2017 IEEE Latin American Conference on Computational Intelligence (LA-CCI)最新文献

Characterization of climatological time series using autoencoders 用自编码器表征气候时间序列

2017 IEEE Latin American Conference on Computational Intelligence (LA-CCI) Pub Date : 2017-11-08 DOI: 10.1109/LA-CCI.2017.8285717

Reynaldo Alfonte Zapana, C. L. D. Alamo, Jan Franco Llerena Quenaya, Ana Maria Cuadros Valdivia

引用次数: 1

Crowd abnormal detection using artificial bacteria colony and Kohonen's neural network 基于人工菌落和Kohonen神经网络的人群异常检测

2017 IEEE Latin American Conference on Computational Intelligence (LA-CCI) Pub Date : 2017-11-01 DOI: 10.1109/LA-CCI.2017.8285685

Joelmir Ramos da Costa, N. Nedjah, L. M. Mourelle, Daniel Ramos da Costa

引用次数: 1

Software time estimation using regression methods 软件时间估计的回归方法

2017 IEEE Latin American Conference on Computational Intelligence (LA-CCI) Pub Date : 2017-11-01 DOI: 10.1109/LA-CCI.2017.8285723

Yanne M. G. Soares, Roberta Fagundes

引用次数: 1

Multivariate data mapping based on dendritic lattice associative memories 基于树突格联想记忆的多元数据映射

2017 IEEE Latin American Conference on Computational Intelligence (LA-CCI) Pub Date : 2017-11-01 DOI: 10.1109/LA-CCI.2017.8285687

G. Urcid, Rocio Morales-Salgado, G. Ritter

引用次数: 1

Self-organizing maps for anomaly detection in fuel consumption. Case study: Illegal fuel storage in Bolivia 燃油消耗异常检测的自组织映射。案例研究:玻利维亚的非法燃料储存

2017 IEEE Latin American Conference on Computational Intelligence (LA-CCI) Pub Date : 2017-11-01 DOI: 10.1109/LA-CCI.2017.8285697

Vanessa Gironda Aquize, Eduardo Emery, Fernando Buarque de Lima-Neto

引用次数: 6

Sentiment analysis using convolutional neural network with fastText embeddings 基于快速文本嵌入的卷积神经网络情感分析

2017 IEEE Latin American Conference on Computational Intelligence (LA-CCI) Pub Date : 2017-11-01 DOI: 10.1109/LA-CCI.2017.8285683

Igor Santos, N. Nedjah, L. M. Mourelle

引用次数: 46

Development of a smartphone controlled quadrotor: A testbed for autonomous applications 智能手机控制四旋翼飞行器的开发:自主应用的测试平台

2017 IEEE Latin American Conference on Computational Intelligence (LA-CCI) Pub Date : 2017-11-01 DOI: 10.1109/LA-CCI.2017.8285688

Gildo F. Dantas, S. C. Oliveira

引用次数: 1

Supervised learning algorithms for indoor localization fingerprinting using BLE4.0 beacons 使用BLE4.0信标的室内定位指纹的监督学习算法

2017 IEEE Latin American Conference on Computational Intelligence (LA-CCI) Pub Date : 2017-11-01 DOI: 10.1109/LA-CCI.2017.8285716

Jesús Lovón-Melgarejo, Manuel Castillo-Cara, L. Orozco-Barbosa, I. García-Varea

{"title":"Supervised learning algorithms for indoor localization fingerprinting using BLE4.0 beacons","authors":"Jesús Lovón-Melgarejo, Manuel Castillo-Cara, L. Orozco-Barbosa, I. García-Varea","doi":"10.1109/LA-CCI.2017.8285716","DOIUrl":"https://doi.org/10.1109/LA-CCI.2017.8285716","url":null,"abstract":"The increasing interest on deploying ubiquitous context-based services has spurred the need of developing indoor localization mechanisms. Such systems should take advantage of the large amount of wireless networks and radio interfaces already incorporated in most mobile consumer devices. Among the existing radio interfaces, Bluetooth Low Energy (BLE) 4.0 is called to play a major role in the deployment of energy efficient ubiquitous services. In this paper, we first show that the high sensitivity of BLE4.0 to fast fading makes infeasible the use of radio propagation models to directly estimate the distance between a reference transmitter and the mobile device. We then explore the use of supervised learning algorithms towards the development of radio maps of beacons analysing in-depth two metrics accuracy and mean error. Our approach also explores two main parameters: (i) Transmission power (Tx) of the BLE4.0 beacons; and (ii) Physical characteristics of the area. Based on our results, we argue that the mean error can be improved up to 28% configuring the two main parameters.","PeriodicalId":144567,"journal":{"name":"2017 IEEE Latin American Conference on Computational Intelligence (LA-CCI)","volume":"226 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124492617","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: 5

A methodology for enhancing data quality for classification purposes using attribute-based decision graphs 一种使用基于属性的决策图提高数据质量以进行分类的方法

2017 IEEE Latin American Conference on Computational Intelligence (LA-CCI) Pub Date : 2017-11-01 DOI: 10.1109/LA-CCI.2017.8285692

J. R. Bertini

引用次数: 1

Modified bat algorithm with cauchy mutation and elite opposition-based learning 基于柯西突变和精英对立学习的改进蝙蝠算法

2017 IEEE Latin American Conference on Computational Intelligence (LA-CCI) Pub Date : 2017-11-01 DOI: 10.1109/LA-CCI.2017.8285715

Fábio A. P. Paiva, Cláudio R. M. Silva, Izabele V. O. Leite, M. Marcone, J. A. F. Costa

{"title":"Modified bat algorithm with cauchy mutation and elite opposition-based learning","authors":"Fábio A. P. Paiva, Cláudio R. M. Silva, Izabele V. O. Leite, M. Marcone, J. A. F. Costa","doi":"10.1109/LA-CCI.2017.8285715","DOIUrl":"https://doi.org/10.1109/LA-CCI.2017.8285715","url":null,"abstract":"Metaheuristics can be used to solve optimization complex problems because they offer approximate and acceptable solutions. In recent years, nature has been a source of inspiration for many computer scientists when proposing new metaheuristics such as the algorithms inspired by swarm intelligence. They are based on the behavior of animals that live in groups such as birds, fishes and bats. In this context, Bat Algorithm (BA) is a recent metaheuristic inspired by echolocation of bats during their flights. However, a problem that this algorithm faces is the loss of the ability to generate diversity and, consequently, the chances of finding the global solution are reduced. This paper proposes a modification to the original BA using two methods known as Cauchy mutation operator and Elite Opposition-Based Learning. The new variant aims generate diversity of the algorithm and increases its convergence velocity. It was compared to the original BA and another variant found in the literature. For this comparison, the proposed variant used four benchmark functions, during 30 independent runs. After the experiments, the superiority of the new variant is highlighted when the results are compared to the original BA.","PeriodicalId":144567,"journal":{"name":"2017 IEEE Latin American Conference on Computational Intelligence (LA-CCI)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124749448","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: 22