2020 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC)最新文献_第10页

Study of the User's Eye Tracking to Analyze the Blinking Behavior While Playing a Video Game to Identify Cognitive Load Levels 使用眼动追踪分析用户在玩电子游戏时的眨眼行为以识别认知负荷水平的研究

2020 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC) Pub Date : 2020-11-04 DOI: 10.1109/ROPEC50909.2020.9258693

Lagunes-Ramírez Derick, G. Gabriel, López-Sánchez Máximo, Fragoso-Díaz Olivia, Castro-Sánchez Noé, Juan C. Olivares-Rojas

引用次数: 3

Measurements to Transformers with a Vector Network Analyzer 用矢量网络分析仪测量变压器

2020 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC) Pub Date : 2020-11-04 DOI: 10.1109/ROPEC50909.2020.9258739

I. D. Santana, F. Uribe

引用次数: 0

Comparative Analysis of Multivariable Deep Learning Models for Forecasting in Smart Grids 智能电网多变量深度学习预测模型的比较分析

2020 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC) Pub Date : 2020-11-04 DOI: 10.1109/ROPEC50909.2020.9258732

E. Avalos, M. R. Licea, H. R. González, A. Calderón, A. Gutiérrez, F. J. P. Pinal

{"title":"Comparative Analysis of Multivariable Deep Learning Models for Forecasting in Smart Grids","authors":"E. Avalos, M. R. Licea, H. R. González, A. Calderón, A. Gutiérrez, F. J. P. Pinal","doi":"10.1109/ROPEC50909.2020.9258732","DOIUrl":"https://doi.org/10.1109/ROPEC50909.2020.9258732","url":null,"abstract":"Clean-energy generation in smart grids is limited by the availability of the energy to be transformed and advanced energy management strategies requires solid and anticipated information about its dynamic behavior. This includes multivariable prediction of meteorological and user consumption data simultaneously in time series. The selection of a predicting model, from long short-term memory (LSTM), convolutional neural networks (CNN), gated recurrent units (GRU), or their hybrid models merging CNN with LSTM and GRU, is a very complex task. In this paper, a mean absolute error, absolute percentage error (MAPE), and root mean square error (RMSE) comparative analysis, for prediction of energy consumption, and solar and onshore wind generation, is presented. A three-day prediction-horizon is used, with four-year hourly training data from Madrid. The combination of the best GRU and CNN models found, subject to the given hyperparameters grid, has a better prediction performance, including if they predict separated. Relevant information about training and coding appreciations is also presented.","PeriodicalId":177447,"journal":{"name":"2020 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC)","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114254629","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: 4

Identification of Agricultural Parcels using Optical and Synthetic Aperture Radar Data 利用光学和合成孔径雷达数据识别农业地块

2020 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC) Pub Date : 2020-11-04 DOI: 10.1109/ROPEC50909.2020.9258694

Jubal López-Amaya, A. López-Caloca, A. Monsiváis-Huertero

{"title":"Identification of Agricultural Parcels using Optical and Synthetic Aperture Radar Data","authors":"Jubal López-Amaya, A. López-Caloca, A. Monsiváis-Huertero","doi":"10.1109/ROPEC50909.2020.9258694","DOIUrl":"https://doi.org/10.1109/ROPEC50909.2020.9258694","url":null,"abstract":"Data fusion methodologies have been implemented in agricultural applications with different types of sensors. One of the problems in delineating cultivation areas is the mixture of spectral signatures due to the transitions between the types of cultivation, built areas, and other natural covers. In order to improve discrimination and identification of crop types, structure data fusion techniques were evaluated. This article aims at showing the potential of using satellite data from the European Space Agency, both optical and SAR, in order to improve land cover classification of agricultural land located in Mexico. To achieve this, an analysis of the spectral, spatial and textural data was performed. Specifically, two classification algorithms were used and compared. The first is based on vector support machines and the second one on Random Forests. The methodology was applied for the study of 4 types of crops in 2017 in the municipality of Villa de Arriaga located in the state of San Luis Potosí. As final results, maps were obtained with the areas with a kappa greater than 0.80.","PeriodicalId":177447,"journal":{"name":"2020 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124996762","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

