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2017 Brazilian Conference on Intelligent Systems (BRACIS)最新文献

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Using Multiple Clustering Algorithms to Generate Constraint Rules and Create Consensus Clusters 基于多聚类算法的约束规则生成与一致聚类
2017 Brazilian Conference on Intelligent Systems (BRACIS) Pub Date : 2017-10-01 DOI: 10.1109/BRACIS.2017.78
Gabriel da Silva, M. Albertini
{"title":"Using Multiple Clustering Algorithms to Generate Constraint Rules and Create Consensus Clusters","authors":"Gabriel da Silva, M. Albertini","doi":"10.1109/BRACIS.2017.78","DOIUrl":"https://doi.org/10.1109/BRACIS.2017.78","url":null,"abstract":"Data clustering techniques is used for aiding knowledge discovery when no additional information is available. There are several clustering techniques which produce reasonable results, although they often produce qualitatively distinct clusterings. In this paper, we study how different clustering algorithms produce different kinds of clusters and their relations. Also, we evaluate the possibility to merge differently generated clustering into a new clustering which neither of original algorithms can produce. The main contribution of this paper is a new algorithm which merges previous generated clusterings based on must-link constraint rules built from agreements among elements observed from such clusterings. This novel approach employs the entropy of agreements in order to decide to which cluster should an element belong. Experimental results indicate: 1) our approach can merge characteristics from original clusterings; 2) in some situations, it captures new information from data and improve results, mainly when considering external perspective; and 3) in no situation it has produced significantly worse results.","PeriodicalId":202240,"journal":{"name":"2017 Brazilian Conference on Intelligent Systems (BRACIS)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114813225","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
Neural Networks Architecture Evaluation in a Quantum Computer 量子计算机中的神经网络体系结构评估
2017 Brazilian Conference on Intelligent Systems (BRACIS) Pub Date : 2017-10-01 DOI: 10.1109/BRACIS.2017.33
A. J. D. Silva, Rodolfo Luan Franco de Oliveira
{"title":"Neural Networks Architecture Evaluation in a Quantum Computer","authors":"A. J. D. Silva, Rodolfo Luan Franco de Oliveira","doi":"10.1109/BRACIS.2017.33","DOIUrl":"https://doi.org/10.1109/BRACIS.2017.33","url":null,"abstract":"In this work, we propose a quantum algorithm to evaluate neural networks architectures named Quantum Neural Network Architecture Evaluation (QNNAE). The proposed algorithm is based on a quantum associative memory and the learning algorithm for artificial neural networks. Unlike conventional algorithms for evaluating neural network architectures, QNNAE does not depend on initialization of weights. The proposed algorithm has a binary output and results in 0 with probability proportional to the performance of the network. And its computational cost is equal to the computational cost to train a neural network.","PeriodicalId":202240,"journal":{"name":"2017 Brazilian Conference on Intelligent Systems (BRACIS)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132873654","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
Probabilistic Analysis of Pareto Front Approximation for a Hybrid Multi-objective Bayesian Estimation of Distribution Algorithm 混合多目标贝叶斯分布估计算法Pareto前逼近的概率分析
2017 Brazilian Conference on Intelligent Systems (BRACIS) Pub Date : 2017-10-01 DOI: 10.1109/BRACIS.2017.32
M. Martins, M. Delgado, R. Lüders, Roberto Santana, Richard A. Gonçalves, C. Almeida
{"title":"Probabilistic Analysis of Pareto Front Approximation for a Hybrid Multi-objective Bayesian Estimation of Distribution Algorithm","authors":"M. Martins, M. Delgado, R. Lüders, Roberto Santana, Richard A. Gonçalves, C. Almeida","doi":"10.1109/BRACIS.2017.32","DOIUrl":"https://doi.org/10.1109/BRACIS.2017.32","url":null,"abstract":"Metaheuristics that explore the decision variables space to construct probabilistic modeling from promising solutions, like estimation of distribution algorithms (EDAs), are becoming very popular in the context of Multi-objective Evolutionary Algorithms (MOEAs). The probabilistic model used in EDAs captures certain statistics of problem variables and their interdependencies. Moreover, the incorporation of local search methods tends to achieve synergy of MOEAs' operators and local heuristics aiming to improve the performance. In this work, we aim to scrutinize the probabilistic graphic model (PGM) presented in Hybrid Multi-objective Bayesian Estimation of Distribution Algorithm (HMOBEDA), which is based on a Bayesian network. Different from traditional EDA-based approaches, the PGM of HMOBEDA provides the joint probability of decision variables, objectives, and configuration parameters of an embedded local search. HMOBEDA has shown to be very competitive on instances of Multi-Objective Knapsack Problem (MOKP), outperforming state-of-the-art approaches. Two variants of HMOBEDA are proposed in this paper using different sample methods. We aim to compare the learnt structure in terms of the probabilistic Pareto Front approximation produced at the end of evolution. Results on instances of MOKP with 2 to 8 objectives show that both proposed variants outperformthe original approach, providing not only the best values for hypervolume and inverted generational distance indicators, butalso a higher diversity in the solution set.","PeriodicalId":202240,"journal":{"name":"2017 Brazilian Conference on Intelligent Systems (BRACIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130452902","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
