International Joint Conference SOCO'16-CISIS'16-ICEUTE'16 : San Sebastián, Spain, October 19th-21st, 2016 Proceedings
This volume of Advances in Intelligent and Soft Computing contains accepted papers presented at SOCO 2016, CISIS 2016 and ICEUTE 2016, all conferences held in the beautiful and historic city of San Sebastián (Spain), in October 2016. Soft computing represents a collection or set of computational tec...
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| Corporate Authors | , , |
|---|---|
| Other Authors | , , , , , |
| Format | Electronic eBook |
| Language | English |
| Published |
Cham, Switzerland :
Springer,
[2016]
|
| Series | Advances in intelligent systems and computing ;
527. |
| Subjects | |
| Online Access | Full text |
| ISBN | 9783319473642 9783319473635 |
| ISSN | 2194-5357 ; |
| Physical Description | 1 online resource (xxiv, 805 pages) : illustrations |
Cover
Table of Contents:
- Preface; SOCO 2016; Contents; SOCO 2016: Classification; Predicting 30-Day Emergency Readmission Risk; Abstract; 1 Introduction; 2 Related Work; 3 Materials and Methods; 3.1 Support Vector Machine; 3.2 Random Forest; 4 Results; 4.1 Class Balancing; 4.2 Feature Selection; 5 Conclusions and Future Work; References; Use of Support Vector Machines and Neural Networks to Assess Boar Sperm Viability; 1 Introduction; 2 Description of the Features; 3 Experimental Results; 3.1 Linear and Quadratic Support Vector Machine; 3.2 Neural Network; 3.3 Discussion; 4 Conclusions; References
- Learning Fuzzy Models with a SAX-based Partitioning for Simulated Seizure Recognition1 Introduction; 2 Related Techniques; 2.1 AntMiner+; 2.2 Learning FRBC with ACS; 2.3 Simbolic Aggregation AproXimation; 3 Introducing SAX in the Model Learning; 4 Experiment and Results; 4.1 Materials and Methods; 4.2 Results and Discussion; 5 Conclusion; References; Real Prediction of Elder People Abnormal Situations at Home; 1 Introduction; 2 Dataset Description, Extraction and Reduce Strategy; 3 Modeling the Elders Behaviour; 4 New Raw Data Vectors to Improve Behaviour Modeling
- 5 The Hierarchical Supervised Classifier Learning6 Use Cases and Conclusion; References; SOCO 2016: Machine Learning; Assisting the Diagnosis of Neurodegenerative Disorders Using Principal Component Analysis and TensorFlow; 1 Introduction; 2 Materials and Methods; 2.1 Data Description; 2.2 Feature Extraction Based on Principal Component Analysis; 2.3 Classification Based on TensorFlow; 3 Experiments and Results; 4 Discussion and Conclusions; References; Cyclone Performance Prediction Using Linear Regression Techniques; Abstract; 1 Introduction; 1.1 Operating Principle
- 1.2 Collection Efficiency2 Materials; 3 Methodology; 3.1 Linear Regression; 3.2 Enhanced Linear Regression; 3.3 Generalized Linear Regression; 3.4 Enhanced Generalized Linear Regression; 3.5 Method of Validation; 3.6 Model Efficiency; 4 Results; 5 Conclusions; References; Time Analysis of Air Pollution in a Spanish Region Through k-means; Abstract; 1 Introduction; 2 Clustering Techniques and Methods; 2.1 Cluster Evaluation Measures; 2.2 k-means Clustering Technique; 3 Real-Life Case Study; 4 Results and Discussion; 5 Conclusions and Future Work; References
- Using Non-invasive Wearables for Detecting Emotions with Intelligent Agents1 Introduction; 2 State of the Art; 3 Problem Description; 4 System Proposal; 4.1 Data Acquisition Process; 4.2 Emotion Recognition; 4.3 Wristband Prototype; 5 Conclusions and Future Work; References; Impulse Noise Detection in OFDM Communication System Using Machine Learning Ensemble Algorithms; Abstract; 1 Introduction; 2 System Model; 3 Multi-classifiers (Ensembles) Algorithms; 3.1 Bagging; 3.2 Boosting (Bos); 3.3 Random Forest (RF); 3.4 Stacking (Stack); 4 Simulations; 4.1 Simulation Set-up; 4.2 Results Discussion