Keywords:
Electronic books.
Type of Medium:
Online Resource
Pages:
1 online resource (617 pages)
Edition:
1st ed.
ISBN:
9783030200558
Series Statement:
Advances in Intelligent Systems and Computing Series ; v.950
URL:
https://ebookcentral.proquest.com/lib/geomar/detail.action?docID=5771262
Language:
English
Note:
Intro -- Preface -- Organization -- General Chairs -- International Advisory Committee -- Program Committee Chairs -- Program Committee -- Special Sessions -- Soft Computing Methods in Manufacturing and Management Systems -- Sec7 -- Soft Computing Applications in the Field of Industrial and Environmental Enterprises -- Sec9 -- Optimization, Modeling and Control by Soft Computing Techniques -- Sec11 -- Soft Computing in Aerospace, Mechanical and Civil Engineering: New Methods and Industrial Applications -- Sec13 -- SOCO 2019 Organizing Committee -- Contents -- Machine Learning -- Indexes to Find the Optimal Number of Clusters in a Hierarchical Clustering -- 1 Introduction -- 2 Related Work -- 2.1 Clustering Methods -- 2.2 Validation Indexes -- 3 Our Proposal -- 3.1 Implementation -- 4 Experimentation -- 4.1 Working Environment and Datasets -- 4.2 Experimental Results -- 5 Conclusions -- References -- Analysis and Application of Normalization Methods with Supervised Feature Weighting to Improve K-means Accuracy -- 1 Introduction -- 2 Hypothesis and Foundations -- 3 Proposed Two-Stage Methodology for Normalization and Feature Weighting -- 3.1 First Stage: Normalization Methods -- 3.2 Second Stage: Feature Weighting Strategy -- 4 Results -- 5 Conclusions -- References -- Classifying Excavator Operations with Fusion Network of Multi-modal Deep Learning Models -- Abstract -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Video-Based Model -- 3.2 Sensor-Based Model -- 3.3 Fusion Network -- 4 Experiments -- 4.1 Dataset and Experimental Settings -- 4.2 Result Analysis -- 5 Conclusion -- Acknowledgement -- References -- A Study on Trust in Black Box Models and Post-hoc Explanations -- 1 Introduction -- 2 Intelligibility and Trust -- 2.1 Human Subject Studies and Trust Measures -- 2.2 Post-hoc Explanation Approaches -- 3 Method.
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3.1 Participants -- 3.2 Materials -- 3.3 Design -- 3.4 Procedure -- 4 Results -- 4.1 Trust Variables -- 5 Conclusion -- References -- A Study on Hyperparameter Configuration for Human Activity Recognition -- 1 Introduction -- 2 Related Work -- 3 Activity Recognition Overview -- 4 Experimental Results -- 4.1 The PAMAP2 Dataset -- 4.2 Experimental Setup -- 4.3 HAR Accuracy Results -- 4.4 Execution Time and Energy Consumption -- 5 Conclusion -- References -- A Fuzzy Approach for Sentences Relevance Assessment in Multi-document Summarization -- Abstract -- 1 Introduction -- 2 Proposed Method -- 2.1 Preprocessing -- 2.2 Semantic Graph Generation -- 2.3 Graph Merging Process -- 2.4 Concepts Clustering -- 2.5 Fuzzy Relevance Assessment of the Sentences -- 2.6 Summary Construction -- 3 Experimental Results -- 4 Conclusions and Future Works -- Acknowledgments -- References -- Online Estimation of the State of Health of a Rechargeable Battery Through Distal Learning of a Fuzzy Model -- 1 Introduction -- 2 Description of the Proposed Model -- 2.1 IC Curves and Analysis -- 2.2 Proposed Model and Learning Methodology -- 2.3 Fuzzy Rule-Based Model -- 3 Empirical Study -- 3.1 Experimental Setup -- 3.2 Numerical Results -- 4 Concluding Remarks -- References -- A Proposal for the Development of Lifelong Dialog Systems -- 1 Introduction and Related Work -- 2 Statistical Dialog Management Methodologies -- 3 User Intention Modeling -- 4 Emotional State Recognition -- 5 The Enhanced UAH Dialog System -- 6 Experiments -- 7 Conclusions and Future Work -- References -- Smart Cities and IOT -- Real-Time Big Data Analytics in Smart Cities from LoRa-Based IoT Networks -- 1 Introduction -- 2 Related Works -- 3 System Architecture -- 3.1 LoRa Based Infrastructure -- 3.2 JSON Payload Buffering and Preprocessing -- 3.3 Real-Time Environment -- 3.4 Big Data Streaming Engine.
