2022 4th International Conference on Artificial Intelligence and Advanced Manufacturing (AIAM)最新文献_第2页

Adaptive design and grasping motion analysis of a four-fingered dexterous hands 四指灵巧手的自适应设计与抓握运动分析

2022 4th International Conference on Artificial Intelligence and Advanced Manufacturing (AIAM) Pub Date : 2022-10-01 DOI: 10.1109/AIAM57466.2022.00131

Yu Feng, Fei Li, Jianzhe Min

引用次数: 0

An Energy Optimization Algorithm for Data Centers based on Deep Q-learning with Multi-Source Energy 基于深度q -学习的多源能量数据中心能量优化算法

2022 4th International Conference on Artificial Intelligence and Advanced Manufacturing (AIAM) Pub Date : 2022-10-01 DOI: 10.1109/AIAM57466.2022.00079

Hui Yu, Mingxiu. Tong

{"title":"An Energy Optimization Algorithm for Data Centers based on Deep Q-learning with Multi-Source Energy","authors":"Hui Yu, Mingxiu. Tong","doi":"10.1109/AIAM57466.2022.00079","DOIUrl":"https://doi.org/10.1109/AIAM57466.2022.00079","url":null,"abstract":"More and more data centers are supplied by multi-source energy. However, the features of random, uncertain, and time-varying of renewable energy has made it difficult to achieve good results with traditional methods. In this paper, we research how to coordinate multiple energy sources (such as wind power, solar, and smart grids) to reduce energy costs of data centers. We propose a deep Q-learning (DQN) algorithm based on the auto encoder to control the energy consumption of data center. Our algorithm uses the auto encoder to approximate the Q-value function, learning the expected cost based on the state of current system. It solves the problem that the Q-value function in traditional Q-learning algorithm is difficultly designed under multi-constraint conditions, and it can converge by any state of the system to obtain the optimal solution. In order to further improve the convergence speed and accuracy of the algorithm. We design a parameter optimization strategy to solve the slow convergence problem of the algorithm. This strategy is based on the experience replay technology to optimize the parameters of algorithm. We conducted extensive experiments based on real- world data, and evaluated the performance of our algorithm. The experiment results show that our algorithm can average save 20% energy cost so as to bring a set of safe and highly available solution to meet the requirements of multi-Source energy for data centers.","PeriodicalId":439903,"journal":{"name":"2022 4th International Conference on Artificial Intelligence and Advanced Manufacturing (AIAM)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126366649","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

Dataset Outlier Detection Method Based on Random Forest Algorithm 基于随机森林算法的数据集离群点检测方法

2022 4th International Conference on Artificial Intelligence and Advanced Manufacturing (AIAM) Pub Date : 2022-10-01 DOI: 10.1109/AIAM57466.2022.00111

Ying-gang Zheng

{"title":"Dataset Outlier Detection Method Based on Random Forest Algorithm","authors":"Ying-gang Zheng","doi":"10.1109/AIAM57466.2022.00111","DOIUrl":"https://doi.org/10.1109/AIAM57466.2022.00111","url":null,"abstract":"Outlier detection plays a very important role in real life, and requires long-term and continuous study and research in this field. The purpose of this paper is to study outlier detection methods for datasets based on the random forest algorithm. This paper briefly describes the research background and significance of the field of outlier detection, the research status at home and abroad, the application of outlier detection in various real-world scenarios, and some research problems that need to be solved urgently. The concept of outliers is summarized, and random forests and locality-sensitive hashing algorithms are briefly introduced. The RHSForest algorithm is proposed, the idea and process of the algorithm are discussed in detail, and the parameter settings and evaluation indicators are discussed in detail. Then the RHSForest algorithm is verified and evaluated by experiments. The experimental results are then analyzed, and the experimental results on 5 benchmark datasets show that the RHSForest algorithm has an AUC value of up to 95% in the Glass dataset, providing consistent performance improvements for the detection of outliers.","PeriodicalId":439903,"journal":{"name":"2022 4th International Conference on Artificial Intelligence and Advanced Manufacturing (AIAM)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126405276","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

Analyzing the Influence of Different Activation Functions Based on Deep Learning Model for Facial Expression Recognition 基于深度学习模型的不同激活函数对面部表情识别的影响分析

