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检索条件"任意字段=14th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2013"

共 80 条记录，以下是11-20 订阅

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learning-Guided Exploration in Airfoil Optimization

Learning-Guided Exploration in Airfoil Optimization

引用

14th international conference on intelligent data engineering and automated learning (ideal)

作者： Reehuis, Edgar Olhofer, Markus Sendhoff, Bernhard Back, thomas Leiden Univ LIACS Nat Comp Grp Niels Bohrweg 1 NL-2333 CA Leiden Netherlands Honda Res Inst Europe GmbH D-63073 Offenbach Germany

ISBN: (纸本)9783642412783;9783642412776

A learning-based exploration approach is proposed to escape from the basins of attraction of converged-to optima, by selecting on what is termed the interestingness of a solution. this interestingness is based on the modeling error made by a surrogate model that is trained on all solutions encountered earlier during the search. Compared to multiple standard optimization runs, a learning-guided restart scheme that alternates between a quality optimization phase and an exploration phase directed by interestingness finds solutions that are more diverse and of higher quality.

关键词： Novelty interestingness diversity restarts airfoil optimization

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Sparse Prototype Representation by Core Sets

Sparse Prototype Representation by Core Sets

引用

14th international conference on intelligent data engineering and automated learning (ideal)

作者： Schleif, Frank-Michael Zhu, Xibin Hammer, Barbara Univ Bielefeld CITEC Ctr Excellence D-33615 Bielefeld Germany

ISBN: (纸本)9783642412783;9783642412776

Due to the increasing amount of large data sets, efficient learning algorithms are necessary. Also the interpretation of the final model is desirable to draw efficient conclusions from the model results. Prototype based learning algorithms have been extended recently to proximity learners to analyze data given in non-standard data formats. the supervised methods of this type are of special interest but suffer from a large number of optimization parameters to model the prototypes. In this contribution we derive an efficient core set based preprocessing to restrict the number of model parameters to O(n/is an element of(2)) with n as the number of prototypes. Accordingly, the number of model parameters gets independent of the size of the data sets but scales with the requested precision is an element of of the core sets. Experimental results show that our approach does not significantly degrade the performance while significantly reducing the memory complexity.

关键词： learning algorithms

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A Survey on Benchmarks for Big data and Some More Considerations

A Survey on Benchmarks for Big Data and Some More Considerat...

引用

14th international conference on intelligent data engineering and automated learning (ideal)

作者： Qin, Xiongpai Zhou, Xiaoyun Renmin Univ China Sch Informat Beijing 100872 Peoples R China Jiangsu Normal Univ Dept Comp Sci Xuzhou 221116 Jiangsu Peoples R China

ISBN: (纸本)9783642412783;9783642412776

A big data benchmark suite is needed eagerly by customers, industry and academia recently. A number of prominent works in last several years are reviewed, their characteristics are introduced and shortcomings are analyzed. the authors also provide some suggestions on building the expected benchmark, including: component based benchmarks as well as end-to-end benchmarks should be used together to test distinct tools and test the system as a whole;workloads should be enriched with complex analytics to encompass different application scenarios;metrics other than performance metrics should also be considered.

关键词： Big data Benchmark Performance Scalability Fault Tolerance Energy Saving Security

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An Initialized ACO for the VRPTW

An Initialized ACO for the VRPTW

引用

14th international conference on intelligent data engineering and automated learning (ideal)

作者： Shi, Wei Weise, thomas Univ Sci & Technol China USTC Birmingham Joint Res Inst Intelligent Comput Hefei 230026 Anhui Peoples R China

ISBN: (纸本)9783642412783;9783642412776

the Vehicle Routing Problem with Time Windows is an important task in logistic planning. the expenditure on employing labor force, i.e., drivers for vehicles, accounts for most of the costs in this domain. We propose an initialized Ant Colony approach, IACO-VRPTW, with the primary goal (f(1)) to reduce the number of vehicle needed to serve the customers and the second-priority goal (f(2)) of decreasing the travel distance. Compared with methods that optimize f(2), IACO-VRPTW can reach or reduce f(1) in 8 out of 18 instances of the Solomon benchmark set, at the cost of increasing travel distance slightly. IACO-VRPTW can effectively decrease the number of vehicles, travel distance and runtime compared with an ACO without initialization.

关键词： Vehicles

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A Pruning Algorithm for Extreme learning Machine

A Pruning Algorithm for Extreme Learning Machine

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14th international conference on intelligent data engineering and automated learning (ideal)

作者： Li Ying Li Fan-jun Qi Lu Univ Technol Sch Sci Jinan 250353 Shandong Peoples R China Univ Jinan Sch Math Sci Jinan 250022 Shandong Peoples R China

ISBN: (纸本)9783642412783;9783642412776

It is difficult for Extreme learning Machine (ELM) to estimate the number of hidden nodes used to match with the learning data. In this paper, a novel pruning algorithm based on sensitivity analysis is proposed for ELM. the measure to estimate the necessary number of hidden layer nodes is presented according to the defined sensitivity. When the measure is below the given threshold, the nodes with smaller sensitivities are removed from the existent network all together. Experimental results show that the proposed method can produce more compact neural network than some other existing similar algorithms.

