
Advances in Computational Intelligence Systems
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Content
- Intro
- Preface
- Organisation
- Programme Committee
- Additional Reviewers
- Contents
- Modelling and Representation
- Integrating Association Rules Mined from Health-Care Data with Ontological Information for Automated Knowledge Generation
- 1 Introduction
- 2 Methods
- 2.1 Programming Environment
- 2.2 Databases, Ontologies and Pre-processing
- 2.3 Association Rule Mining
- 2.4 Related Work
- 3 Results
- 3.1 Ontology Integration
- 4 Discussion
- 5 Conclusions
- References
- Sentiment Analysis Model Based on Structure Attention Mechanism
- Abstract
- 1 Introduction
- 2 Related Work
- 2.1 Sentiment Classification with Traditional Machine Learning Methods
- 2.2 Sentiment Classification with RNN and Attention Mechanism
- 3 Structure-Attention-Based LSTM
- 4 Experiment
- 4.1 Dataset
- 4.2 Vector Dimension Selection
- 4.3 Results
- 4.4 Discussion
- 5 Conclusion and Outlook
- Acknowledgement
- References
- Fuzzy Representation for Flexible Requirement Satisfaction
- Abstract
- 1 Introduction
- 2 Background
- 2.1 Fuzzy Sets
- 2.2 RELAX Requirement Language
- 3 Fuzzy for Requirement Satisfaction Representation
- 4 Conclusion
- References
- A Multidisciplinary Method for Constructing and Validating Word Similarity Datasets
- Abstract
- 1 Introduction
- 2 Word Pairs Selection Based on Computational Linguistic Resources
- 2.1 Word Length and Frequency
- 2.2 Entity Words vs Non-entity Words
- 2.3 Data Balance and Word Pairs Classification
- 2.4 Word Pairs Selection Result
- 3 Scoring by Psychological Scaling
- 4 Validation Based on ERPs Experiments
- 4.1 A Brief Introduce to ERPs
- 4.2 Participants
- 4.3 Electroencephalography Recording
- 4.4 Experimental Procedure
- 4.5 Data Analysis
- 4.6 Result 1: Response Time Comparison
- 4.7 Result 2: Comparison Among Different Similarity Groups
- 4.8 Result 3: Comparison Between the Similarity Group and the Relatedness Group
- 5 Conclusion
- Acknowledgments
- References
- Fuzzy Connected-Triple for Predicting Inter-variable Correlation
- 1 Introduction
- 2 Predicting System
- 2.1 Conceptual Framework
- 2.2 Connected-Triple Extraction
- 2.3 Link Strength Measurement
- 2.4 Fuzzy Inference Model
- 3 Experimental Evaluation
- 3.1 Datasets
- 3.2 Implementation of Fuzzy Inference Model
- 3.3 Illustrative Example of Link Prediction
- 3.4 Experimental Setup
- 3.5 Results and Discussion
- 4 Conclusion
- References
- Data Integration with Self-organising Neural Network Reveals Chemical Structure and Therapeutic Effects of Drug ATC Codes
- 1 Introduction
- 1.1 Related Work
- 2 Methods
- 3 Results
- 4 Discussion
- 5 Conclusions
- References
- A Modified Approach to Inferring Animal Social Networks from Spatiotemporal Data Streams
- 1 Introduction
- 2 Network Generation
- 2.1 Arrival Time Record Selection
- 2.2 Gathering Events Clustering
- 2.3 Link Generation
- 3 Coincident Link Filtering
- 3.1 Null Model
- 3.2 Problems with Null Model
- 3.3 Fuzzy C-Means Filter
- 4 Experimental Evaluation
- 4.1 Seed Data Set and Experimental Setup
- 4.2 Results on Seeds Data Set
- 4.3 Results on Spatiotemporal Dataset (of No Ground Truth)
- 5 Conclusion
- References
- Optimisation
- A Heuristic Approach for the Dynamic Frequency Assignment Problem
- Abstract
- 1 Introduction
- 2 Overview of the Dynamic FAP
- 3 Generating the Dynamic FAP Datasets
- 4 Heuristic Approach for the Dynamic FAP
- 4.1 Initial Assignment Phase
- 4.2 Online Assignment Phase
- 4.3 Repair Phase
- 5 Experiments and Results
- 5.1 Online Assignment Phase
- 5.2 Repair Phase
- 5.3 Results Comparison with Other Approaches
- 6 Conclusions
- References
- Applying ACO to Large Scale TSP Instances
- 1 Introduction
- 2 ACO Applied to the TSP
- 3 Addressing the Scalability of ACO
- 3.1 Introducing PartialACO
- 4 Experiments with PartialACO
- 4.1 Incorporating Local Search
- 5 Applying PartialACO to Larger TSP Instances
- 6 Related Work
- 7 Conclusions
- References
- A New Steady-State MOEA/D for Sparse Optimization
- 1 Introduction
