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Prediction of Energy Consumption in Digital Twins of Intelligent Factory by Artificial Intelligence 3

Prediction of Energy Consumption in Digital Twins of Intelli...

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3rd international conference on Technology and Policy in Energy and Electric Power, ICT-PEP 2021

作者： Wu, Jingyi Dang, Yukun Jia, Hongxiang Liu, Xinyue Lv, Zhihan Qingdao University School of Computer Science and Technology Qingdao China

ISBN: (纸本)9781665416412

The goal is to explore the prediction performance of energy consumption in digital twins of the intelligent factory in the process of urbanization, so that it can provide good guidance for the green development of cities. The digital twin technology is introduced into the intelligent factory, in view of the influence of life cycle, data transmission delay and other factors of the equipment on product energy consumption of intelligent factory manufacturing in the real physical environment. Meanwhile, it is improved by DL (deep learning) algorithm to construct an improved AlexNet algorithm framework. Then, DPFS (Differential Privacy Frequent Subgraph) algorithm is adopted to build a digital twin energy consumption prediction model of intelligent factory based on DL and privacy algorithm. Finally, a simulation scenario is established to verify its performance. Through the comparative analysis of the digital twin energy consumption prediction model and other scholars' models in related fields, the feature recognition accuracy of the constructed model reaches 89.23%, at least 1.95% higher than that of other neural network models. From the perspective of energy consumption data transmission performance, the data message delivery rate of the proposed model is not less than 80%. Besides, the data message leakage rate and packet loss rate are less than 11%, and the average delay is basically stable. Therefore, the constructed model can achieve high energy consumption data transmission security performance under the premise of ensuring the prediction accuracy, which can provide experimental basis for the prediction of energy consumption and the improvement of security maintenance performance in intelligent factories. © 2021 IEEE.

关键词： Deep learning

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3rd EAI international conference on Artificial Intelligence for Communications and Networks, AICON 2021

3rd EAI International Conference on Artificial Intelligence ...

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3rd EAI international conference on Artificial Intelligence for Communications and Networks, AICON 2021

ISBN: (纸本)9783030901950

The proceedings contain 80 papers. The special focus in this conference is on Artificial Intelligence for Communications and Networks. The topics include: Power Quality Prediction of Active Distribution Network Based on CNN-LSTM Deep Learning Model;System simulation and Coverage Analysis of 5G NR Communication System Based on 700 MHz Frequency Band;The Influence of Navigation and Remote Sensing LEO Satellite Attitude on BDS Augmentation;LEO-Assisted Beidou B1C Signal Acquisition algorithm and On-Orbit Verification;Research on Ship Target Detection in SAR Image Based on Improved YOLO v3 algorithm;Energy Efficiency Optimization for Plane Spiral OAM Mode-Group Based MIMO-NOMA Systems;Energy Efficient Resource Allocation for UCA-Based OAM-MIMO System;Experimental Study on Target Localization for DTMB-Based Passive Bistatic Radar;application of Artificial Intelligence in the Planning of Navigation Satellite in Orbit Reconstruction Tasks;Fast Beam Switching Based on Machine Learning for MmWave Massive MIMO Systems;Coordinated Beamforming Optimization with Interference Suppressing for Massive MIMO Systems;Mobile Load Balancing for 5G RAN Slicing in Mobile Network;dynamic Communication and Computation Resource Allocation algorithm for End-to-End Slicing in Mobile Networks;Passive Target Detection Based on GLRT Using Multi-satellite Illumination;passive Target Detection Based on Rao Using Multi-satellite Illumination;environment-Driven Modulation and Coding Schemes for Cognitive Multicarrier Communication Systems;Secure Communications for Dual-UAV-MEC Networks;An Improved MAX-Log MPA Multiuser Detection algorithm in SCMA System;An Adaptive Slice Type Decision algorithm for HEVC Based on Local Luminance Histogram;research on Sound Source Recognition algorithm of Pickup Array Based on Adaptive Background Noise Removal;service Migration Based on Replaying.

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3rd EAI international conference on Artificial Intelligence for Communications and Networks, AICON 2021

3rd EAI International Conference on Artificial Intelligence ...

