2022 ELEKTRO (ELEKTRO)最新文献

Research of Multipath Routing and Load Balancing Processes in Software Defined Networks Based on Artificial Bee Colony Algorithm 基于人工蜂群算法的软件定义网络多路径路由与负载均衡过程研究

2022 ELEKTRO (ELEKTRO) Pub Date : 2022-05-23 DOI: 10.1109/ELEKTRO53996.2022.9803416

D. Perepelkin, Tin Nguyen

{"title":"Research of Multipath Routing and Load Balancing Processes in Software Defined Networks Based on Artificial Bee Colony Algorithm","authors":"D. Perepelkin, Tin Nguyen","doi":"10.1109/ELEKTRO53996.2022.9803416","DOIUrl":"https://doi.org/10.1109/ELEKTRO53996.2022.9803416","url":null,"abstract":"Software defined network (SDN) is a cloud computing-oriented approach, that centralizes network device administration, facilitates network management and enables efficient network configuration by software programs to improve performance and enhance network monitoring. In SDN network administrators can shape traffic from a centralized controller without having to set it up on each individual device in the network. The SDN controller can receive information about the links in real-time, as well as distribute and transmit network traffic according to the current network. The aim of this work is research and analysis of multipath routing and load balancing processes in SDN based on artificial bee colony algorithm. In theoretical part an algorithm for multipath routing and load balancing in the SDN based on the model of an artificial bee colony is proposed. In experimental part the simulation results are showed that confirm the effectiveness of the proposed algorithm for solving the problem of multipath routing by avoiding congestion of routes and increasing the planned volume of data packet transmission along all available routes.","PeriodicalId":396752,"journal":{"name":"2022 ELEKTRO (ELEKTRO)","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125007609","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: 1

Domestic Hot Water Heating Prediction with the Utilization of Artificial Neural Network 应用人工神经网络进行生活热水供热预测

2022 ELEKTRO (ELEKTRO) Pub Date : 2022-05-23 DOI: 10.1109/ELEKTRO53996.2022.9803643

P. Belány, P. Hrabovský, Katarina Bednarcikova, Z. Kolková, N. Kantová

{"title":"Domestic Hot Water Heating Prediction with the Utilization of Artificial Neural Network","authors":"P. Belány, P. Hrabovský, Katarina Bednarcikova, Z. Kolková, N. Kantová","doi":"10.1109/ELEKTRO53996.2022.9803643","DOIUrl":"https://doi.org/10.1109/ELEKTRO53996.2022.9803643","url":null,"abstract":"Nowadays, there is a lot of pressure to adopt environmentally friendly energy sources like natural renewable energy. However, its instability and dependency on a variety of factors make their application a challenge. With the deployment of new technological systems, this unpredictability can be eliminated and their utilization maximized. This article discusses the possibility of using an artificially network to predict heat generation in a photovoltaic power plant. A Matlab script that creates a simple neural network serves as the foundation for the prediction model. The function fitting neural network is created using a backpropagation technique based on the Levenberg-Marquardt optimization. Because of the rapid response of the technique, it is suitable for basic predictions using fast computation speed. A simple artificial neural network based on the aforementioned approach is built in a publication. Created network is trained, tested, and validated on input and measured data. The constructed network is utilized as a prediction of heat generation after the results have been validated. The predictions' outcomes assist us to optimize consumption. This feature allows decreasing energy consumption from an external source. The utilization of a local source and optimization based on neural networks increase building energy efficiency The second important benefit is a decrease in the environmental impact and total carbon footprint of buildings.","PeriodicalId":396752,"journal":{"name":"2022 ELEKTRO (ELEKTRO)","volume":"27 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126053161","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

Numerical approach to design of low frequency magnetic field irradiation system for lab on chip experiments 芯片实验用低频磁场辐照系统的数值设计

2022 ELEKTRO (ELEKTRO) Pub Date : 2022-05-23 DOI: 10.1109/ELEKTRO53996.2022.9803452

R. Radil, Marek Bajtoš, Lucia Čarnecká, Klaudia Hargašová, P. Kamencay

引用次数: 0

The EM Field Investigation of Specific Microwave Sources in Specific Areas 特定区域特定微波源的电磁场研究

2022 ELEKTRO (ELEKTRO) Pub Date : 2022-05-23 DOI: 10.1109/ELEKTRO53996.2022.9803735

M. Beňová, Frederika Bačová, Andrea Cikaiova

引用次数: 2

Use of FEM modeling to optimize the design of induction motor 采用有限元建模方法对感应电机进行优化设计

2022 ELEKTRO (ELEKTRO) Pub Date : 2022-05-23 DOI: 10.1109/ELEKTRO53996.2022.9803602

P. Pečínka, S. Kocman, V. Pečínková

引用次数: 0

Use of diagnostic system for analysis of mechanical condition of transformers winding 利用诊断系统对变压器绕组的机械状况进行分析