关键词： Single-hidden-layer feedforward neural networks Extreme learning Machine Sensitivity analysis Pruning algorithm

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Racing for Unbalanced Methods Selection

Racing for Unbalanced Methods Selection

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14th international conference on intelligent data engineering and automated learning (ideal)

作者： Dal Pozzolo, Andrea Caelen, Olivier Waterschoot, Serge Bontempi, Gianluca Univ Libre Bruxelles Fac Sci ULB Dept Comp Sci Machine Learning Grp Brussels Belgium Business Analyt Competence Ctr Atos Worldline Belgium

ISBN: (纸本)9783642412783;9783642412776

State-of-the-art classification algorithms suffer when the data is skewed towards one class. this led to the development of a number of techniques to cope with unbalanced data. However, as confirmed by our experimental comparison, no technique appears to work consistently better in all conditions. We propose to use a racing method to select adaptively the most appropriate strategy for a given unbalanced task. the results show that racing is able to adapt the choice of the strategy to the specific nature of the unbalanced problem and to select rapidly the most appropriate strategy without compromising the accuracy.

关键词： Unbalanced data Fraud detection Racing

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Handling Different Levels of Granularity within Naive Bayes Classifiers

Handling Different Levels of Granularity within Naive Bayes ...

引用

14th international conference on intelligent data engineering and automated learning (ideal)

作者： Ince, Kemal Klawonn, Frank Volkswagen AG Komponenten Werkzeugbau Gifhornerstr 180 D-38037 Braunschweig Germany Ostfalia Univ Appl Sci Dept Comp Sci D-38302 Wolfenbuettel Germany Helmholtz Ctr Infect Res Bioinformat & Stat D-38124 Braunschweig Germany

ISBN: (纸本)9783642412783;9783642412776

data mining techniques usually require a flat data table as input. For categorical attributes, there is often no canonical flat data table, since they can often be considered in different levels of granularity (like continent, country or local region). the choice of the best level of granularity for a data mining task can be very tedious, especially when a larger number of attributes with different levels of granularities is involved. In this paper we propose two approaches to automatically select the granularity levels in the context of a naive Bayes classifier. the two approaches are based on the. 2 independence test including correction for multiple testing and the minimum description length principle.

关键词： data mining

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Customer Unification in E-Commerce

Customer Unification in E-Commerce

引用

14th international conference on intelligent data engineering and automated learning (ideal)

作者： Gorawski, Marcin Chroszcz, Aleksander Gorawska, Anna Silesian Tech Univ Inst Comp Sci PL-44100 Gliwice Poland

ISBN: (纸本)9783642412783;9783642412776

data mining applied to social media is gaining popularity. It is worth noticing that most e-commerce services also cause the formation of small communities not only services oriented toward socializing people. the results of their analysis are easier to implement. Besides, we can expect a better perception of the business by its own users, therefore the analysis of their behavior is justified. In the paper we introduce an algorithm which identifies particular customers among not logged or not registered users of a given e-commerce service. the identification of a customer is based on data that was given so as to accomplish selling procedure. Customers rarely use exactly the same identification data each time. In consequence, it is possible to check if customers create a group of unrelated individuals or if there are symptoms of social behavior.

关键词： data mining

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Understanding Instance Complexity in the Linear Ordering Problem

Understanding Instance Complexity in the Linear Ordering Pro...

引用

14th international conference on intelligent data engineering and automated learning (ideal)

作者： Ceberio, Josu Hernando, Leticia Mendiburu, Alexander Lozano, Jose A. Univ Basque Country UPV EHU Dept Comp Sci & Artificial Intelligence Intelligent Syst Grp Donostia San Sebastian 20018 Gipuzkoa Spain

ISBN: (纸本)9783642412783;9783642412776

the Linear Ordering Problem is a combinatorial optimization problem which has been frequently addressed in the literature due to its numerous applications in diverse fields. In spite of its popularity, little is known about its complexity. In this paper we analyze the linear ordering problem trying to identify features or characteristics of the instances that can provide useful insights into the difficulty of solving them. Particularly, we introduce two different metrics, insert ratio and ubiquity ratio, that measure the difficulty of solving the LOP with local search type algorithms with the insert neighborhood system. Conducted experiments demonstrate that the proposed metrics clearly correlate with the complexity of solving the LOP with a multistart local search algorithm.

关键词： linear ordering problem instance complexity local optima

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A Study of Representations for Resource Constrained Project Scheduling Problems Using Fitness Distance Correlation

A Study of Representations for Resource Constrained Project ...

引用

14th international conference on intelligent data engineering and automated learning (ideal)

作者： Cai, Bingqi Liu, Jing Xidian Univ Minist Educ Key Lab Intelligent Percept & Image Understanding Xian 710071 Peoples R China

ISBN: (纸本)9783642412783;9783642412776

Four representations for resource constrained project scheduling problems (RCPSPs) are studied by making use of the fitness landscape analysis technique. the fitness distance correlation (FDC) measure is used to analyze the landscapes. In the experiments, the study on the benchmark problems J30 is first presented to investigate which distance metric is more suitable for calculating FDC for RCPSPs. then, the benchmark problems Patterson, J30, and J60 are used to evaluate the effect of the four encodings on the performance of evolutionary algorithms. Finally, a standard genetic algorithm is applied to verify the predictions made by the FDC. To the best of our knowledge, this is the first work on using FDC to study different encodings for RCPSPs.

关键词： Fitness landscape analysis Fitness distance correlation Representation Resource constrained project scheduling problems

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