- 2 MOEA/D for Sparse Optimization
- 2.1 Problem Decomposition
- 2.2 Framework of MOEA/D
- 3 MOEA/D-II
- 3.1 Main Idea
- 3.2 Framework of MOEA/D-II
- 3.3 The Connections with MOEA/D
- 4 Computational Experiments
- 4.1 Experimental Setting
- 4.2 Experimental Results
- 5 Conclusion
- References
- A Multiobjective Evolutionary Algorithm Approach for Map Sketch Generation
- 1 Introduction
- 2 Related Work
- 2.1 Procedural Content Generation
- 2.2 Map Sketches for Real Time Strategy Games
- 3 Proposed Approach
- 3.1 Objective Functions
- 3.2 Crossover
- 3.3 Mutation
- 4 Experiments
- 4.1 Experimental Design
- 4.2 Results
- 5 Conclusion
- References
- A Reference-Inspired Evolutionary Algorithm with Subregion Decomposition for Many-Objective Optimization
- 1 Introduction
- 2 Fitness Assignment
- 3 The Algorithm
- 3.1 Initialisation and Decomposition to Subregions
- 3.2 Reproduction Procedure
- 3.3 Environmental Selection
- 4 Experimental Study
- 4.1 Experimental Results
- 5 Conclusion
- References
- Learning
- Generation of Reducts and Threshold Functions Using Discernibility and Indiscernibility Matrices for Classification
- Abstract
- 1 Introduction
- 2 Boolean Reasoning of Reducts
- 3 Generation of Reducts Based on Nearest Neighbor Relation and External Set
- 4 Generation of Reducts Based on Nearest Neighbor Relation and Indiscernibility Matrix
- 4.1 Relation Between Set [B] and Indiscernibility Matrix
- 5 Generation of Threshold Functions Using Discernibility and Indiscernibility Matrices
- 6 Conclusion
- References
- Adaptive Noise Cancelation Using Fuzzy Brain Emotional Learning Network
- 1 Introduction
- 2 Structure of FBELN
- 3 Learning Algorithm of the Adaptive FBELN Filter
- 3.1 Learning Algorithm
- 3.2 Convergence Analysis
- 4 Simulation
- 5 Conclusion
- References
- Artificial Neural Network Analysis of Volatile Organic Compounds for the Detection of Lung Cancer
- Abstract
- 1 Introduction
- 2 Methods
- 3 Classification Results
- 4 Discussion
- 5 Conclusion
- Acknowledgments
- References
- Predicting the Occurrence of World News Events Using Recurrent Neural Networks and Auto-Regressive Moving Average Models
- 1 Introduction
- 2 Related Work
- 3 Auto-Regressive Moving Average
- 4 Long Short-Term Memory
- 5 Methodology
- 5.1 Data Representation
- 5.2 Model Architectures
- 5.3 Training Procedures
- 6 Results
- 7 Discussion
- 8 Conclusion
- References
- A Comparison Study on Flush+Reload and Prime+Probe Attacks on AES Using Machine Learning Approaches
- 1 Introduction
- 2 Background and Related Works
- 2.1 Performance Monitor Unit (PMU)
- 2.2 Side Channel Attacks
- 2.3 Flush+Reload (FR)
- 2.4 Prime+Probe (PP)
- 2.5 Detection and Mitigation
- 3 Methodologies
- 3.1 Principle Component Analysis (PCA)
- 3.2 Neural Network (NN)
- 3.3 K Nearest Neighbour KNN
- 3.4 C4.5
- 4 FR and PP Attack Detection
- 4.1 Hardware and Software Specifications
- 4.2 Experiment
- 4.3 Result Analysis and Discussion
- 5 Conclusions
- References
- Classifying and Recommending Using Gradient Boosted Machines and Vector Space Models
- 1 Problem Domain: Overview
- 1.1 RecSys Challenge
- 1.2 Wider Applicability
- 2 Implementation
- 2.1 Framework
- 2.2 Features
- 2.3 Models and Training
- 2.4 Inference - Initial Results
- 2.5 Optimising Click and Buy Item Similarity Features
- 3 Conclusion and Future Work
- References
- SemCluster: Unsupervised Automatic Keyphrase Extraction Using Affinity Propagation
- 1 Introduction
- 2 Related Work
- 3 SemCluster Overview
- 3.1 Candidate Term Extraction and Disambiguation
- 3.2 Candidate Terms Similarity Computation and Clustering
- 3.3 Candidate Phrase Extraction and Keyphrase Selection
- 4 Evaluation and Results
- 5 Conclusion and Future Work
- References
- Control and Human-Machine Systems
- Towards Low-Cost P300-Based BCI Using Emotiv Epoc Headset
- Abstract
- 1 Introduction
- 2 Methodology
- 2.1 Participants
- 2.2 EEG Equipment
- 2.3 Stimuli and Procedure
- 2.4 Data Analysis and Classification
- 3 Results and Discussions
- 4 Conclusion
- Acknowledgment
- References
