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

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SPEA — MA: A social evolutionary algorithm for managing multiple transmissions SPEA - MA:一种管理多重传输的社会进化算法
2017 IEEE Latin American Conference on Computational Intelligence (LA-CCI) Pub Date : 2017-11-01 DOI: 10.1109/LA-CCI.2017.8285703
P. F. Barbosa, Luis Menezes
{"title":"SPEA — MA: A social evolutionary algorithm for managing multiple transmissions","authors":"P. F. Barbosa, Luis Menezes","doi":"10.1109/LA-CCI.2017.8285703","DOIUrl":"https://doi.org/10.1109/LA-CCI.2017.8285703","url":null,"abstract":"Multicast communication transmits packages from a single source to many destinations in a single transmission. Several algorithms have been proposed to obtain the best multicast routes using approaches such as exhaustive search, meta-heuristics or simulation. Besides achieving good results, theses techniques are focused on one aspect of the routing problem and may produce suboptimal results when other aspects become relevant. This paper proposes a hybrid algorithm that combines different routing techniques to produce optimum routes. This algorithm uses search techniques to find candidate solutions and simulation to analyze their performance in multiple transmission circumstances.","PeriodicalId":144567,"journal":{"name":"2017 IEEE Latin American Conference on Computational Intelligence (LA-CCI)","volume":"47 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":"122547107","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
Application of PSO-based clustering algorithms on educational databases 基于粒子群算法的聚类算法在教育数据库中的应用
2017 IEEE Latin American Conference on Computational Intelligence (LA-CCI) Pub Date : 2017-11-01 DOI: 10.1109/LA-CCI.2017.8285690
Pedro Santos, M. Macedo, Elliackin M. N. Figueiredo, Clodomir J. Santana, Fabiana Soares, H. Siqueira, A. M. A. Maciel, A. Gokhale, C. J. A. B. Filho
{"title":"Application of PSO-based clustering algorithms on educational databases","authors":"Pedro Santos, M. Macedo, Elliackin M. N. Figueiredo, Clodomir J. Santana, Fabiana Soares, H. Siqueira, A. M. A. Maciel, A. Gokhale, C. J. A. B. Filho","doi":"10.1109/LA-CCI.2017.8285690","DOIUrl":"https://doi.org/10.1109/LA-CCI.2017.8285690","url":null,"abstract":"This paper performs an investigation on the application of well-known Particle Swarm Optimization based algorithms for clustering tasks, namely, PSOClustering, Hybrid PSOClustering with K-means and Particle Swarm Clustering. The case study is to tackle a significant problem related to grouping students of an on-line educational database, aiming to increase their learning process through the recommendation of specific grammar lessons. The clustering process is performed based on the type, and the number of errors done by the students. The results show that the PSOClustering algorithm can achieve the best performance when compared to the other PSO-based algorithms and the standard K-means algorithm.","PeriodicalId":144567,"journal":{"name":"2017 IEEE Latin American Conference on Computational Intelligence (LA-CCI)","volume":"22 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":"123637445","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: 21
Knowledge extraction from time series of electric energy demand using temporal data mining 基于时态数据挖掘的电力需求时间序列知识提取
2017 IEEE Latin American Conference on Computational Intelligence (LA-CCI) Pub Date : 2017-11-01 DOI: 10.1109/LA-CCI.2017.8285720
A. C. S. D. Queiroz, J. A. F. Costa
{"title":"Knowledge extraction from time series of electric energy demand using temporal data mining","authors":"A. C. S. D. Queiroz, J. A. F. Costa","doi":"10.1109/LA-CCI.2017.8285720","DOIUrl":"https://doi.org/10.1109/LA-CCI.2017.8285720","url":null,"abstract":"Planning activities are very important in the energy sector, where the utilities are seeking information that may assist in decisions regarding expansion needs and resource management, improving the quality of their services. This paper presents a methodology based on mining tools and representation of time series, in order to extract knowledge from series of electricity demand in various substations connected to an energy provider. To represent this knowledge, the language proposed by Mörchen (2005) called Time Series Knowledge Representation (TSKR) is used. It was conducted a case study using time series of energy demand for 8 substations interconnected by a ring system, which feeds the metropolitan area of Goiania-GO (Brazil), provided by CELG (Companhia Energética de Goiás), responsible for the service of power distribution in the state of Goiás (Brazil). Using the proposed methodology, three levels of knowledge that describe the behavior of the studied system were extracted, representing clearly the system dynamics, thus becoming a tool to assist planning activities.","PeriodicalId":144567,"journal":{"name":"2017 IEEE Latin American Conference on Computational Intelligence (LA-CCI)","volume":"5 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":"125319234","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
Better exploration-exploitation pace, better swarm: Examining the social interactions 更好的探索开发速度，更好的群体:考察社会互动
2017 IEEE Latin American Conference on Computational Intelligence (LA-CCI) Pub Date : 2017-11-01 DOI: 10.1109/LA-CCI.2017.8285712
Marcos A. C. Oliveira, Diego Pinheiro, M. Macedo, C. J. A. B. Filho, R. Menezes
