2021 3rd International Conference on Artificial Intelligence and Advanced Manufacture最新文献_第4页

Design and Implementation of Art Design System Based on Artificial Intelligence Processing Technology 基于人工智能处理技术的艺术设计系统的设计与实现

2021 3rd International Conference on Artificial Intelligence and Advanced Manufacture Pub Date : 2021-10-23 DOI: 10.1145/3495018.3495414

Yanyan Li

{"title":"Design and Implementation of Art Design System Based on Artificial Intelligence Processing Technology","authors":"Yanyan Li","doi":"10.1145/3495018.3495414","DOIUrl":"https://doi.org/10.1145/3495018.3495414","url":null,"abstract":"In the process of art design, it is difficult to transform music into image or image into music. However, the intervention of artificial intelligence makes this transformation very easy to achieve. Based on the above background, this paper designs and implements an art design system based on artificial intelligence processing technology. Artificial intelligence technology is helpful to the creation of art design. Firstly, this paper summarizes, summarizes and analyzes the corresponding relationship between art design and system design; secondly, it analyzes the feasibility of applying multi information fusion technology to art design of artificial intelligence processing technology; finally, it uses artificial intelligence technology to accurately depict the art design model of data layer, feature layer, decision layer and multi information fusion, and constructs the art design model based on artificial intelligence processing technology. The model includes data layer, feature layer and decision layer. Among them, RBF neural network, which can deal with nonlinear problems, has the ability of self-learning and fault tolerance, and can quickly make fault classification, is used to build the art design system model of the data layer. At the same time, the integration design test of data layer, feature layer and decision layer is carried out for the art design system model based on artificial intelligence. The experiment verifies the accuracy and timeliness of the art design system model.","PeriodicalId":6873,"journal":{"name":"2021 3rd International Conference on Artificial Intelligence and Advanced Manufacture","volume":"75 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86164994","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

Performance Class Classification of ZPW-2000 Track Circuit Attenuator Based on Probabilistic Neural Network 基于概率神经网络的ZPW-2000轨道电路衰减器性能分类

2021 3rd International Conference on Artificial Intelligence and Advanced Manufacture Pub Date : 2021-10-23 DOI: 10.1145/3495018.3495070

Minggui Huang

{"title":"Performance Class Classification of ZPW-2000 Track Circuit Attenuator Based on Probabilistic Neural Network","authors":"Minggui Huang","doi":"10.1145/3495018.3495070","DOIUrl":"https://doi.org/10.1145/3495018.3495070","url":null,"abstract":"ZPW-2000 uninsulated frequency-shifted rail circuit equipment requires manual testing of electrical parameters in daily maintenance work, resulting in high labor intensity and low work efficiency of maintenance personnel in the field. The intelligent ZPW-2000 track circuit attenuator designed in this article can monitor and display the relevant parameters and equipment status of the track circuit in real time, so that maintenance personnel can directly view the information of the equipment without tedious operation, which can improve maintenance efficiency and equipment reliability. Safety of railroad operation can be ensured. Fault diagnosis of rail circuits is of great importance for the safe operation of railroad operations. First of all, the parameters are collected by using the track circuit wearer and the data are divided into 5 classes according to the existing maintenance experience. The performance classes of the track circuits were diagnosed using probabilistic fault neural networks (PNN). The experimental results show that the correct rate reaches more than 95% and achieves good results, which provides theoretical basis and practical experience for the maintenance of railroad turnout system and improvement of turnout performance.","PeriodicalId":6873,"journal":{"name":"2021 3rd International Conference on Artificial Intelligence and Advanced Manufacture","volume":"130 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86377526","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

Computer Numerical Simulation of the Effect of Coagulant Type on Electroplating Wastewater under Mathematical Calculation 数学计算下混凝剂类型对电镀废水影响的计算机数值模拟

2021 3rd International Conference on Artificial Intelligence and Advanced Manufacture Pub Date : 2021-10-23 DOI: 10.1145/3495018.3501064

Yongli Zhang, Guo-Wen Zhang, Xin Chen

引用次数: 0

Improved Computer Aided Design of Face from the Perspective of Fuzzy Computing and Smart Information System 基于模糊计算和智能信息系统的人脸计算机辅助设计

2021 3rd International Conference on Artificial Intelligence and Advanced Manufacture Pub Date : 2021-10-23 DOI: 10.1145/3495018.3501101

Yanlong Guo

引用次数: 0

Simulation Study on Neutral Grounding Mode of Marine Intermediate Voltage Power System 船用中压电力系统中性点接地方式的仿真研究

2021 3rd International Conference on Artificial Intelligence and Advanced Manufacture Pub Date : 2021-10-23 DOI: 10.1145/3495018.3495108

Yuling Zhou, Guoliang Sun, L. Gao, Yifan Chen, Lu Han

引用次数: 0

Research on College English Teaching Model Based on Information Technology of Artificial Intelligence 基于人工智能信息技术的大学英语教学模式研究

2021 3rd International Conference on Artificial Intelligence and Advanced Manufacture Pub Date : 2021-10-23 DOI: 10.1145/3495018.3495333

