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检索条件"任意字段=19th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2018"

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19th international conference on intelligent data engineering and automated learning, ideal 2018

19th International Conference on Intelligent Data Engineerin...

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19th international conference on intelligent data engineering and automated learning, ideal 2018

ISBN: (纸本)9783030034955

the proceedings contain 125 papers. the special focus in this conference is on intelligent data engineering and automated learning. the topics include: Mining attributed interaction networks on industrial event logs;evidence-based systematic literature reviews in the cloud;bibliometric network analysis to identify the intellectual structure and evolution of the big data research field;a new approach for implicit citation extraction;constructing bibliometric networks from Spanish doctoral theses;measuring the impact of the international relationships of the andalusian universities using dimensions database;gaussian process kernels for support vector regression in wind energy prediction;studying the effect of measured solar power on evolutionary multi-objective prediction intervals;Merging ELMs with satellite data and clear-sky models for effective solar radiation estimation;measuring extremism: Validating an alt-right Twitter accounts dataset;distribution-based discretisation and ordinal classification applied to wave height prediction;wind power ramp events ordinal prediction using minimum complexity echo state networks;GELAB - A Matlab toolbox for grammatical evolution;bat algorithm swarm robotics approach for dual non-cooperative search with self-centered mode;hospital admission and risk assessment associated to exposure of fungal bioaerosols at a municipal landfill using statistical models;novelty detection using elliptical fuzzy clustering in a reproducing kernel Hilbert space;semi-supervised learning to reduce data needs of indoor positioning models;different approaches of data and attribute selection on headache disorder;a study of fuzzy clustering to archetypal analysis;bare bones fireworks algorithm for medical image compression;riskTrack: Assessing the risk of Jihadi radicalization on Twitter using linguistic factors.

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19th international conference on intelligent data engineering and automated learning, ideal 2018

19th International Conference on Intelligent Data Engineerin...

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19th international conference on intelligent data engineering and automated learning, ideal 2018

ISBN: (纸本)9783030034924

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data Analysis and Anomaly Detection in a Wind Farm with k-Nearest Neighbors 25th

Data Analysis and Anomaly Detection in a Wind Farm with k-Ne...

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25th international conference on intelligent data engineering and automated learning

作者： Weiss, Bassel Esteban, Segundo Santos, Matilde Univ Complutense Madrid Dpto Arquitectura Computadores Automat Madrid 28040 Spain UCM Inst Knowledge Technol Madrid 28040 Spain

ISBN: (纸本)9783031777370;9783031777387

this paper presents an in-depth analysis of data from the Alpha Ventus offshore wind farm, emphasizing the identification and detection of anomalies in wind turbine performance. Utilizing real-world data from the RAVE (Research at Alpha Ventus) project, we explore the complexities of offshore wind energy generation, including the effects of wind speed, nacelle position, and environmental factors on turbine behaviour. In this paper, among the various machine learning techniques, we have selected k-nearest neighbours (k-NN), to identify patterns and detect anomalies indicative of potential issues. Our findings demonstrate that some turbines of the wind farm, centrally located, are subject to significant wake effects and operational irregularities. By adjusting the parameters of the k-NN model, we achieved an anomaly detection framework, enhancing the reliability of turbine operation and maintenance.

关键词： Offshore wind energy Anomaly detection Wind turbine data analytics Machine learning K-nearest neighbours Predictive maintenance

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A Supervised Clustering Approach to Detect Similar Soccer Players 25th

A Supervised Clustering Approach to Detect Similar Soccer Pl...

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25th international conference on intelligent data engineering and automated learning

作者： Vidal, Andreu Simo Sanchez-Anguix, Victor Alberola, Juan M. Valencian Res Inst Artificial Intelligence Valencia Spain Univ Politecn Valencia Inst Tecnol Informat Cami Vera S-N Valencia 46022 Spain Univ Politecn Valencia Cami Vera S-N Valencia 46022 Spain

ISBN: (纸本)9783031777370;9783031777387

One promising application of data analytics in soccer is the identification of groups of players with similar playing styles. this can enhance recruitment processes and assist in tactical decisions, such as substitutions during a match. Previous research has explored various methods to measure a player's contribution, identify key variables for player positions, and predict market value using machine learning techniques. However, these efforts often focus on traditional player positions or a limited set of gameplay characteristics, lacking a comprehensive analysis of player participation. this paper introduces a novel approach to clustering similar soccer players using supervised clustering and dimensionality reduction. Unlike previous studies, our method aims to refine the well-known positions of players and incorporates a wide range of in-game metrics to provide a holistic view of each player's playing style.

关键词： big data machine learning dimensionality reduction sports analytics clustering optimisation

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Optimizing Vehicle Coordination at Multi-lane Intersections Using Traffic Control Algorithms 25th

Optimizing Vehicle Coordination at Multi-lane Intersections ...

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25th international conference on intelligent data engineering and automated learning

作者： Gonzalez, Cesar L. Delgado, Santiago L. Alberola, Juan Miguel Nino, Luis F. Julian, Vicente Univ Politecn Valencia Valencian Res Inst Artificial Intelligence VRAIN Camino Vera S-N Valencia 46022 Spain Univ Nacl Colombia Lab Invest Sistemas Inteligentes LISI Ingn Sistemas Ind Carrera 45 26-85 Bogota 111321 Colombia Univ ECCI Grp Invest SIGCIENTY Carrera 10 19-64 Bogota 110311 Colombia

ISBN: (纸本)9783031777370;9783031777387

intelligent Transportation Systems (ITS) encompass several strategies aimed at ensuring safe and efficient vehicle-to-vehicle interactions on roads. these strategies involve the implementation of advanced technologies, including intelligent traffic lights, wireless (V2X) communication systems, visual recognition systems, and algorithms. In this research, we introduce the implementation of a distributed algorithm tailored for managing highly complex road infrastructure, particularly intersections in urban areas with multiple lanes. Our evaluation of the system's performance involves applying a type of density distribution called "Biased" and comparing it against a traditional traffic control system (traffic lights - "Green Wave"). the inclusion of this type of density distribution aims to align our approach with real-world traffic conditions, specifically the variation in densities across different lanes. this comprehensive assessment allows for a more thorough evaluation of system performance.

