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检索条件"任意字段=2021 3rd International Conference on Computer Modeling, Simulation and Algorithm, CMSA 2021"

共 219 条记录，以下是141-150 订阅

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Social Network Management of Safety Risk in Prefabricated Building Construction Based on computer simulation 3

Social Network Management of Safety Risk in Prefabricated Bu...

引用

3rd international conference on Artificial Intelligence and Advanced Manufacture, AIAM 2021

作者： Yang, Yu Chen, Yan Zhang, Hanxin School of Management Engineering Qingdao Technological University QingDao China

ISBN: (纸本)9781450385046

At present, the research on the safety risk of prefabricated construction mostly regards the risk factors as independent points, and there is little research on the interaction between the risk factors. Firstly, this paper identifies and classifies the safety risk factors of prefabricated building construction from the two-dimensional perspective of safety risk dimension and safety accident, and establishes the 1-model network of the relationship between construction safety risk factors and the 2-model network model of construction safety risk and safety accident by using social network analysis (SNA);Secondly, combined with 1-mode network block model analysis, overall network density analysis and 2-mode network centrality analysis, the core risk factors are identified, the key relationship of security risk is obtained by analyzing the middle centrality of 1-mode network line, and the Countermeasures for the core risk and key relationship are further put forward;Finally, combined with computer simulation technology, the effect of risk control is tested. According to the computer modeling and simulation technology, the results show that controlling the core risk factors and blocking the transmission of key risk relationships can reduce the complexity of the whole risk network. This model can effectively improve the safety degree of prefabricated construction project and reduce the occurrence of safety accidents. © 2021 ACM.

关键词： Social networking (online)

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Minimum UAV Fog Servers with Maximum IoT Devices Association Using Genetic algorithms 3

Minimum UAV Fog Servers with Maximum IoT Devices Association...

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3rd IEEE international Multidisciplinary conference on Engineering Technology, IMCET 2021

作者： Abbas, Nadine Abusrewil, Rayan Najjar, Amir Sharafeddine, Sanaa Lebanese American University Department of Computer Science and Mathematics Beirut Lebanon

ISBN: (纸本)9781665405874

Internet of Things (IoT) has emerged as a new technology to enhance many services and applications including the industrial sector;thus, enabling the Industry 4.0 among many others. IoT created many challenges as the services response time requirements have grown more strict and urged the need for faster means of communications and computation processing. To solve this problem, fog computing has emerged to serve IoT devices at closer distances than cloud computing. In this paper, we leverage the Unmanned Aerial Vehicles (UAVs) mounted cloudlets to provide computation offloading opportunities to IoT devices while meeting the latency constraints. We aim at deploying the minimum number of UAVs to serve the maximum number of IoT devices within their deadlines subject to communication and computation constraints. We first formulate the problem as a multi-objective optimization problem which can be shown to be mixed-integer non-linear program (MINLP) and is NP-hard. We then propose a heuristic sub-optimal approach based on genetic algorithm (GA) to decide on the minimum number of UAVs to be deployed and the IoT-to-UAV association. simulation results demonstrated the efficiency of the proposed approach under different system parameters and constraints in minimizing the number of UAVs while maximizing the number of served IoT devices. © 2021 IEEE.

关键词： Genetic algorithms

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Estimation of Synchrophasor Parameters in the Presence of 3rd & 5th Harmonics and White Gaussian Noise 8th

Estimation of Synchrophasor Parameters in the Presence of 3r...

引用

8th EAI international conference on Advancement of Science and Technology, ICAST 2020

作者： Gizaw, Kassaye Ygzaw, Alganesh Bantyirga, Belachew Aberie, Habtemariam Bahir Dar Institute of Technology Bahir Dar Ethiopia

ISBN: (纸本)9783030806200

Nowadays, power systems, particularly distribution networks, often operate close to their stability limit due to the rapid growth of new customers and inauguration of industrial sectors. Though the advancement of renewable energy sources (RESs) and Flexible Alternating Current Transmission (FACT) devices are the right solutions to meet these demands, they increase the network’s complexity and dynamic behavior. To solve these complexities, introducing advanced controllers that are fast, accurate, and have a reliable synchronization method is the most effective solution. On this basis, one of the foremost promising technologies that constitute the backbone of wide-area and local monitoring systems in real-time is the Phasor Measurement Units (PMU) device. Thus, in this paper, the synchrophasor estimation (SE) algorithm, which is the main component to build up a PMU, is developed using the iterative interpolated DFT technique. Even if the analyzed interferences are two harmonics (3rd and 5th), the developed algorithm can work for any type and number of interferences. Based on the simulation result demonstration, the algorithm can effectively estimate the amplitude, phase, and frequency within the maximum error of 0.039, 0.002, and 0.0001. This research work can solve various interrelated problems of electrical utilities for those lacking a tool that can trace the system at proper time snapshot like in our country Ethiopia. © 2021, ICST Institute for computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Discrete Fourier transforms