Xuanze Zhao

{"title":"Research on College English Teaching Model Based on Information Technology of Artificial Intelligence","authors":"Xuanze Zhao","doi":"10.1145/3495018.3495333","DOIUrl":"https://doi.org/10.1145/3495018.3495333","url":null,"abstract":"The traditional college English teaching model cannot fully meet students' individualized learning needs in terms of teaching methods and teaching evaluation, while the AI-assisted college English teaching can effectively solve the limitations in teaching period, teaching space and evaluation methods, etc. Based on the application of artificial intelligence technology in college English reading, listening, speaking, and writing teaching, this paper discusses the tendency of the traditional college English teaching mode in the era of AI, which offers possibilities of the improvement in college English teaching, and the establishment of a new teaching mode, especially in the natural language processing(NLP) field. Related researches have demonstrated that it will provide a new train of thought and entry point for the reform of teaching mode to apply AI into college English teaching, and it will be as well as significant for achieving teaching goals. Relevant studies show that the application of artificial intelligence to college English education will provide a new train of thought for the reform of teaching mode, and is of great significance to achieve teaching objectives.","PeriodicalId":6873,"journal":{"name":"2021 3rd International Conference on Artificial Intelligence and Advanced Manufacture","volume":"14 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82952818","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 Voice Activity Detection Method Based on TEE 一种基于TEE的语音活动检测方法

2021 3rd International Conference on Artificial Intelligence and Advanced Manufacture Pub Date : 2021-10-23 DOI: 10.1145/3495018.3495154

Lingxiang Xia, Z. Cheng, Changhong Gong, Xiang Zou

引用次数: 0

Cluster Analysis of Consumer's Behaviors Based on Unsupervised Learning 基于无监督学习的消费者行为聚类分析

2021 3rd International Conference on Artificial Intelligence and Advanced Manufacture Pub Date : 2021-10-23 DOI: 10.1145/3495018.3495360

Zhao Zhang

引用次数: 0

Rapid calculation method of pore section hydraulic conductivity based on convolution neural network 基于卷积神经网络的孔隙截面水力导率快速计算方法

2021 3rd International Conference on Artificial Intelligence and Advanced Manufacture Pub Date : 2021-10-23 DOI: 10.1145/3495018.3501057

Yifei An, Liya Duan, Xin Wang, Xi-Ping Jia

{"title":"Rapid calculation method of pore section hydraulic conductivity based on convolution neural network","authors":"Yifei An, Liya Duan, Xin Wang, Xi-Ping Jia","doi":"10.1145/3495018.3501057","DOIUrl":"https://doi.org/10.1145/3495018.3501057","url":null,"abstract":"Structural differences in pore space are the direct factors affecting fluid movement in porous media, while the shape of the pore cross-section determines the process and state of fluid movement, which is closely related to the conductivity in fluid media. Considering the traditional engineering calculations such as pore network models and finite element methods use shape approximation to describe pore cross-sections, which lose part of the shape information. To address the above problems, we proposes a computational method based on convolution neural network to accurately describe the pore cross-section shape by extracting the cross-section shape features and correct the computational misalignment problem of the traditional method. In order to ensure the universality of the method to different rock types, we extract (3779) 2D pore cross-sections from the 3D X-ray images of Bethemier and Limestone samples as the sample set for the training of the convolution neural network model. Finally, the accuracy of the model prediction results and the efficiency comparison with the mainstream methods are given, proving that the method proposed in this paper outperforms other methods in terms of accuracy and efficiency. This work is of significance for oil and gas field exploitation.","PeriodicalId":6873,"journal":{"name":"2021 3rd International Conference on Artificial Intelligence and Advanced Manufacture","volume":"6 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83087196","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

Short Text Generation Based on Adversarial Graph Attention Networks 基于对抗性图注意网络的短文本生成

2021 3rd International Conference on Artificial Intelligence and Advanced Manufacture Pub Date : 2021-10-23 DOI: 10.1145/3495018.3501202

Meng Chen

{"title":"Short Text Generation Based on Adversarial Graph Attention Networks","authors":"Meng Chen","doi":"10.1145/3495018.3501202","DOIUrl":"https://doi.org/10.1145/3495018.3501202","url":null,"abstract":"Text generation has attracted more and more attention in the field of natural language. Recently, GAN (Generative Adversarial Networks) have been widely used in text generation, among which the GAN-based models, such as SeqGAN and SentiGAN, have shown remarkable effects in text generation. However, previous text generation models simply use CNN (Convolutional Neural Networks) as discriminators and ignore relationships between the same-label texts. Meanwhile, most models only consider using a single generator to generate a single species text, not for multispecies texts. To meet the requirements, in this paper, we propose a novel framework model-SGATGAN, which applies GAT (Generative Attention Nets) as the discriminator to establish the connection between the texts of the same type. It also provides a method of generating multispecies texts using a single generator. In this model, the graph attention neural network is used as the discriminator via the feedback to guide the generator in a specific location to generate a specific type of short text. Experimental results on two benchmarks show that our model significantly outperforms previous methods, giving state-of-the-art results in short text generation.","PeriodicalId":6873,"journal":{"name":"2021 3rd International Conference on Artificial Intelligence and Advanced Manufacture","volume":"57 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83103758","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