{"title":"Better exploration-exploitation pace, better swarm: Examining the social interactions","authors":"Marcos A. C. Oliveira, Diego Pinheiro, M. Macedo, C. J. A. B. Filho, R. Menezes","doi":"10.1109/LA-CCI.2017.8285712","DOIUrl":"https://doi.org/10.1109/LA-CCI.2017.8285712","url":null,"abstract":"Swarm-based models have successfully solved real-world problems in the past two decades and yet they continue to exhibit a major shortcoming of premature convergence. Previous research suggests that an appropriate exploitation-exploration balance can prevent premature convergence and different approaches have been proposed to control this balance. Still, despite several references demonstrating the interplay between social interactions and swarm behavior, the majority of works lack a network-based assessment of the level of balance in a swarm. We propose that pacing social interactions is the key to balance exploration-exploitation. Here we examine the impact of the exploration-exploitation balance on the swarm performance by controlling the pace at which the swarm goes from exploration to exploitation. Our results revealed that this pace influences the swarm dynamics and that different problems demand distinct paces. Swarm-based models that are capable of adapting their exploration-exploitation pace have the potential to overcome premature convergence.","PeriodicalId":144567,"journal":{"name":"2017 IEEE Latin American Conference on Computational Intelligence (LA-CCI)","volume":"117 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":"127574194","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: 14
Clustering techniques applied to detection of inefficiency in electrical submersible pumps startup 聚类技术在电潜泵启动低效检测中的应用
2017 IEEE Latin American Conference on Computational Intelligence (LA-CCI) Pub Date : 2017-11-01 DOI: 10.1109/LA-CCI.2017.8285725
L. J. Lopes, G. Almeida
{"title":"Clustering techniques applied to detection of inefficiency in electrical submersible pumps startup","authors":"L. J. Lopes, G. Almeida","doi":"10.1109/LA-CCI.2017.8285725","DOIUrl":"https://doi.org/10.1109/LA-CCI.2017.8285725","url":null,"abstract":"Electrical submersible pumps have been increasingly used in the oil industry. The startup cycle of this equipment causes it to be subjected to extreme conditions that can reduce its useful life. In addition, the oil flow produced during this process is lower than the normal operating condition. Currently, the control of this process is manual and subject to operator experience and sensitivity. In this way, mechanisms that allow to evaluate and increase the efficiency of this process are necessary. The methodology proposed in this work applies clustering technique to identify the possibility of reducing process time and was feasible.","PeriodicalId":144567,"journal":{"name":"2017 IEEE Latin American Conference on Computational Intelligence (LA-CCI)","volume":"13 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":"127783888","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
An investigation on the use of convolutional neural network for image classification in embedded systems 卷积神经网络在嵌入式系统图像分类中的应用研究
2017 IEEE Latin American Conference on Computational Intelligence (LA-CCI) Pub Date : 2017-11-01 DOI: 10.1109/LA-CCI.2017.8285727
Cecília Silva, C. Siebra
{"title":"An investigation on the use of convolutional neural network for image classification in embedded systems","authors":"Cecília Silva, C. Siebra","doi":"10.1109/LA-CCI.2017.8285727","DOIUrl":"https://doi.org/10.1109/LA-CCI.2017.8285727","url":null,"abstract":"The study of Convolutional Neural Network (CNN) for image classification is basically carried out on high performance and parallel platforms, so that the results of the literature cannot be replied on embedded systems. The aim of our work is to investigate CNN architectures that can run in such limited platforms and still maintain or improve the results of the current approaches. To that end, we specify and evaluate the performance of several CNN frameworks using different network configurations and dataset pre-processing techniques. The results of our final approach show that its classification efficiency is close to the best results of the literature, however using a much lower computational power.","PeriodicalId":144567,"journal":{"name":"2017 IEEE Latin American Conference on Computational Intelligence (LA-CCI)","volume":"74 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":"127377444","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: 7
Surrogate models assisted by neural networks to assess the resilience of networks 神经网络辅助的代理模型评估网络的弹性
2017 IEEE Latin American Conference on Computational Intelligence (LA-CCI) Pub Date : 2017-11-01 DOI: 10.1109/LA-CCI.2017.8285704
Danilo R. B. Araújo, Gustavo H. P. S. de Barros, C. J. A. B. Filho, J. Martins-Filho