A Comparison of Hierarchical Biclustering Ensemble Methods 层次双聚类集成方法的比较
2017 Brazilian Conference on Intelligent Systems (BRACIS) Pub Date : 2017-10-01 DOI: 10.1109/BRACIS.2017.38
V. A. Padilha, A. Carvalho
{"title":"A Comparison of Hierarchical Biclustering Ensemble Methods","authors":"V. A. Padilha, A. Carvalho","doi":"10.1109/BRACIS.2017.38","DOIUrl":"https://doi.org/10.1109/BRACIS.2017.38","url":null,"abstract":"Biclustering aims at providing techniques able to detect submatrices following coherent patterns according to a pre-established criterion in a data matrix. These techniques are able to simultaneously cluster both dimensions of a data matrix (objects and features). Several real-world applications can benefit from the use of this paradigm (e.g., gene expression data analysis). However, biclustering is proven to be a NP-hard problem. For such, an alternative to provide more meaningful and robust solutions is the combination of several biclustering results by using ensemble methods. The development of ensemble methods is a relatively new issue in the biclustering literature. Thus, few methods have been proposed and, to the best of the authors' knowledge, no comparative study has been conducted so far. This paper compares two biclustering ensemble methods based on a hierarchical aggregation of previously found biclusters. Experiments are carried out with both on synthetic and real datasets. Despite the results obtained, the authors believe that there is room for further improvement of the methods for real gene expression data scenarios.","PeriodicalId":202240,"journal":{"name":"2017 Brazilian Conference on Intelligent Systems (BRACIS)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125498922","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
Blind Image Quality Assessment Using Local Variant Patterns 基于局部变异模式的盲图像质量评估
2017 Brazilian Conference on Intelligent Systems (BRACIS) Pub Date : 2017-10-01 DOI: 10.1109/BRACIS.2017.16
P. Freitas, W. Y. L. Akamine, Mylène C. Q. Farias
{"title":"Blind Image Quality Assessment Using Local Variant Patterns","authors":"P. Freitas, W. Y. L. Akamine, Mylène C. Q. Farias","doi":"10.1109/BRACIS.2017.16","DOIUrl":"https://doi.org/10.1109/BRACIS.2017.16","url":null,"abstract":"This paper introduces a new blind image quality assessment (BIQA) metric using texture analysis. The method adopts two texture operators to select image texture information. The first operator is the Local Binary Pattern (LBP), an effective texture operator that is extensively adopted for texture analysis. The second operator is proposed as an extension of LBP. The proposed operator, the Local Variant Pattern (LVP), extracts local energy information. Energy information is particularly important for BIQA metrics because image distortions modify the energy of the textures. Histograms of the LBP and LVP outputs are used as features in a random forest regression algorithm. The proposed method surpass other state-of-the-art BIQA method, as results demonstrate.","PeriodicalId":202240,"journal":{"name":"2017 Brazilian Conference on Intelligent Systems (BRACIS)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127669082","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
University Entrance Exam as a Guiding Test for Artificial Intelligence 高考作为人工智能的指导性考试
2017 Brazilian Conference on Intelligent Systems (BRACIS) Pub Date : 2017-10-01 DOI: 10.1109/BRACIS.2017.44
I. Silveira, D. Mauá
{"title":"University Entrance Exam as a Guiding Test for Artificial Intelligence","authors":"I. Silveira, D. Mauá","doi":"10.1109/BRACIS.2017.44","DOIUrl":"https://doi.org/10.1109/BRACIS.2017.44","url":null,"abstract":"In this paper, we propose using an University Entrance Exam (the Exame Nacional do Ensido Médio) as a proper test of success of artificial intelligence techniques, thus replacing the famous Turing Test. We argue that more importantly than measuring the ability of a system in replicating human competence, the so-called ENEM test can serve as a driver of development of new techniques. Additionally, we describe how we produced a machine-readable database of questions from previous exams, which can be used for comparing techniques for natural language processing, image processing and knowledge representation and reasoning. We then present some preliminaries to serve as baseline that are based on information retrieval techniques and Word2Vec. Experiments with previous exams show that in questions concerning Humanities and Languages these baseline methods perform in average slightly better than random guessing.","PeriodicalId":202240,"journal":{"name":"2017 Brazilian Conference on Intelligent Systems (BRACIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130319665","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 Comparison of Crossover Operators Applied to the Vehicle Routing Problem with Time Window 求解带时间窗车辆路径问题的交叉算子比较
2017 Brazilian Conference on Intelligent Systems (BRACIS) Pub Date : 2017-10-01 DOI: 10.1109/BRACIS.2017.47
Thiago Muniz Stehling, S. R. Souza