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A feature clustering-based IP localization algorithm 3

A feature clustering-based IP localization algorithm

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2021 3rd international conference on Artificial Intelligence and computer Science, AICS 2021

作者： Gan, Yong Wang, Yifan Jia, Dongwei 1 Zhengzhou Institute of Engineering and Technology Zhengzhou Henan China 2 School of Computer and Communication Engineering Zhengzhou University of Light Industry Zhengzhou Henan China

The geographic location of network IP is an important foundation of location-based services, which plays an increasingly important role in people’s daily life and work. However, the existing IP location methods based on database query, network measurement and machine learning often have some problems, such as poor timeliness, low reliability, difficult feature modeling and so on, or need a large amount of user data as support, which is often only suitable for the more ideal network environment, so the positioning accuracy and applicability are far from the actual needs. To solve this problem, this paper proposes an IP location method based on clustering. The initial IP address of the classifier is located by training. Combined with the method of IP address database matching, the accurate location of IP address is finally realized. Experimental results show the effectiveness of the method. © Journal of Physics: conference Series 2021.

关键词： Support vector machines

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Fault Diagnosis Method of Rotating Machinery Based on CEEMDAN-LSTM Model 3

Fault Diagnosis Method of Rotating Machinery Based on CEEMDA...

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3rd international conference on modeling, simulation, Optimization and algorithm, ICMSOA 2021

作者： Wang, Peng Zhou, Yiren Zhang, Lan School of Mechanical Engineering Tianjin University Tianjin China Nanchang University of Technology Jiangxi Nanchang China International Institute for Innovative Design and Intelligent Manufacturing Tianjin University in Zhejiang Zhejiang Shaoxing China

To overcome the shortcomings of traditional feature extraction methods that rely on prior knowledge and expert experience in the field and the problems of shallow machine learning in fault diagnosis, such as inability to extract deep features, low accuracy of model recognition and poor generalization ability, a fault diagnosis method based on complete ensemble empirical mode decomposition with adaptive noise and long short-term memory (CEEMDAN-LSTM) model is proposed. Firstly, the original signal is decomposed by complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN);secondly, the temporal features of selected component signals are extracted by long short-term memory (LSTM);thirdly the temporal features of each component are concatenated into feature vectors according to the order of high and low frequencies;finally, the feature vectors are input into the softmax layer to get the fault classification category. The results of gear box fault diagnosis test show that the model can effectively identify the fault location. Compared with empirical mode decomposition and support vector machine (EMD-SVM) model and LSTM model, CEEMDAN-LSTM model can obtain the highest fault identification accuracy. © Published under licence by IOP Publishing Ltd.

关键词： Empirical mode decomposition

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An Improved LEACH Protocol Based on Location and Residual Energy for Wireless Sensor Networks 22

An Improved LEACH Protocol Based on Location and Residual En...

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3rd Asia-Pacific conference on Image Processing, Electronics and computers, IPEC 2022

作者： Liu, Yongmin Shi, Tingting Liu, Yiming Liu, Hanlin Xu, Zhuonong School of Computer and Information Engineering Central South University of Forestry and Technology Changsha China Research Center of Smart Forestry Cloud Central South University of Forestry and Technology Changsha China

ISBN: (纸本)9781450395786

Normally, in the classical Low Energy Adaptive Clustering Hierarchy protocol (LEACH), the choice of cluster heads does not rely on the location of node and the residual energy of node. Under the circumstances, the cluster head nodes often die prematurely, resulting in a short lifetime of the whole network. Based on traditional LEACH protocols, this paper gave a new rule of cluster formation by K-means clustering method. When ordinary nodes are upgraded to cluster head nodes, the location and residual energy of nodes are comprehensive considered to improve the election method of cluster head. At the same time, the ordinary node closing to the sink node is marked as a special node, and it jumps out of the cluster structure to transmit data directly to the sink node. Thus, the LEACH-CS (Cluster Selection) algorithm was proposed. Then, we derived the formula of total energy consumption, calculated the optimal value of the number of cluster centers in the lowest energy consumption and the selection of special node distance by mathematical deduction. Finally, the effectiveness of the method was verified by simulations. The simulation results demonstrate that compared with the traditional LEACH protocol and LEACH-C protocol, the proposed algorithm LEACH-CS can effectively reduce the total energy consumption of the network and greatly prolong the network lifetime. © 2022 ACM.

关键词： Energy utilization

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Research on an intelligent path planning algorithm for robot using electrical control technology 3

Research on an intelligent path planning algorithm for robot...