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4 Results -- 4.1 Dataset Construction and Linear Regression Parametrization -- 4.2 Experimental Setup -- 4.3 Analysis -- 5 Conclusions -- References -- Deep Learning in Modeling Energy Cost of Buildings in the Public Sector -- Abstract -- 1 Introduction -- 2 Literature Review -- 3 Data and Sampling -- 4 Methodology -- 5 Results and Discussion -- 6 Conclusion -- Acknowledgments -- References -- Framework for the Detection of Physiological Parameters with Musical Stimuli Based on IoT -- Abstract -- 1 Introduction -- 2 Physiological Parameters, Emotions and External Stimuli -- 2.1 From the Theories of Emotion to Affective Computing -- 2.2 Physiological Parameters and Emotional States -- 2.3 IoT and Biosensors -- 3 Smoodsically. An Overview of the Framework Proposed -- 4 Case Study -- 4.1 EDA and Temperature Results -- 5 Conclusion and Future Work -- Acknowledgments -- References -- Edge Computing Architectures in Industry 4.0: A General Survey and Comparison -- 1 Introduction -- 2 Internet of Things and Edge Computing -- 3 Edge Computing Reference Architectures -- 3.1 FAR-Edge RA -- 3.2 Edge Computing RA 2.0 -- 3.3 Industrial Internet Consortium RA -- 4 Evaluation of the Edge Reference Architectures -- 5 Conclusions and Future Work -- References -- Predictive Maintenance from Event Logs Using Wavelet-Based Features: An Industrial Application -- 1 Introduction -- 2 From Event to Time Functions -- 3 Methods -- 3.1 Wavelets Transform -- 3.2 Random Forest -- 4 Experiments -- 4.1 Predictive Performance -- 4.2 Variable Importance -- 4.3 Observations Proximity -- 5 Discussion and Conclusion -- References -- Building Robust Prediction Models for Defective Sensor Data Using Artificial Neural Networks -- 1 Introduction -- 2 Proposed Approach -- 2.1 NoiseDrop -- 2.2 Input Drop -- 3 Experimental Setup -- 3.1 Data -- 3.2 Results -- 4 Conclusions -- References.
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Temporal Data Analysis -- Ensemble Deep Learning for Forecasting 222Rn Radiation Level at Canfranc Underground Laboratory -- 1 Introduction -- 2 Methods and Materials -- 2.1 Convolutional Neural Networks -- 2.2 Seasonal and Trend Decomposition Using Loess -- 2.3 Recurrent Neural Networks -- 2.4 Statistics -- 3 Experimental Results and Models Comparison -- 4 Conclusions -- References -- Search of Extreme Episodes in Urban Ozone Maps -- 1 Introduction -- 2 Methods and Materials -- 2.1 DBSCAN -- 2.2 Distance Metrics -- 3 Experimental Results -- 3.1 Outliers Detection with DBSCAN and L2 Norm -- 3.2 Outliers Detection with DBSCAN and L1-Norm -- 4 Conclusions -- References -- A Novel Heuristic Approach for the Simultaneous Selection of the Optimal Clustering Method and Its Internal Parameters for Time Series Data -- 1 Introduction -- 2 Proposed Harmony Search Algorithm for Optimal Clustering Configuration (HSOCC) -- 2.1 Encoding Solution -- 2.2 Steps of the HSOCC Algorithm -- 3 Simulation Results -- 4 Conclusions and Future Work -- References -- A Hybrid Approach for Short-Term NO2 Forecasting: Case Study of Bay of Algeciras (Spain) -- Abstract -- 1 Introduction -- 2 Area and Data Description -- 3 Methods -- 3.1 LASSO -- 3.2 ANNs -- 4 Experimental Procedure -- 5 Results and Discussion -- 6 Conclusions -- Acknowledgements -- References -- Context-Aware Data Mining vs Classical Data Mining: Case Study on Predicting Soil Moisture -- 1 Introduction -- 1.1 Related Work -- 1.2 Context-Aware DM vs Classical DM Concepts -- 2 Experimental Setup -- 2.1 Description (Reading) of the Existing Data -- 2.2 Preprocessing the Data -- 2.3 Preliminary Decisions Before Implementing the Data Mining Processes -- 3 Experiment Implementation and Results -- 3.1 Classical DM vs CADM Process Implementation -- 3.2 DM vs CADM Results -- 4 Conclusions -- References.
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DTW as Alignment Function in the Context of Time Series Balancing -- 1 Introduction -- 2 The Proposal -- 2.1 The TS_SMOTE Algorithm -- 2.2 The Distance Functions and Alignment Issues in Balancing TS Problems -- 2.3 Building an Unaligned Dataset -- 3 Experiments and Results -- 3.1 Materials and Methods -- 3.2 Numerical Results -- 4 Conclusions -- References -- Feature Clustering to Improve Fall Detection: A Preliminary Study -- 1 Introduction -- 2 Peak Detection and Feature Extraction -- 3 Data Modeling and Classification -- 4 Experimental Design -- 4.1 Dataset Description -- 4.2 Cross Validation -- 5 Obtained Results and Discussion -- 6 Conclusions -- References -- Data Generation and Preparation -- Creation of Synthetic Data with Conditional Generative Adversarial Networks -- 1 Introduction -- 2 Methodology -- 2.1 Generative Adversarial Networks -- 2.2 Conditional Adversarial Networks -- 2.3 Dataset -- 2.4 Software and Experimental Setting -- 3 Results -- 3.1 Generating New Credit Card Data with CGANs -- 3.2 Similarity of the Data -- 3.3 Classification Results -- 4 Discussion -- References -- Data Selection to Improve Anomaly Detection in a Component-Based Robot -- 1 Introduction and Previous Work -- 2 Anomaly Detection -- 2.1 Support Vector Machines -- 2.2 Metrics -- 3 Experiments and Results -- 3.1 Dataset -- 3.2 Results on the Whole Dataset -- 3.3 Results on Trial 21 -- 4 Conclusions and Future Work -- References -- Addressing Low Dimensionality Feature Subset Selection: ReliefF(-k) or Extended Correlation-Based Feature Selection(eCFS)? -- 1 Introduction -- 2 Background -- 3 The Proposed Approach -- 4 Experimentation -- 5 Results -- 6 Conclusions -- References -- A Predictive Maintenance Model Using Recurrent Neural Networks -- 1 Introduction -- 2 Background -- 3 Case Study -- 4 LSTM Architecture -- 5 Results -- 5.1 Network Classifier.
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5.2 Regressive Network.
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