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3rd EAI international conference on Artificial Intelligence for Communications and Networks, AICON 2021

ISBN: (纸本)9783030901981

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Time Allocation in Multi-UAV Energy Harvesting Network 1

引用

3rd EAI international conference on Artificial Intelligence for Communications and Networks, AICON 2021

作者： Li, Yuchen Zhou, Cong Shi, Shuo Xu, Zhenyu Harbin Institute of Technology Harbin150001 China International Innovation Institute of HIT in Huizhou Guangdong516000 China Huizhou Engineering Vocational College Guangdong516023 China

ISBN: (数字)9783030901998

ISBN: (纸本)9783030901981

To handle the problem of energy scarcity and make up for the lack of working ability of single unmanned aerial vehicle (UAV), we studies the time allocation problem in multi-UAV energy harvesting network. In order to get the nodes which each UAV communicates with, we propose a node allocation scheme based on Kuhn-Munkres (KM) algorithm, and give the trajectory of multiple UAVs. Selection weight is designed to make the UAV select next node according to the shortest moving distance. Then we use convex optimization method to get the dual problem of the optimization problem and solve the time allocation problem which maximizes the system throughput. Finally, the simulation results show that our node assignment scheme can achieve better system performance than clustering node assignment scheme. © 2021, ICST Institute for computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Convex optimization Energy harvesting Multi-UAV Time allocation

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Multi-sensor Information Fusion algorithm Based on Power-Average Operator and D-S Evidence Theory 1

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3rd EAI international conference on Artificial Intelligence for Communications and Networks, AICON 2021

作者： Chen, Bohang Ma, Jun Yongjie, Zhou Zhang, Lingfei The Computer College Qinghai Normal University Xining810008 China Academy of Plateau Science and Sustainability Qinghai Normal University Xining810008 China

ISBN: (数字)9783030901998

ISBN: (纸本)9783030901981

Data fusion algorithm based on power-average operator and D-S evidential theory is proposed to solve the problem of information loss or low accuracy in single sensor data acquisition, which is based on multi-sensor information. Firstly, the outliers of multi-sensor data are removed. Considering the problem of the increase of computation caused by the overuse of redundant information, a dynamic sliding window method is proposed to reduce the data usage. Then, the first data fusion is carried out by using the power average operator. Finally, a hierarchical decision-making method is proposed, according to the characteristics of wireless sensor networks, and the conflict of D-S evidence theory is processed by setting the evidence threshold. The simulation results show that this method can solve the problems of inaccurate information loss and D-S evidence theory conflict in single sensor information acquisition. compared with other algorithms, the recognition rate of H1 is 0.81, the decision-making effect is good, and it has the advantages of relatively simple calculation. © 2021, ICST Institute for computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： D-S evidence theory Hierarchical decision-making Information fusion Power-average algorithm Sliding window

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Bullet Engraving Automated Comparison Optimization Method Based on Second Moment Invariant 3

Bullet Engraving Automated Comparison Optimization Method Ba...

引用

2020 3rd international conference on modeling, simulation and Optimization Technologies and Applications, MSOTA 2020

作者： He, Chenggang Ding, Chris H. Q. Chen, Sibao Wang, Jiaxin Tan, Shicheng Key Lab of ICandSP of Moe School of Computer Science and Technology Anhui University Hefei China School Department of Computer Science and Engineering University of Texas at Arlington ArlingtonTX United States

In the research of bullet engraving comparison method at home and abroad, the traditional method is through visual observation by microscope, comparing line-Type engraving of two bullets to distinct whether the line match, which is inefficient and having big error. In this paper we proposed method based on moment invariant to identify the bullet engraving, which eliminate the actual measurement error (translation error and rotation error). Finally we get the high performance result of bullet engraving identifying based on second moment invariant. © Published under licence by IOP Publishing Ltd.

关键词： Errors

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A Privacy Enhancement Scheme Based on Blockchain and Blind Signature for Internet of Vehicles 3rd

A Privacy Enhancement Scheme Based on Blockchain and Blind S...