关键词： Autonomous driving Distributed intersection management Multiple lanes intelligent transportation system Density distribution

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intelligent Agents in a Blockchain-Based Electronic Voting System 19th

Intelligent Agents in a Blockchain-Based Electronic Voting S...

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19th international conference on intelligent data engineering and automated learning (ideal)

作者： Pawlak, Michal Poniszewska-Maranda, Aneta Guziur, Jakub Lodz Univ Technol Inst Informat Technol Lodz Poland

ISBN: (纸本)9783030034931;9783030034924

there exist many approaches to electronic voting. Each of them has its own advantages and disadvantages. However, most of them suffer from lack of transparency and auditability. Recently developed blockchain technology may provide a solution to these issues. this paper presents a use of multi-agent system idea and intelligent agents in Auditable Blockchain Voting System (ABVS), which is a blockchain-based supervised and non-remote internet voting system intended to be end-to-end verifiable and auditable.

关键词： E-voting Blockchain E-voting system intelligent agent Multi-agent system

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Improving SeNA-CNN by Automating Task Recognition 19th

Improving SeNA-CNN by Automating Task Recognition

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19th international conference on intelligent data engineering and automated learning (ideal)

作者： Zacarias, Abel Alexandre, Luis A. Univ Beira Interior Inst Telecomunicacoes Rua Marques d Avila & Bolama P-6201001 Covilha Portugal

ISBN: (纸本)9783030034931;9783030034924

Catastrophic forgetting arises when a neural network is not capable of preserving the past learned task when learning a new task. there are already some methods proposed to mitigate this problem in artificial neural networks. In this paper we propose to improve upon our previous state-of-the-art method, SeNA-CNN, such as to enable the automatic recognition in test time of the task to be solved and we experimentally show that it has excellent results. the experiments show the learning of up to 4 different tasks with a single network, without forgetting how to solve previous learned tasks.

关键词： Supervised learning Lifelong learning Catastrophic forgetting Convolutional neural networks

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Improving Time Series Prediction via Modification of Dynamic Weighted Majority in Ensemble learning 19th

Improving Time Series Prediction via Modification of Dynamic...

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19th international conference on intelligent data engineering and automated learning (ideal)

作者： Loderer, Marek Pavlik, Peter Rozinajova, Viera Slovak Univ Technol Bratislava Fac Informat & Informat Technol Ilkovicova 2 Bratislava 84104 Slovakia

ISBN: (纸本)9783030034931;9783030034924

In this paper, we explore how the modified Dynamic Weighted Majority (DWM) method of ensemble learning can enhance time series prediction. DWM approach was originally introduced as a method to combine predictions of multiple classifiers. In our approach, we propose its modification to solve the regression problems which are based on using differing features to further improve the accuracy of the ensemble. the proposed method is then tested in the domain of energy consumption forecasting.

关键词： Ensemble learning Dynamic weighted majority method Time series prediction

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ALoT: A Time-Series Similarity Measure Based on Alignment of Textures 19th

ALoT: A Time-Series Similarity Measure Based on Alignment of...

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19th international conference on intelligent data engineering and automated learning (ideal)

作者： Ogul, Hasan Ostfold Univ Coll Fac Comp Sci POB 700 N-1757 Halden Norway

ISBN: (纸本)9783030034931;9783030034924

Inferring the similarity between two time-series signals is a key step in several data analysis tasks for a variety of engineering applications. In this paper, we introduce a novel elastic similarity measure (ALoT) based on the alignment of textures, instead of observed values, extracted from input time-series signals. To obtain the texture information, Local Binary Patterns are adapted for one-dimensional signals. According to experiments performed on a large number of benchmark time-series classification datasets, the proposed method achieves higher accuracy than current pairwise similarity measures for several cases in a 1-Nearest Neighbor classification setup.

关键词： Time-series analysis Similarity measure Classification Sensory data

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Taking e-Assessment Quizzes - A Case Study with an SVD Based Recommender System 19th

Taking e-Assessment Quizzes - A Case Study with an SVD Based...

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19th international conference on intelligent data engineering and automated learning (ideal)

作者： Teodorescu, Oana Maria Popescu, Paul Stefan Mihaescu, Marian Cristian Univ Craiova Craiova Romania NetRom Software Craiova Romania

ISBN: (纸本)9783030034931;9783030034924

Recommending learning assets in e-learning systems represents a key feature. Among many available assets there are quizzes that validate and also evaluate learner's knowledge level. this paper presents a recommender system based on SVD algorithm that is able to properly recommend quizzes such that learner's knowledge level is evaluated and displayed in real time by means of a custom designed concept map for graphs algorithms within the data Structures course. A preliminary case study presents a comparative analysis between a group of learners that received random quizzes and a group of learners that received recommended questions. the visual analytics and interpretation of two representative cases show a clear advantage of the students who received recommended questions over the other ones.

关键词： SVD Recommender systems Quizzes e-learning

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