{"title":"Surrogate models assisted by neural networks to assess the resilience of networks","authors":"Danilo R. B. Araújo, Gustavo H. P. S. de Barros, C. J. A. B. Filho, J. Martins-Filho","doi":"10.1109/LA-CCI.2017.8285704","DOIUrl":"https://doi.org/10.1109/LA-CCI.2017.8285704","url":null,"abstract":"The assessment of networks is frequently accomplished by using time-consuming analysis tools based on simulations. For example, the blocking probability of networks can be estimated by Monte Carlo simulations and the network resilience can be assessed by link or node failure simulations. We propose in this paper to use Artificial Neural Networks (ANN) to predict the robustness of networks based on simple topological metrics to avoid time-consuming failure simulations. We accomplish the training process using supervised learning based on a historical database of networks. We compare the results of our proposal with the outcome provided by targeted and random failures simulations. We show that our approach is faster than failure simulators and the ANN can mimic the same robustness evaluation provide by these simulators. We obtained an average speedup of 300 times.","PeriodicalId":144567,"journal":{"name":"2017 IEEE Latin American Conference on Computational Intelligence (LA-CCI)","volume":"6 1 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":"123528377","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
IVF/NSGAII: In vitro fertilization method coupled to NSGAII IVF/NSGAII:结合NSGAII的体外受精方法
2017 IEEE Latin American Conference on Computational Intelligence (LA-CCI) Pub Date : 2017-11-01 DOI: 10.1109/LA-CCI.2017.8285710
Sávio Menezes Sampaio, C. Camilo-Junior
{"title":"IVF/NSGAII: In vitro fertilization method coupled to NSGAII","authors":"Sávio Menezes Sampaio, C. Camilo-Junior","doi":"10.1109/LA-CCI.2017.8285710","DOIUrl":"https://doi.org/10.1109/LA-CCI.2017.8285710","url":null,"abstract":"The In Vitro Fertilization Genetic Algorithm — IVF/GA is a promising algorithm applicable to mono-objective problems, especially for complex and multimodal ones. Due to the balance between the exploration and exploitation of the IVF/GA, and thus its abilities to avoid the local optimum, we speculate that the IVF can also improve the Multi-Objective Evolutionary Algorithms (MOEA). So, this paper proposes the IVF/NSGAII, which is the IVF coupled to NSGAII. We evaluate the proposal's improvement comparing the canonical NSGAII versus IVF/NSGAII, applied to Zitzler-Deb-Thiele (ZDT) functions. The results show the IVF/NSGAII outperformed the canonical version on Inverted Generational Distance (IGD) metric, mainly in the complex functions, e.g. ZDT 4, 5 and 6. Therefore, we conclude that IVF improved the NSGAII and also is a promising approach to support MOEA's.","PeriodicalId":144567,"journal":{"name":"2017 IEEE Latin American Conference on Computational Intelligence (LA-CCI)","volume":"76 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":"124680906","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: 3
PSO for parametric identification of rotatory induction motors using experimental data with unknown time-delays 基于未知时滞实验数据的旋转感应电机参数辨识的粒子群算法
2017 IEEE Latin American Conference on Computational Intelligence (LA-CCI) Pub Date : 2017-11-01 DOI: 10.1109/LA-CCI.2017.8285718
A. Alanis, N. Arana-Daniel, C. López-Franco, M. A. P. Cisneros, E. Sánchez
{"title":"PSO for parametric identification of rotatory induction motors using experimental data with unknown time-delays","authors":"A. Alanis, N. Arana-Daniel, C. López-Franco, M. A. P. Cisneros, E. Sánchez","doi":"10.1109/LA-CCI.2017.8285718","DOIUrl":"https://doi.org/10.1109/LA-CCI.2017.8285718","url":null,"abstract":"This paper deals with parametric identification for discrete-time α-ß model for three phase linear induction motors (LIM). This parametric identification is performed using the well-known PSO algorithm, using experimental data obtained from a real-time implementation on a LIM benchmark. Obtained parameters are validated using signal fitting for state variables, under presence of unknown disturbances and time-delays.","PeriodicalId":144567,"journal":{"name":"2017 IEEE Latin American Conference on Computational Intelligence (LA-CCI)","volume":"4 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":"127006998","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
Images segmentation by using differential evolution with constraints handling 基于约束处理的差分进化图像分割
2017 IEEE Latin American Conference on Computational Intelligence (LA-CCI) Pub Date : 2017-11-01 DOI: 10.1109/LA-CCI.2017.8285713
R. Ochoa-Montiel, M. A. Carrasco-Aguilar, C. Sánchez-López, Francisco Javier Albores-Velasco, F. E. Morales-Lopez, L. Flores-Pulido
{"title":"Images segmentation by using differential evolution with constraints handling","authors":"R. Ochoa-Montiel, M. A. Carrasco-Aguilar, C. Sánchez-López, Francisco Javier Albores-Velasco, F. E. Morales-Lopez, L. Flores-Pulido","doi":"10.1109/LA-CCI.2017.8285713","DOIUrl":"https://doi.org/10.1109/LA-CCI.2017.8285713","url":null,"abstract":"This paper address the multilevel image segmentation by merging Gaussian mixtures models (GMM) and Differential Evolution (DE) with constraints handling. Since the estimation of parameters associated to GMM is a complex task, DE is used to estimate them. Afterwards, these parameters are used for obtaining the optimal thresholds and achieve a multilevel image segmentation. The tests include the use of 83 images of a parasite named Trypanosoma. The experiments were done by using original and equalized images. The results show a better performance with the latter. We conclude that the method is likely useful for applications where the data are similar the data used in this work.","PeriodicalId":144567,"journal":{"name":"2017 IEEE Latin American Conference on Computational Intelligence (LA-CCI)","volume":"45 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":"125466287","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: 3
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