is discussed. Under the compact form dynamic linearization technique framework, an equivalent linear data model is established. The pseudo partial derivative (PPD) parameter estimator is constructed by the saturated output. With the help of system measured error, the adaptive eventtriggered condition is developed to update the estimator. Different from the previous results, the controller is redesigned by the measured output. The boundedness of the system tracking error is guaranteed. A simulation example is shown to demonstrate the feasibility of the proposed algorithm.","PeriodicalId":138951,"journal":{"name":"2022 4th International Conference on Industrial Artificial Intelligence (IAI)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124425070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Fast situation-based correction of AI systems 人工智能系统基于情境的快速修正
2022 4th International Conference on Industrial Artificial Intelligence (IAI) Pub Date : 2022-08-24 DOI: 10.1109/IAI55780.2022.9976512
George D. Leete, Alexander N. Gorban, I. Tyukin
{"title":"Fast situation-based correction of AI systems","authors":"George D. Leete, Alexander N. Gorban, I. Tyukin","doi":"10.1109/IAI55780.2022.9976512","DOIUrl":"https://doi.org/10.1109/IAI55780.2022.9976512","url":null,"abstract":"In this paper we present algorithms for continuous maintenance and improvement in a broad class Artificial Intelligence (AI) system whose primary function is to detect and report various multiple co-occurring objects or events in each data frame. The data frame combines features of various objects of interests as well as their relevant environments and as such represents a “situation”. Examples of such data frames and “situations” are feature vectors of deep neural networks with YOLO backbone. A distinct property of these data is that important operational information, such as input data corresponding to errors and misclassifications, does not always have fixed features associated with it. Instead, and depending on the context, this information can move from one feature to the other making the task of learning errors difficult. Here we present a solution to this problem by exploring clustered structure of data in high-dimensional spaces and analyse the effectiveness of these algorithms when presented with training samples of full input spaces. In addition to correcting errors, we test the outlined algorithms in the task of detecting adversarial attacks in a full input space. To illustrate the concepts in use, a case study is given which demonstrates the adaptive removal of false positives in an object-detection AI census system being developed for use in industry.","PeriodicalId":138951,"journal":{"name":"2022 4th International Conference on Industrial Artificial Intelligence (IAI)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123289626","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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