Proceedings of the 2nd International Conference on Artificial Intelligence and Advanced Manufacture最新文献_第8页

Design and simulation of a new type of high-speed UAV measurement and control radio 新型高速无人机测控无线电的设计与仿真

Proceedings of the 2nd International Conference on Artificial Intelligence and Advanced Manufacture Pub Date : 2020-10-15 DOI: 10.1145/3421766.3421832

Luoyang Zhou, Xiaowei Dong, Jianzhong Qi

引用次数: 0

Research on the Artificial Intelligence Applied in Logistics Warehousing 人工智能在物流仓储中的应用研究

Proceedings of the 2nd International Conference on Artificial Intelligence and Advanced Manufacture Pub Date : 2020-10-15 DOI: 10.1145/3421766.3421798

Xinke Du

引用次数: 2

Research on Recognition of Shoulder Joint Movement Imagination Based on BCI Technology 基于BCI技术的肩关节运动想象识别研究

Proceedings of the 2nd International Conference on Artificial Intelligence and Advanced Manufacture Pub Date : 2020-10-15 DOI: 10.1145/3421766.3421805

Shan Guan, Jilong Wang, Fuwang Wang

引用次数: 0

Fingerprint-based Indoor Localization using Weighted K-Nearest Neighbor and Weighted Signal Intensity 基于加权k近邻和加权信号强度的指纹室内定位

Proceedings of the 2nd International Conference on Artificial Intelligence and Advanced Manufacture Pub Date : 2020-10-15 DOI: 10.1145/3421766.3421813

Liwei Zhang, Changming Zhao, Yunshi Wang, Lei Dai

{"title":"Fingerprint-based Indoor Localization using Weighted K-Nearest Neighbor and Weighted Signal Intensity","authors":"Liwei Zhang, Changming Zhao, Yunshi Wang, Lei Dai","doi":"10.1145/3421766.3421813","DOIUrl":"https://doi.org/10.1145/3421766.3421813","url":null,"abstract":"In the past few decades, wireless indoor positioning systems, especially signal strength fingerprint technology, have become the subject of major research efforts. However, most proposed solutions require an expensive site survey to build a radio map, which can be used to match the radio signature to a specific location. In this study, we proposed a novel fingerprint-based indoor localization using weighted K-nearest neighbor and weighted signal strength, named WKNNS. We adjust the weight of samples by the strength of the signal: reduce the influence of strong signal samples, and increase the influence of weak signal samples. First, the strong signal samples were divided into multiple clusters by dividing. Then, the weak signal samples are divided into those clusters. Thus, multi-sample classification can be turned into a binary classification problem. This algorithm was applied to indoor positioning and obtained better accuracy. Compared with the traditional KNN and Bayesian algorithms, we found that the positioning accuracy of WKNNS after region division is higher than that of Bayesian algorithm. The cumulative error probability distribution of the WKNNS algorithms optimized by the reader is also higher than Bayesian algorithm. The positioning accuracy of the WKNNS algorithm based on the fingerprint conversion model is higher than that based on the signal strength fingerprint.","PeriodicalId":360184,"journal":{"name":"Proceedings of the 2nd International Conference on Artificial Intelligence and Advanced Manufacture","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130760714","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: 3

Research on Light Weight of the Electric Cabinet of CR400BF Standard EMU CR400BF标准动车组电控箱轻量化研究

Proceedings of the 2nd International Conference on Artificial Intelligence and Advanced Manufacture Pub Date : 2020-10-15 DOI: 10.1145/3421766.3421875

Zhenqiang Liu, Xiangli Lin, D. Jia, Dongjun Yang, Jun Zhang, Ting Xin

引用次数: 0

The Performance of Radar Heat Dissipation System under Particle Swarm Optimization Algorithm and Structural Design of Front-end Prototype 粒子群优化算法下雷达散热系统性能及前端样机结构设计

Proceedings of the 2nd International Conference on Artificial Intelligence and Advanced Manufacture Pub Date : 2020-10-15 DOI: 10.1145/3421766.3421810

Zhen Wang, Jinwen Zhou

{"title":"The Performance of Radar Heat Dissipation System under Particle Swarm Optimization Algorithm and Structural Design of Front-end Prototype","authors":"Zhen Wang, Jinwen Zhou","doi":"10.1145/3421766.3421810","DOIUrl":"https://doi.org/10.1145/3421766.3421810","url":null,"abstract":"To clarify the problems of aviation radar in heat dissipation, optimize the overall operational capability of radar equipment, and improve the safety of aviation radar equipment, under the premise of studying the structure of the radar heat dissipation system, by analyzing the operation of the radar heat dissipation system and the motor of the front-end prototype structure, the main reasons for heat dissipation faults are deeply analyzed. The method of statistical process control is utilized to predict the performance of the front-end motor and remind maintenance personnel to monitor the radar heat dissipation system in real-time. At the same time, by using the improved particle swarm optimization (PSO) algorithm model, the factors and kernel functions of the support vector machine (SVM) are optimized, and the regression accuracy of the SVM is improved. Furthermore, the motor failure prediction model is established, thereby ensuring the efficient and safe operating state of the radar system. The results show: (1) the failure of the radar motor is the major cause of heat dissipation faults; (2) compared to other algorithms, the efficiency of the PSO algorithm is improved by 30%, but the accuracy rate drops by 5%; (3) the applications of forewarning model for front-end prototype under statistical process control (SPC) can reduce the workload of maintenance personnel by 50%. The simulation results show that the combined method of SPC and SVM can predict the failure of the powering devices in radar heat dissipation systems. Besides, if the classification and regression models are combined, the difference between the predicted voltage and the true voltage will be smaller, and the accuracy will be higher. The above results provide a theoretical basis for the research of radar heat dissipation system and motor failure, which ensures the overall safety of the radar system and provides the necessary guarantee for the crew and the aviation command system.","PeriodicalId":360184,"journal":{"name":"Proceedings of the 2nd International Conference on Artificial Intelligence and Advanced Manufacture","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121845482","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: 2

