Advances in Computational Collective Intelligence : 12th International Conference, ICCCI 2020, Da Nang, Vietnam, November 30 - December 3, 2020, Proceedings / Marcin Hernes, Krystian Wojtkiewicz, Edward Szczerbicki (eds.)
Intro -- Preface -- Organization -- Contents -- Data Mining and Machine Learning -- Rule Induction of Automotive Historic Styles Using Decision Tree Classifier -- 1 Introduction -- 2 Artificial Intelligence and Style -- 2.1 Research Relevant to the Application of AI in Design -- 2.2 The Definition and Classification of Design -- 2.3 Potential of Using Data Mining and Decision Tree to Classify Styles -- 3 Method -- 3.1 Choice of Features and Style -- 3.2 Choice of Case Study -- 3.3 Classification Methods and Tools -- 4 Results -- 4.1 Decision Tree Classification Model Diagram
4.2 The Average Accuracy of Ten Decision Trees -- 4.3 Correlation Between Design Features and Accuracy -- 4.4 The Accumulated Number of Statistical Design Features -- 4.5 Entropy, Information Gain and Gain Ratio -- 5 Discussion -- 5.1 Case Study of Automotive-Style Classification -- 5.2 Summary -- 6 Conclusion -- References -- Deep Learning for Multilingual POS Tagging -- 1 Introduction -- 2 Related Work -- 2.1 Deep Neural Network -- 2.2 Max-Margin Tensor Neural Networks -- 2.3 Convolutional Neural Network -- 2.4 Recurrent Neural Network -- 3 Part-of-Speech Taggers -- 4 Experiments
4.1 Data Set -- 4.2 Model Setup -- 4.3 Results -- 5 Conclusion -- References -- Study of Machine Learning Techniques on Accident Data -- 1 Introduction -- 2 Dataset -- 3 The Methodology -- 3.1 Clustering to Subgroup Similar Types of Accidents -- 3.2 Classification/Predictive Models for Each Cluster -- 4 Experiments, Result Analysis and Discussion -- 4.1 Results of Cluster Analysis -- 4.2 Selecting Influential Attributes by Random Forest Analysis -- 4.3 Classification and Rule Generation -- 4.4 Rule Generation Using PART -- 5 Conclusion and Possible Future Work -- References
Soil Analysis and Unconfined Compression Test Study Using Data Mining Techniques -- 1 Introduction -- 2 Related Work -- 3 Dataset -- 3.1 Mymensingh -- 3.2 Rangamati -- 4 Methodology and Results -- 4.1 Models -- 4.2 Accuracy Metric -- 4.3 Results -- 5 Conclusion -- References -- Self-sorting of Solid Waste Using Machine Learning -- 1 Introduction -- 1.1 Waste Recycling -- 1.2 Literature Review of Self-sorting Bins -- 2 Self-sorting Bin Design -- 2.1 Mechanical Design -- 2.2 Electrical Design -- 2.3 Sensors -- 3 Software Architecture -- 3.1 Classification Models -- 3.2 Combined Classifier
4 Classifiers Performance -- 5 Conclusion -- References -- Clustering Algorithms in Mining Fans Operating Mode Identification Problem -- 1 Introduction -- 2 Problem Description -- 3 Description of the Industrial Fan Station -- 4 Methodology -- 4.1 Source Data Characteristics and Preprocessing -- 4.2 Algorithms Description -- 5 Applications to Real-Life Data and Algorithms Comparison -- 6 Conclusions -- References -- K-Means Clustering for Features Arrangement in Metagenomic Data Visualization -- 1 Introduction -- 2 Related Work -- 3 Features Clustering in Synthetic Metagenomic Images
Summary
This book constitutes refereed proceedings of the 12th International Conference on International Conference on Computational Collective Intelligence, ICCCI 2020, held in Da Nang, Vietnam, in November - December 2020. Due to the the COVID-19 pandemic the conference was held online. The 68 papers were thoroughly reviewed and selected from 314 submissions. The papers are organized according to the following topical sections: data mining and machine learning; deep learning and applications for industry 4.0; recommender systems; computer vision techniques; decision support and control systems; intelligent management information systems; innovations in intelligent systems; intelligent modeling and simulation approaches for games and real world systems; experience enhanced intelligence to IoT; data driven IoT for smart society; applications of collective intelligence; natural language processing; low resource languages processing; computational collective intelligence and natural language processing
Notes
"Due to the the COVID-19 pandemic the conference was held online."
Includes author index
Online resource; title from PDF title page (SpringerLink, viewed February 1, 2021)