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3rd international conference on Blockchain and Trustworthy Systems, Blocksys 2021

作者： Wang, Huajie Gan, Jin Feng, Yong Li, Yingna Fu, Xiaodong Yunnan Key Laboratory of Computer Technology Applications Kunming University of Science and Technology Yunnan Kunming650500 China

ISBN: (纸本)9789811679926

In Internet of Vehicles (IoV), it is getting increasing interests how to enhance the privacy of vehicles while commucating with other vehicles or Infrastructres. This paper proposes a vehicle privacy protection scheme based on blockchain and blind signature. Each vehicle has its own private key, and uses it to generate the correspongding public key. Then the vehicle obtains a digital certicate from the certicate authority (CA) through a blind signature algorithm, which ensures that the real identity information of the vehicle is strictly condential. When CA issues a certicate to a vehicle, the public key of the vehicle is stored in the blockchain. In vehicle-to-vehicle communication, the receiver can perform a hash operation with the sender’s public key to obtain a Merkel’s root value, and compare it with the root in the blockchain to confirm the legitimacy of the sender’s identity. simulation experiment results verify the effectiveness and applicability of the proposed scheme. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Vehicles

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3rd EAI international conference on Multimedia Technology and Enhanced Learning, ICMTEL 2021

3rd EAI International Conference on Multimedia Technology an...

引用

3rd EAI international conference on Multimedia Technology and Enhanced Learning, ICMTEL 2021

ISBN: (纸本)9783030825645

The proceedings contain 97 papers. The special focus in this conference is on Multimedia Technology and Enhanced Learning. The topics include: Research on the Method of Eliminating Duplicated Encrypted Data in Cloud Storage Based on Generated Countermeasure Network;design of Distributed Hybrid Pipeline Multimedia Aided Scheduling System;intelligent Scheduling of Distributed Displacement Pipeline Based on Hybrid Discrete Drosophila Optimization algorithm;research on Grid Planning Method of Distribution Network Based on Artificial Intelligence Technology;intelligent Monitoring Method for Backstage Data Security of Tourism Information Promotion Platform Based on Cloud Computing;preface;research on Multithreaded Data Scheduling Control Method for Power Communication Based on Wireless Sensor;research on Industrial Product modeling Design Method Based on Deep Learning;a Frequency Conversion Circuit for Piezoelectric Vibrating Energy Harvesting;an Adaptive Optimization Strict Reverse Navigation algorithm for Ship Fine Alignment Process;research on Load Feature Extraction Method of Typical Users Based on Deep Learning;enterprise Financial Risk Early Warning System Based on Catastrophe Progression Method;research on Transportation Route Planning Method of Regional Logistics Network Based on Transfer Learning;simultaneous Localization of Multiple Defects in Software Testing Based on Reinforcement Learning;Design of Embedded Network Human Machine Interface Based on VR Technology;Design of Information Security System Based on JSP Technology and Reinforcement Model;sliding Mode Adaptive Control for Sensorless Permanent Magnet Synchronous Motor;recognition Method of Metal Material Pitting Defect Based on Visual Signal Processing;an Improved Detection Method of Safety Helmet Wearing Based on CenterNet;influence Maximization Based on True Threshold in Social Networks;arabic Question-Answering System Using Search Engine Techniques.

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3rd EAI international conference on Multimedia Technology and Enhanced Learning, ICMTEL 2021

3rd EAI International Conference on Multimedia Technology an...

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3rd EAI international conference on Multimedia Technology and Enhanced Learning, ICMTEL 2021

ISBN: (纸本)9783030825614

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A Fuzzy Clustering Based Collaborative Filtering algorithm for Time-Aware POI Recommendation 3

A Fuzzy Clustering Based Collaborative Filtering Algorithm f...

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2020 3rd international conference on modeling, simulation and Optimization Technologies and Applications, MSOTA 2020

作者： Yin, Minghao Liu, Yanheng Zhou, Xu Sun, Geng College of Computer Science and Technology Jilin University Changchun Jilin China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun Jilin China Center for Computer Fundamental Education Jilin University Changchun Jilin China

Location based social network develops and gets widely concern along with the population and widespread use of mobile. Point of interest(POI) recommendation become one of the most widely application among location-based service. To get better POI recommendation performance, a fuzzy clustering based collaborative filtering algorithm (FCCF) for time-Aware POI recommendation is proposed in this paper. It first constructs the user feature vector from users' check-in behaviours. Individual's check-in behaviour can be under the influence of location region and time slots, so user's feature consists of two parts. One is the vising frequency of each user in different location regions, and the other is the vising frequency of each user in different time slots. Next fuzzy c-means is adopted due to its simplicity to group users according to user feature vector. Then the user similarity computation can be limited in the similar small user groups. In the end, a collaborative filtering algorithm is applied to recommend a number of top-N POIs at a given time for the target user. Some experiments are conducted and the comparative results on Foursquare and Gowalla show that FCCF has higher precision and recall value than the comparative algorithms. © Published under licence by IOP Publishing Ltd.

关键词： Fuzzy clustering

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