Multi-angle SAR Image Fusion Algorithm Based on Optimal Local Image Index 基于最优局部图像索引的多角度SAR图像融合算法

Proceedings of the 2nd International Conference on Artificial Intelligence and Advanced Manufacture Pub Date : 2020-10-15 DOI: 10.1145/3421766.3421885

Da Ran, Fengjie Zheng, Zhiliang Li, Can-bin Yin

引用次数: 1

Prediction Model of Needle Valve Body Extrusion Grinding Process Based on GA-ELM 基于GA-ELM的针阀体挤压磨削过程预测模型

Proceedings of the 2nd International Conference on Artificial Intelligence and Advanced Manufacture Pub Date : 2020-10-15 DOI: 10.1145/3421766.3421887

Chenzhe Sun, Shuzhen Yang, Tao Yu

{"title":"Prediction Model of Needle Valve Body Extrusion Grinding Process Based on GA-ELM","authors":"Chenzhe Sun, Shuzhen Yang, Tao Yu","doi":"10.1145/3421766.3421887","DOIUrl":"https://doi.org/10.1145/3421766.3421887","url":null,"abstract":"There is a complicated non-linear relationship between the process parameters of the needle valve body extrusion grinding and the process effect, it is difficult to establish a complete and accurate process model. Therefore, by introducing genetic algorithm to optimize and improve the ELM extreme learning machine, a complete set of needle valve body process effect prediction model is established. The historical experimental data obtained by the self-developed needle valve body squeezing and grinding equipment were used as sample data for ELM algorithm model and GA-ELM algorithm model training. The results show that the optimized model can significantly improve the prediction accuracy of the data in the sample. The actual processing experiment of the needle valve body is carried out through the process parameter data in and out of the sample, the predicted value is compared with the actual value, and the performance of the accuracy of the predicted model is tested. The comparison results show that the actual data prediction error is kept within ±4%, which basically meets the actual prediction requirements, and thus provides a theoretical basis and reference value for subsequent process optimization.","PeriodicalId":360184,"journal":{"name":"Proceedings of the 2nd International Conference on Artificial Intelligence and Advanced Manufacture","volume":"82 11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124457200","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

New Progress in the Research on the Stability of 3D Footprint Acquisition System and the Application of Personal Identification 三维足迹采集系统稳定性及个人识别应用研究新进展

Proceedings of the 2nd International Conference on Artificial Intelligence and Advanced Manufacture Pub Date : 2020-10-15 DOI: 10.1145/3421766.3421773

Yi Gao

{"title":"New Progress in the Research on the Stability of 3D Footprint Acquisition System and the Application of Personal Identification","authors":"Yi Gao","doi":"10.1145/3421766.3421773","DOIUrl":"https://doi.org/10.1145/3421766.3421773","url":null,"abstract":"The extraction of stereoscopic field footprint has always been a major problem in the field of physical evidence processing, and the application of optical measurement technology and computer technology to extract the footprint of the site has become the main trend of footprint extraction analysis. Although the existing on-site stereoscopic footprint instruments are relatively numerous, the reliability and the stability need to be tested. Therefore, the system stability test of the 3D stereoscopic footprint acquisition instrument is a prerequisite method for instrument application. By verifying the stability of the instrument's effects, obtaining a reliable method for collecting footprints with a 3D footprint acquisition instrument. And then by experimental and statistical analysis of the stability of the three-dimensional footprint left during walking with pseudo-color pictures and indentation, summarizing the phenomenon of stable features in different footprints produced by the same person and realizing the comparison and differences of the footprints of different individuals. It seems to use the three-dimensional footprint acquisition system to collect on-site footprints or even during the subsequent detection and identification applications, which is of great significance to carry out the personal identification technology based on the biometric characteristics of the three-dimensional footprint in the future.","PeriodicalId":360184,"journal":{"name":"Proceedings of the 2nd International Conference on Artificial Intelligence and Advanced Manufacture","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133406250","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

Application of Ergonomics Form in Car Seat Modeling Design 人体工程学形式在汽车座椅造型设计中的应用

Proceedings of the 2nd International Conference on Artificial Intelligence and Advanced Manufacture Pub Date : 2020-10-15 DOI: 10.1145/3421766.3421865

Ya Wen, Weiguo Yang

引用次数: 3