2022 4th International Conference on Artificial Intelligence and Advanced Manufacturing (AIAM) Pub Date : 2022-10-01 DOI: 10.1109/AIAM57466.2022.00143

Tian Xia

{"title":"Analyzing the Influence of Different Activation Functions Based on Deep Learning Model for Facial Expression Recognition","authors":"Tian Xia","doi":"10.1109/AIAM57466.2022.00143","DOIUrl":"https://doi.org/10.1109/AIAM57466.2022.00143","url":null,"abstract":"Facial expressions are an important channel for people to communicate their emotions. To more accurately recognize people's facial expressions, researchers are constantly exploring the possibilities of convolutional neural networks. For convolutional neural network models, many factors can have a significant impact on the performance, including the structure and parameters. In this paper, it analyze the impact of different activation functions on the deep learning model of facial expression recognition with the FER-2013 dataset, compare the advantages and disadvantages between traditional and new activation functions, and finally build a deep learning model of facial expression recognition with better performance. In addition to the baseline CNN model, the paper also analyzes the performance of famous deep learning models such as ResNet, VGG and Inception, from which the best-performing baseline CNN model is selected to explore the impact of different activation functions. The results show that the GELU activation function-based facial expression deep learning model has the best performance and the highest recognition accuracy among the activation functions ReLU, L-ReLU/P-ReLU, Swish, etc. Compared with the deep learning model with the traditional ReLU activation function, the facial expression deep learning model based on GELU activation function constructed in this paper approximately improves the accuracy by 1%.","PeriodicalId":439903,"journal":{"name":"2022 4th International Conference on Artificial Intelligence and Advanced Manufacturing (AIAM)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121781174","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

Conformance requirements and test standard research for communication protocols of electric vehicle wireless power transfer 电动汽车无线电力传输通信协议一致性要求及测试标准研究

2022 4th International Conference on Artificial Intelligence and Advanced Manufacturing (AIAM) Pub Date : 2022-10-01 DOI: 10.1109/AIAM57466.2022.00162

Bao-Sheng Zhang, Y. Li, Jin Li, Bin Fan, Ming Liang, Chao Hu

引用次数: 0

Siting of Electric Vehicle Charging Stations Based on User Behavior 基于用户行为的电动汽车充电站选址

2022 4th International Conference on Artificial Intelligence and Advanced Manufacturing (AIAM) Pub Date : 2022-10-01 DOI: 10.1109/AIAM57466.2022.00108

Ziqiong Ding, Cao Li, Chen An, Hao Ding, Zibao Lu, Youhong Feng

引用次数: 0

Thermoelectric Coupled Analyses of the Thermal and Electric Fields at the Tulip Contact for a Medium-Voltage Switchgear 中压开关柜郁金香接点的热电耦合分析

2022 4th International Conference on Artificial Intelligence and Advanced Manufacturing (AIAM) Pub Date : 2022-10-01 DOI: 10.1109/aiam57466.2022.00117

M. Wu, Wei Yang, Jie Chen, Xue Wang, Lei Shi

引用次数: 0

Development of Standard Measurement Device for 0.1Hz VLF Dielectric Loss Tester 0.1Hz VLF介质损耗测试仪标准测量装置的研制

2022 4th International Conference on Artificial Intelligence and Advanced Manufacturing (AIAM) Pub Date : 2022-10-01 DOI: 10.1109/AIAM57466.2022.00170