2022 ELEKTRO (ELEKTRO) Pub Date : 2022-05-23 DOI: 10.1109/elektro53996.2022.9803469

M. Gutten, D. Korenčiak, Viktor Cefer, Martin Karman

引用次数: 1

Recognition of Human Activity and Abnormal Behavior using Deep Neural Network 基于深度神经网络的人类活动和异常行为识别

2022 ELEKTRO (ELEKTRO) Pub Date : 2022-05-23 DOI: 10.1109/ELEKTRO53996.2022.9803355

R. Vrskova, R. Hudec, P. Kamencay, P. Sykora

{"title":"Recognition of Human Activity and Abnormal Behavior using Deep Neural Network","authors":"R. Vrskova, R. Hudec, P. Kamencay, P. Sykora","doi":"10.1109/ELEKTRO53996.2022.9803355","DOIUrl":"https://doi.org/10.1109/ELEKTRO53996.2022.9803355","url":null,"abstract":"Recognizing various abnormal activities of human behavior from video is very challenging. The overall results are affected by the available data-sets. The available data-sets contain various abnormal activities, but few of them focus mainly on non-standard human behavior. In data-sets such as KTH, they focus on abnormal activities such as a sudden change in behavior or an object occurrence where it should not occur but also various changes in human interaction. The UCF-crime data-set focuses on data that are more interesting to us, such as fight, abuse, explosions or robbery etc. However, the data-set is very demanding due to the videos length, which contains a given event in just a few seconds. This may affect the overall results of the algorithm used to detect the incident. In this paper, we create a data-set dealing with abnormal activities such as robbery, fight, hijack, harassment and a normal videos. We use the created data-set when training and testing the neural network ConvLSTM (Convolutional Long Short-Term Memory). We have obtained a classification accuracy of 97.64 % on the created data-set and used architecture of neural network.","PeriodicalId":396752,"journal":{"name":"2022 ELEKTRO (ELEKTRO)","volume":"112 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132211242","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

Long-term Analysis and Comparison Electricity Consumption of Retrofitted Lighting Systems 改造照明系统的长期用电分析与比较

2022 ELEKTRO (ELEKTRO) Pub Date : 2022-05-23 DOI: 10.1109/ELEKTRO53996.2022.9803740

P. Belány, Z. Kolková, Katarina Bednarcikova, P. Hrabovský

引用次数: 0

2022 ELEKTRO (ELEKTRO) Pub Date : 2022-05-23 DOI: 10.1109/ELEKTRO53996.2022.9803330

J. Ždánsky, J. Hrbček, K. Rástočný

引用次数: 0

Cost Effective Approach for Limiting Voltage Dip Severity on Radial Industrial Feeders in Uganda 限制乌干达径向工业馈线电压倾斜严重程度的经济有效方法

2022 ELEKTRO (ELEKTRO) Pub Date : 2022-05-23 DOI: 10.1109/ELEKTRO53996.2022.9803683

Daniel Kisira, M. Edimu, J. Serugunda

{"title":"Cost Effective Approach for Limiting Voltage Dip Severity on Radial Industrial Feeders in Uganda","authors":"Daniel Kisira, M. Edimu, J. Serugunda","doi":"10.1109/ELEKTRO53996.2022.9803683","DOIUrl":"https://doi.org/10.1109/ELEKTRO53996.2022.9803683","url":null,"abstract":"The rise in industries utilizing automated control equipment for production efficiency is exposing utilities whose distribution systems are vulnerable to power quality disturbances such as voltage dips. Voltage dips are temporary reductions in supply voltage that cause sensitive industrial process devices to malfunction leading to outages and economic loss in factories. This exploratory research was based on the hypothesis that; if an optimal capacitor bank design is developed to ensure that the pre-disturbance voltage profile on a radial feeder is improved to stay within acceptable limits at all times, then the voltage dip severity can be cost effectively mitigated during the large disturbance events without the need to deploy the expensive fast-switching devices such as the Static VAR compensators. Hence, on the Uganda distribution network, the Wabigalo 33 kV industrial feeder being long and radial was used as case study to establish a cost effective approach for limiting voltage dip severity using an optimal capacitor bank design. The Tabu search algorithm in combination with the Loss Sensitivity Factor applied in the DIgSILENT software was used to ascertain the optimal capacitor bank design with its performance and cost compared with the Static VAR Compensator as the standard method. The study found that the initial investment cost of the optimal capacitor bank design for the Wabigalo feeder is 23.5% of the cost of the Static VAR Compensator and provides superior performance benefits in terms of improvement of the pre-disturbance voltage profile and limiting voltage dip severity determined by residual voltage magnitude and voltage dip propagation.","PeriodicalId":396752,"journal":{"name":"2022 ELEKTRO (ELEKTRO)","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133787086","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