14th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2019) : Seville, Spain, May 13-15, 2019, Proceedings /: Seville, Spain, May 13-15, 2019, Proceedings. ([2020])
- Record Type:
- Book
- Title:
- 14th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2019) : Seville, Spain, May 13-15, 2019, Proceedings /: Seville, Spain, May 13-15, 2019, Proceedings. ([2020])
- Main Title:
- 14th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2019) : Seville, Spain, May 13-15, 2019, Proceedings
- Other Titles:
- SOCO 2019
- Further Information:
- Note: Francisco Martínez Álvarez, [and 4 others], editors.
- Editors:
- Martínez Alvarez, Francisco
- Other Names:
- SOCO (Conference), 14th
- Contents:
- 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 Clustering1 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 Strategy4 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; 5Intro; 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 Clustering1 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 Strategy4 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 Approaches3 Method; 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 Preprocessing2.2 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 … (more)
- Publisher Details:
- Cham, Switzerland : Springer
- Publication Date:
- 2020
- Extent:
- 1 online resource
- Subjects:
- 006.3
Artificial intelligence -- Congresses
Soft computing -- Congresses
Electronic books - Languages:
- English
- ISBNs:
- 9783030200558
3030200558 - Related ISBNs:
- 9783030200541
- Notes:
- Note: Description based on online resource; title from digital title page (viewed on May 23, 2019).
- Access Rights:
- Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
- Access Usage:
- Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD.DS.417203
- Ingest File:
- 02_522.xml