Sansheng Shi, Wen Wang, Wenqi Zhi, Minzhe Tian, Mengxi Li

{"title":"Development of Standard Measurement Device for 0.1Hz VLF Dielectric Loss Tester","authors":"Sansheng Shi, Wen Wang, Wenqi Zhi, Minzhe Tian, Mengxi Li","doi":"10.1109/AIAM57466.2022.00170","DOIUrl":"https://doi.org/10.1109/AIAM57466.2022.00170","url":null,"abstract":"Dielectric loss is an important characterization of insulation performance of power cable. Measuring the dielectric loss of a power cable can effectively evaluate the cable status. There are a large number of power cables, and the operating life is gradually increasing in China's power grids. To prevent accidents and improve the reliability of grid operation, power cable dielectric loss testers are commonly used in 10kV and 35kV power level, but there is still a lack of standard measuring devices to test their performance. For this reason, in this paper, a standard measuring device is proposed, the working principle of the device, the selection method of key components is introduced, and the actual dielectric loss tester using this device is tested. The research results show that the developed device is fit for the calibration of the power cable dielectric loss tester. When the dielectric loss value is high, the difference between the theoretical standard value and the actual measured value is small. However, with the decrease of the dielectric loss of the standard sample, the difference between the theoretical standard value and the actual measured value gradually increases. The reason for this phenomenon is that the capacitor used in the standard test device also has a resistance. The method of recalculating the theoretical standard value considering the resistance value of the capacitor can reduce the difference between the theoretical standard value and the actual measured value, so as to carry out the calibration better.","PeriodicalId":439903,"journal":{"name":"2022 4th International Conference on Artificial Intelligence and Advanced Manufacturing (AIAM)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133879462","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

Research on an Environment-controlled Boat Verification Device 一种环境控制船艇检定装置的研究

2022 4th International Conference on Artificial Intelligence and Advanced Manufacturing (AIAM) Pub Date : 2022-10-01 DOI: 10.1109/AIAM57466.2022.00097

Jing Luan, Huapeng Li, Jun Zhao

{"title":"Research on an Environment-controlled Boat Verification Device","authors":"Jing Luan, Huapeng Li, Jun Zhao","doi":"10.1109/AIAM57466.2022.00097","DOIUrl":"https://doi.org/10.1109/AIAM57466.2022.00097","url":null,"abstract":"Due to the limitation of the environmental conditions on the boat measurement, and under the urgent demand of the instrument measurement in the boat, an environmentally controlled boat verification device is designed. The device focuses on solving the problem that the verification and measurement cannot be conducted under the harsh environmental conditions, and focuses on the constant temperature and constant humidity technology under the high temperature environment, as well as the structure design of the split verification cabin. It provides the automatic adjustment and control function of the micro-environment, so that the verification environment is always in the temperature and humidity index requirements required for the measurement. The verification device follows the design principles of lightweight, modularization, intelligence and standardization, and analyzes the research results that the verification device meets the actual needs, and can solve the environmental condition guarantee problem of on-site metrological verification. It provides a new idea for the subsequent exploration of the new measurement guarantee mode of boat instruments.","PeriodicalId":439903,"journal":{"name":"2022 4th International Conference on Artificial Intelligence and Advanced Manufacturing (AIAM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130916506","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 Optimization Object Detection Model on Brassica Napus Area Based on Image Compression Framework 基于图像压缩框架的甘蓝型油菜区域目标检测优化模型

2022 4th International Conference on Artificial Intelligence and Advanced Manufacturing (AIAM) Pub Date : 2022-10-01 DOI: 10.1109/AIAM57466.2022.00037

Zuhao Ou, Changhua Liu, Daren Jiang

{"title":"An Optimization Object Detection Model on Brassica Napus Area Based on Image Compression Framework","authors":"Zuhao Ou, Changhua Liu, Daren Jiang","doi":"10.1109/AIAM57466.2022.00037","DOIUrl":"https://doi.org/10.1109/AIAM57466.2022.00037","url":null,"abstract":"Using UAV (Unmanned Aerial Vehicle) equipment, it is often easy to take aerial images of brassica napus in the field, and automatically divide the brassica napus areas in the images by the trained object detection network model, which are used for the subsequent research of brassica napus flowering identification. However, the original aerial images obtained from the UAV equipment have a high resolution of about 5427×3078, and each image also takes up more memory space of about 10 MB. In the limit of hardware resource environment, especially in the case of insufficient GPU video memory, if all the original images are used to train the brassica napus object detection model, it will cost a lot of time, and the training process may also fail. To solve the above problems, a modified image compression framework based on deep learning is proposed to process the original aerial images of brassica napus in this paper and compress the storage capacity of the images on the condition of constant image resolution, so as to speed up the training process of brassica napus object detection model. After experimental analysis, the compression ratio of each original image reaches 6.34, and the training time of the brassica napus object detection model is also reduced to 58.7%, achieving the goal of reducing the training time of the model. Finally, the mAP (mean average precision) of the object detection model reaches 97.13%.","PeriodicalId":439903,"journal":{"name":"2022 4th International Conference on Artificial Intelligence and Advanced Manufacturing (AIAM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128878928","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