Roundness Estimation of Sedimentary Rocks Using Eliptic Fourier and Deep Neural Networks 基于椭圆傅里叶和深度神经网络的沉积岩圆度估计

2020 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC) Pub Date : 2020-11-04 DOI: 10.1109/ROPEC50909.2020.9258735

E. M. Hernández, G. M. Chávez, J. Hernández

引用次数: 0

DC-DC Buck Converter with an LC Filter for Battery Parameter Identification 带LC滤波器的DC-DC降压变换器，用于电池参数识别

2020 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC) Pub Date : 2020-11-04 DOI: 10.1109/ROPEC50909.2020.9258696

J. M. Sosa, Iván López-Granados, G. Vázquez, P. Martinez‐Rodriguez, G. Escobar, M. Juárez, D. Langarica

引用次数: 0

Comparative Evaluation of Reduced CMV-SVM Techniques for a Three-Phase ANPC Inverter 一种三相ANPC逆变器的简化CMV-SVM技术的比较评价

2020 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC) Pub Date : 2020-11-04 DOI: 10.1109/ROPEC50909.2020.9258700

H. O. Valdez-Carrera, G. Vazquez‐Guzman, J. M. Sosa, P. Martinez‐Rodriguez, G. Escobar, M. Juárez-Balderas

引用次数: 0

Off-grid Wind Energy Conversion Systems based on Multilevel Cascaded H-bridge Topology in Real Time Simulation 基于多级级联h桥拓扑的离网风能转换系统实时仿真

2020 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC) Pub Date : 2020-11-04 DOI: 10.1109/ROPEC50909.2020.9258773

V. R. Rosales, S. Rodriguez, M. Robles, O. Rodríguez-Hernández, N. M. Salgado‐Herrera

引用次数: 0

Power System Voltage Profile Evaluation Considering Renewable Energy Power Plant Reactive Power Droop Control 考虑可再生能源电厂无功下垂控制的电力系统电压分布评估

2020 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC) Pub Date : 2020-11-04 DOI: 10.1109/ROPEC50909.2020.9258752

R. Reyes, Pedro Rosales, L. M. Castro

引用次数: 1

Analysis of Meat Color Change using Computer Vision 用计算机视觉分析肉的颜色变化

2020 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC) Pub Date : 2020-11-04 DOI: 10.1109/ROPEC50909.2020.9258756

Gustavo Meza, Claudia N. Sánchez, M. T. Orvañanos-Guerrero, J. Domínguez-Soberanes

{"title":"Analysis of Meat Color Change using Computer Vision","authors":"Gustavo Meza, Claudia N. Sánchez, M. T. Orvañanos-Guerrero, J. Domínguez-Soberanes","doi":"10.1109/ROPEC50909.2020.9258756","DOIUrl":"https://doi.org/10.1109/ROPEC50909.2020.9258756","url":null,"abstract":"Sensory parameters are crucial for making a purchase decision in meat products. Thus, consumers will guide their choice based on their color. They will seek cherry red meat; when the meat turns brown due to the myoglobin's oxidation, the product is no longer desired. Therefore, the food industry must have a system that could be effective and give just-in-time information regarding changes in color to maintain the quality during the shelf life that consumers expect. This research aims to present a methodology based on computer vision to analyze the change of color in meat. We used images taken of different beef cuts and tested on different days. The Euclidean distance on the average of colors could be used. However, the method proposed in this study is the use of Kullback Leibler divergence, which takes the meat not only at one color point but as a cloud of points. The results were obtained with the Kullback Leibler divergence demonstrated that it is possible to calculate differences in meat images when passing the days. The practical application for this type of analysis would be in the retail industry in order to give just in time information about the quality of meat.","PeriodicalId":177447,"journal":{"name":"2020 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132350686","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