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Proceedings of the Fifth International Conference on Innovations in Bio-Inspired Computing and Applications IBICA 2014 / edited by Pavel Kömer, Ajith Abraham, Václav Snášel
Mitwirkende(r): Resource type: Ressourcentyp: Buch (Online)Buch (Online)Sprache: Englisch Reihen: Advances in Intelligent Systems and Computing ; 303 | SpringerLink BücherVerlag: Cham ; s.l. : Springer International Publishing, 2014Beschreibung: Online-Ressource (XVI, 440 p. 173 illus., 34 illus. in color, online resource)ISBN:- 9783319081564
- 006.3
- Q342
Inhalte:
Zusammenfassung: This volume of Advances in Intelligent Systems and Computing contains accepted papers presented at IBICA2014, the 5th International Conference on Innovations in Bio-inspired Computing and Applications. The aim of IBICA 2014 was to provide a platform for world research leaders and practitioners, to discuss the full spectrum of current theoretical developments, emerging technologies, and innovative applications of Bio-inspired Computing. Bio-inspired Computing remains to be one of the most exciting research areas, and it is continuously demonstrating exceptional strength in solving complex real life problems. The main driving force of the conference was to further explore the intriguing potential of Bio-inspired Computing. IBICA 2014 was held in Ostrava, Czech Republic and hosted by the VSB - Technical University of OstravaPPN: PPN: 1658613090Package identifier: Produktsigel: ZDB-2-ENG
Preface; Organization; Contents; Multi-Agent System for Remote Healthcare Monitoring; 1 Introduction; 2 A Survey of Decision Fusion Systems; 2.1 Data Fusion Level; 2.2 Feature-Fusion Level; 2.3 Decision-Fusion Level; 3 Architecture of the Multi-Agent Decision Fusion System; 3.1 DSS Encapsulation and Decision Fusion Architecture; 3.2 Two-Phases Collective Decision Process; 3.3 Decision Computation; 4 Application on Remote Healthcare Monitoring System; 4.1 Description of the Simulation Environment and Frames of Discernment; 4.2 Feature Vectors and Basic Belief Assignment; 5 Conclusion
ReferencesOptimization of Wireless Sensor NodeParameters by Differential Evolution andParticle Swarm Optimization; 1 Introduction; 2 Long-Term Simulation of Sensor Node Operation; 2.1 Energy Consumption Model; 2.2 Node Simulator; 2.3 Environmental Data; 3 Differential Evolution; 4 Particle Swarm Optimization; 5 Node Parameter Optimization Using DE and PSO; 5.1 The Optimization Problem; 5.2 Experimental Results; References; Improving the Dendritic Cell AlgorithmPerformance Using Fuzzy-Rough Set Theoryas a Pattern Discovery Technique; 1 Introduction; 2 The Dendritic Cell Algorithm
3 Fuzzy Rough Sets for Pattern Discovery4 FRST-DCA: The Solution Approach; 4.1 The FRST-DCA Feature Selection Process; 4.2 The FRST-DCA Signal Categorization Process; 5 Experimental Setup; 6 Results and Analysis; 7 Conclusion and Future Work; References; Heuristics and H-optimum Estimatorsin a Model with Type-I Constraints; 1 Introduction; 2 Statistical Background; 2.1 Two Stage Regression Model; 2.2 Best Linear Unbiased Estimator - BLUE; 2.3 H-optimum Estimator; 3 Extended H-optimum Estimator Problem; 4 Concluding Remarks; References
Hybrid Job Scheduling Algorithm for Cloud Computing Environment1 Introduction; 2 Related Works; 3 Proposed Approach; 4 Performance Evaluation; 5 Conclusion; References; Using Singular Value Decomposition as a Solution for Search Result Clustering; 1 Introduction; 2 Search Results Clustering; 3 Singular Value Decomposition (SVD); 4 Self-Organizing Maps; 5 Unified Distance Matrix; 6 Problem Formalization and Algorithm; 7 Experiment; 8 Visualizing Result; 9 Conclusion and Future Work; References; Land Cover Disturbance due to Tourism in Czech Republic; 1 Introduction; 2 Objectives and Study Area