{"title":"A Comparison of Crossover Operators Applied to the Vehicle Routing Problem with Time Window","authors":"Thiago Muniz Stehling, S. R. Souza","doi":"10.1109/BRACIS.2017.47","DOIUrl":"https://doi.org/10.1109/BRACIS.2017.47","url":null,"abstract":"Genetic Algorithm (GA) is recognized as a successful optimization technique, capable of solving different types of problems, principally, the NP-Hard ones. In the literature, we can find several works that combine GA with other techniques. However, we believe that a greater exploitation of its intrinsic characteristics may be a more exhaustive (i.e., more experiments will be needed to adjust the similarities and inconsistencies between technique and problem) and less expensive (i.e., other methods, which require a bigger computational effort, will not be included) alternative. In this paper, a comparison of crossover operators is performed to verify this hypothesis. These operators have been applied to the Vehicle Routing Problem with Time Window because it is a well-known and NP-Hard problem, allowing an accurate analysis of the effects of each operator in the solution of the problem. According to the statistical analysis, the results obtained by the crossover operators show significant differences. Consequently, it was possible to indicate, in the proposed scenario, the best among them.","PeriodicalId":202240,"journal":{"name":"2017 Brazilian Conference on Intelligent Systems (BRACIS)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116755345","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
Relevance Image Sampling from Collection Using Importance Selection on Randomized Optimum-Path Trees 基于随机最优路径树重要性选择的相关图像采集
2017 Brazilian Conference on Intelligent Systems (BRACIS) Pub Date : 2017-10-01 DOI: 10.1109/BRACIS.2017.58
M. Ponti
{"title":"Relevance Image Sampling from Collection Using Importance Selection on Randomized Optimum-Path Trees","authors":"M. Ponti","doi":"10.1109/BRACIS.2017.58","DOIUrl":"https://doi.org/10.1109/BRACIS.2017.58","url":null,"abstract":"The growth in image collections became an important issue when designing a successful image retrieval and recognition system. While it is important to investigate methods that uses smaller training sets or under samples the data, it is also challenging to be successful with a single model trained with a reduced number of samples, since they often require representative and sufficient observations to be accurate. We propose an algorithm that selects relevant images from a collection, based on pasting of small votes ensembles of optimum-path forest base classifiers. Since small training sets are used, it is viable for large datasets. Also, the classifiers tested maintained in general their performances after sampling using our method, even using significantly less training data.","PeriodicalId":202240,"journal":{"name":"2017 Brazilian Conference on Intelligent Systems (BRACIS)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115766553","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
A Hybrid Semi-linear System for Time Series Forecasting 时间序列预测的混合半线性系统
2017 Brazilian Conference on Intelligent Systems (BRACIS) Pub Date : 2017-10-01 DOI: 10.1109/BRACIS.2017.23
João F. L. Oliveira, E. Barreiros, C. Rodrigues, Adauto Trigueiro de Almeida Filho
{"title":"A Hybrid Semi-linear System for Time Series Forecasting","authors":"João F. L. Oliveira, E. Barreiros, C. Rodrigues, Adauto Trigueiro de Almeida Filho","doi":"10.1109/BRACIS.2017.23","DOIUrl":"https://doi.org/10.1109/BRACIS.2017.23","url":null,"abstract":"Time series forecasting is a challenging task in machine learning. Each time series may be composed by linear or nonlinear patterns which need to be mapped by techniques such as autoregressive integrated moving average (ARIMA) and artificial neural networks (ANN). This work proposes an evolutionary semi-linear artificial network for time series forecasting. The system selects the best architecture for linear and nonlinear components of the ANN in order to deal with different patterns simultaneously. Particle swarm optimization is used to find suitable architecture and weights. Experiments show that the proposed technique achieved promising results in time series forecasting.","PeriodicalId":202240,"journal":{"name":"2017 Brazilian Conference on Intelligent Systems (BRACIS)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116057048","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 Occupancy Grid Map Merging Algorithm Invariant to Scale, Rotation and Translation 一种不缩放、不旋转、不平移的占用网格地图合并算法
2017 Brazilian Conference on Intelligent Systems (BRACIS) Pub Date : 2017-10-01 DOI: 10.1109/BRACIS.2017.69
Victor Terra Ferrão, C. Vinhal, G. Cruz
{"title":"An Occupancy Grid Map Merging Algorithm Invariant to Scale, Rotation and Translation","authors":"Victor Terra Ferrão, C. Vinhal, G. Cruz","doi":"10.1109/BRACIS.2017.69","DOIUrl":"https://doi.org/10.1109/BRACIS.2017.69","url":null,"abstract":"In this paper, we consider the problem of merging occupancy grid maps obtained by different autonomous robotic agents exploring the same environment. These robots may have different sensors, processing power, memory capacities, and mapping features. Maps produced can present variations on scale, accuracy or orientation. Nowadays, merging such maps is a challenge which led us to propose an alternative heuristic approach which considers these variations. The algorithm implemented uses Scale Invariant Feature Transform (SIFT) to detect key-points while calculating transformations (rotation, translation, and scale) to merge the maps. Merging is accomplished without a priori information about a robot’s initial position and orientation. Public available data sets were used to test the algorithm, and it produced reliable combined maps. Finally, an analysis based on different tests is presented and discussed.","PeriodicalId":202240,"journal":{"name":"2017 Brazilian Conference on Intelligent Systems (BRACIS)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121470898","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: 8
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