- Emotion Detection in E-learning Using Expectation-Maximization Deep Spatial-Temporal Inference Network
- 1 Introduction
- 2 Preliminaries and Related Research
- 2.1 Deep Spatial-Temporal Inference Network
- 3 EM-DeSTIN
- 4 Experiments
- 5 Conclusion
- References
- Human Activities Transfer Learning for Assistive Robotics
- 1 Introduction
- 2 Related Work
- 3 Activity Features
- 3.1 Data Pre-processing
- 3.2 3D Skeleton-Based Features
- 3.3 Features Normalization
- 4 Activity Classification
- 4.1 Support Vector Machine (SVM)
- 4.2 K-Nearest Neighbour (K-NN)
- 4.3 Fuzzy C-Means Algorithm
- 5 Experimental Results
- 6 Conclusions
- References
- 3D Simulation of Navigation Problem of People with Cerebral Visual Impairment
- Abstract
- 1 Introduction
- 2 Related Work
- 3 Aim and Overall Architecture
- 4 Methodology
- 4.1 Image Pre-processing
- 4.2 The Projection of the Vision Map
- 4.3 Simulation of Navigation
- 5 Implementation and Results
- 6 Summary and Conclusions
- Acknowledgment
- References
- A Fall Detection/Recognition System and an Empirical Study of Gradient-Based Feature Extraction Approaches
- 1 Introduction
- 2 Related Work
- 3 Fall Detection and Action Recognition
- 3.1 Feature Extraction
- 3.2 Pre-processing
- 3.3 Classifier
- 4 Data Set
- 5 Experimentation
- 5.1 Experiment 1
- 5.2 Experiment 2
- 5.3 Experiment 3
- 5.4 Discussions
- 6 Conclusions
- References
- Towards an Ontology of Trust for Situational Understanding
- 1 Introduction
- 2 Motivational Scenario and Desiderata
- 3 An Ontology of Trust for Situational Understanding
- 3.1 What is an Ontology?
- 3.2 Our Proposal: SitUTrustOnto
- 3.3 SitUTrustOnto and Our Case Study
- 4 Conclusion
- References
- Intelligent Transportation
- Traffic Condition Analysis Based on Users Emotion Tendency of Microblog
- Abstract
- 1 Introduction
- 2 Related Work
- 2.1 Traffic Condition Analysis Based on Social Network
- 2.2 Sentiment Analysis on Social Network
- 3 Traffic Condition Analysis Based on Users' Emotion
- 3.1 Sample Generation
- 3.2 Traffic Condition Analysis
- 4 Experiments
- 4.1 Dataset
- 4.2 The Effect of Users' Emotion Model
- 4.3 Traffic Condition Analysis on Chinese Cities
- 5 Conclusions and Future Work
- Acknowledgement
- References
- Fuzzy Bi-objective Chance-Constrained Programming Model for Timetable Optimization of a Bus Route
- 1 Introduction
- 2 Model Formulation
- 2.1 Passenger Volume Objective
- 2.2 Travel Time Objective
- 2.3 Capacity Rate Constraint
- 2.4 Model
- 3 Genetic Algorithm of Variable Length
- 4 Case Study
- 4.1 Data Collection
- 4.2 Data Processing
- 4.3 Results
- 5 Conclusion
- References
- Solving Dial-A-Ride Problems Using Multiple Ant Colony System with Fleet Size Minimisation
- 1 Introduction
- 2 Terminology
- 3 Problem Formulation
- 4 Multiple Ant Colony System
- 4.1 Fleet Size Minimisation
- 5 Simulation Results
- 6 Conclusion
- References
- Bus Scheduling Timetable Optimization Based on Hybrid Bus Sizes
- 1 Introduction
- 2 Problem Description and Model
- 2.1 Assumptions
- 2.2 Notations
- 2.3 Objectives
- 2.4 Load Factor Constraint
- 3 Model Transform and Solution
- 3.1 Genetic Algorithm with Self-crossover Operation
- 4 Case Study
- 5 Conclusion
- References
- Supplier's Information Strategy in the Presence of a Dominant Retailer
- 1 Introduction
- 2 Problem Description
- 3 Information Leakage
- 4 Information Concealment
- 5 The Supplier's Equilibrium Strategy
- 6 Conclusions
- References
- Optimization Allocation Between Multiple Logistic Tasks and Logistic Resources Considered Demand Uncertainty
- Abstract
- 1 Introduction
- 2 Problem Description
- 3 Model Building
- 3.1 Mathematical Description
- 3.2 Mathematical Model
- 4 Model Algorithm
- 5 Case Simulation
- 5.1 Case Description
- 5.2 Case Solving
- 6 Conclusion
- Acknowledgements
- References
- Two-Stage Heuristic Algorithm for a New Model of Hazardous Material Multi-depot Vehicle Routing Problem
- 1 Introduction
- 2 Transportation Model
- 3 Numerical Experiments
- 4 Conclusion
- References
- Author Index
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