3 Methodology4 Results; 5 Conclusions; References; Power Demand Daily Predictions Using the Combined Differential Polynomial Network; 1 Introduction; 2 Power Demand Prediction; 3 General Differential Equation Composition; 4 Combined Differential Polynomial Neural Network; 5 Power Demand Prediction Experiments; 6 Conclusion; References; Liver CT Image Segmentation with an OptimumThreshold Using Measure of Fuzziness; 1 Introduction; 2 Methodology; 2.1 Fuzzy C-Means Clustering; 2.2 Measure of Fuzziness; 2.3 Optimum Threshold and Ambiguous Pixels; 3 Abdominal CT Data Collection
4 Results and Discussion
Multi-Agent System for Remote Healthcare MonitoringOptimization of Wireless Sensor Node Parameters by Differential Evolution and Particle Swarm Optimization -- Improving the Dendritic Cell Algorithm Performance using Fuzzy-Rough Set Theory as a Pattern Discovery Technique -- Heuristics and H-optimum estimators in a model with type-I constraints -- Hybrid Job scheduling Algorithm for Cloud Computing Environment -- Using Singular Value Decomposition as a Solution for Search Result Clustering -- Land Cover Disturbance due to Tourism in Czech Republic -- Power Demand Daily Predictions using the Combined Differential Polynomial Network -- Liver CT Image Segmentation with an Optimum Threshold using Measure of Fuzziness -- Retinal Vessel Segmentation Based on Flower Pollination Search Algorithm -- Predicting biological activity of 2,4,6-trisubstituted 1,3,5-triazines using random forest -- Rich Internet Application for Crisis Management Support Case Study on Floods in Olomouc City -- Climate Recommender System for Wheat Cultivation in North Egyptian Sinai Peninsula -- Fuzzy C-Means Based Liver CT Image Segmentation with Optimum Number of Clusters -- Complex Network Analysis of Evolutionary Algorithms Applied to Combinatorial Optimization Problem -- A New Hybrid Particle Swarm Optimization with Variable Neighborhood Search for Solving Unconstrained Global Optimization -- Visualizing and Identifying the DNA Methylation Markers in Breast Cancer Tumor Subtypes -- Multiobjective Genetic Programming of Agent Decision Strategies -- Clustering the Sources of EEG Activity During Motor Imagery by Attractor Neural Network with Increasing Activity (ANNIA) -- Neutrosophic Sets and Fuzzy C-means Clustering for Improving CT Liver Image Segmentation -- Random Forests Based Classification for Crops Ripeness Stages -- Cattle Identication using Muzzle Print Images based on Texture Features Approach -- Networks Community Detection Using Artificial Bee Colony Swarm Optimization -- Underdetermined Blind Separation of Mixtures of an Unknown Number of Sources with Additive White and Pink Noises -- Selection of Nodes and Sensors for Monitoring of Air Pollutants Related to City Trac -- Orphan Drug Legislation with Data Fusion Rules Using Multiple Fingerprints Measurements -- A Framework of Secured and Bio-Inspired Image Steganography using Chaotic Encryption with Genetic Algorithm Optimization (CEGAO) -- Design and Implementation of an improved Datacenter Broker policy to improve the QoS of a Cloud -- Evolutionary Techniques for Image Segmentation -- Dimensionality Reduction and Prediction of the Protein Macromolecule Dissolution Profile -- Remote Sensing Image Fusion Approach Based on Brovey and Wavelets Transforms -- Application of FUZZY-AHP for Industrial Cluster Identification -- Basic Mechanisms of the Formal Knowledge Representation for the Information Searching Tool for Process Modeling -- Prediction of Oil Prices Using Bagging and Random Subspace -- Comparison of Local and Global Ranking in Networks -- Formalization of Software Process Using Intuitive Mapping of UML Activity Diagram to CPN -- Comparison of Feature Reduction Methods in the Task of Arrhythmia Classification -- Short Term Power Prediction of the Photovoltaic Power Station Based on Power Profiles -- Bagging Technique using Temporal Expansion Functions.
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