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3rd international conference on Electrical, Communication and computer Engineering, ICECCE 2021

作者： Li, Rui Wang, Zexiao Yan, Dongwen Department of Electrical and Computer Engineering University of Illinois at Chicago ChicagoIL60607 United States College of Mechanical and Electrical Engineering Beijing University of Chemical Technology Beijing100000 China School of Intelligent Equipment Shandong University of Science and Technology Shandong Taian271000 China

In view of the shortcomings of traditional genetic algorithm in path planning, such as infeasible path, falling into local optimization, too many turning times and so on, an improved adaptive genetic algorithm is proposed. A priori knowledge is used to optimize the initial population, and the initial population that does not intersect with obstacles is obtained. The probability formulas of crossover and mutation are designed to avoid falling into local optimization, so as to improve the convergence speed. The smoothness of the path and the shortest path are introduced into the fitness function as the evaluation criteria to make the planned path more efficient. The simulation results show that: compared with the basic algorithm, when the number of obstacles is 20:00, the path of the improved algorithm is reduced by 4.2%;when the number of obstacles is 115, the path is reduced by 25.1%. With the continuous increase of obstacles, the percentage of path reduction shows an upward trend, and the number of iterations of the algorithm and the number of turning points in the path are better than the basic genetic algorithm. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Motion planning

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Research on wind speed prediction model of least squares support vector machine through genetic algorithm optimization 3

Research on wind speed prediction model of least squares sup...

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3rd international conference on Electrical, Communication and computer Engineering, ICECCE 2021

作者： Li, Shan Xu, Kexin Zhang, Yipeng School of Computer and Information Science Chongqing Normal University Chongqing400000 China Business College of Southwest University Chongqing402400 China School of Computer Science and Technology East China Normal University Shanghai200062 China

Wind energy has become the fastest-growing new energy source due to its environmentally friendly sustainability and has been widely used in wind power generation. Wind speed prediction is crucial to the stable operation of the power generation system. Accurately obtaining the change trend of wind speed can effectively reduce the adverse effects of wind farms on the operation of the power system. In recent years, big data technologies such as data mining and artificial intelligence have gradually become a research trend, and they have good solutions to complex nonlinear regression and classification problems. Therefore, based on machine learning and optimization algorithms, this paper combines genetic algorithm with LS-SVM, and proposes a genetic algorithm to optimize the prediction model of LS-SVM. The simulation results show that: compared with a single LS-SVM prediction model, the genetic algorithm optimized LS-SVM prediction model error is smaller and has higher prediction accuracy. This prediction method has certain practical significance. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Genetic algorithms

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Research on nonlinear identification control based on exercise quality analysis and computer numerical simulates with MATLAB 3

Research on nonlinear identification control based on exerci...

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3rd international conference on Artificial Intelligence and Advanced Manufacture, AIAM 2021

作者： Gou, Xiaoping Zhang, Wanjun Zhang, Feng Zhang, Jingxuan Qi, Yu Zhang, Wenlan School of Physical Education Longdong University Qingyang745000 China Gansu Zede Electronic Technology Company Limited Tianshui741003 China Lanzhou Industry and Equipment Company Limited Lanzhou730050 China Jingning County Gangou Middle School Pingliang743412 China

ISBN: (纸本)9781450385046

Aiming at the problems of non-linear physical exercise, difficult predictive model identification control and difficult control target, this paper presents an algorithm of non-linear identification control for physical exercise, establishes a control system of non-linear identification control for physical exercise, and simulates it with MATLAB. The simulation results show that the identification ability of physical exercise is strong, the requirements of improving the quality of physical exercise, the control ability and anti-interference ability are increased. © 2021 ACM.

关键词： MATLAB

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Multi-objective Task Scheduling algorithm Based on Harmony Search for Grid Microservice Optimization 3

Multi-objective Task Scheduling Algorithm Based on Harmony S...

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

作者： Xie, Yuqing Wang, Yuan Jiang, Ying Peng, Zirong Wang, Yongli Information and Telecommunication Branch State Grid Zhejiang Electric Power Corporation Hangzhou310000 China State Grid Electric Power Research Institute Co Ltd Nanjing211100 China China Realtime Database Co Ltd Nanjing211100 China School of Computer Science and Technology Nanjing University of Science and Technology Nanjing210094 China

In order to solve the multi-objective task scheduling optimization problem of data platform microservice combination, this paper proposes an improved harmony search algorithm MODRHS, which fuses the multi-objective optimization NSGA-II algorithm, and improve its elite selection strategy by a circular elimination method, and strengthens the uniformity of the non-dominated solutions at first layer and improves the algorithm's Pareto optimization ability. At the same time, it describes the mathematical expression of the Dockers model and service optimization goals of the data platform microservice scheduling. The improved harmony search algorithm is applied to practical problems. The performance test of MODRHS is carried out through standard test functions and real data sets. Compared with other classic multi-objective optimization algorithms, the convergence and diversity of the MODRHS algorithm have been effectively improved. © Published under licence by IOP Publishing Ltd.

关键词： Multiobjective optimization

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