Details

Subject(s)

• Decision making—Data processing [Browse]
• Data mining—Congresses [Browse]
• Computational intelligence—Congresses [Browse]

Editor

• Lytvynenko, Volodymyr [Browse]
• Babichev, Sergii [Browse]

Series

Lecture notes on data engineering and communications technologies ; Volume 149. [More in this series]

Bibliographic references

Includes bibliographical references and index.

Source of description

Description based on print version record.

Contents

• Intro
• Preface
• Organization
• Program Committee
• Chairman
• Vice-chairmen
• Members
• Organization Committee
• Contents
• Analysis and Modeling of Hybrid Systems and Processes
• Application of Convolutional Neural Network for Gene Expression Data Classification
• 1 Introduction
• 2 Literature Review
• 3 Material and Methods
• 3.1 Architecture, Structure and Model of Convolutional Neural Network
• 4 Simulation, Results and Discussion
• 4.1 Gene Expression Dataset Formation and Preprocessing
• 4.2 Application of 1D One-Layer CNN for Gene Expression Data Classification
• 4.3 Application of 1D Two-Layer CNN for Gene Expression Data Classification
• 4.4 Model of 2D Convolutional Neural Network
• 4.5 Model of 2D Three-Layer Convolutional Neural Network
• 4.6 Estimation of CNN Robustness to Different Levels of Noise Component
• 5 Conclusions
• References
• Formation of Subsets of Co-expressed Gene Expression Profiles Based on Joint Use of Fuzzy Inference System, Statistical Criteria and Shannon Entropy
• 2 Problem Statement
• 3 Literature Review
• 4 Fuzzy Model of Removing the Non-informative Gene Expression Profiles by Statistical and Entropy Criteria
• 4.1 Simulation Regarding Practical Implementation of the Proposed Fuzzy Logic Inference Model
• 5 Assessing the Fuzzy Inference Model Adequacy by Applying the Gene Expression Data Classification Technique
• 6 Conclusions
• Mathematical Model of Preparing Process of Bulk Cargo for Transportation by Vessel
• 4 Materials and Methods
• 5 Experiment and Results
• 6 Discussions
• 7 Conclusions
• Computer Simulation of Joule-Thomson Effect Based on the Use of Real Gases
• 2 Literature Review.
• 3 Materials and Methods
• 3.1 Theoretical Describing the Joule-Thomson Effect
• 3.2 Calculation of Heating System Efficiency Based on the Joule-Thomson Effect
• 3.3 Calculation of Heating System Efficiency Whose Working Fluid is Water
• Simulating Soil Organic Carbon Turnover with a Layered Model and Improved Moisture and Temperature Impacts
• 3 Mathematical Model
• 3.1 Layered SOC Decomposition Model
• 3.2 Soil Moisture and Temperature Model
• 3.3 Abiotic Stress Functions
• 4 Experiment
• 4.1 Experimental Setting
• 4.2 Data Sources
• 5 Results and Discussion
• Optimization of Coagulant Dosing Process for Water Purification Based on Artificial Neural Networks
• 4.1 Water Purification Process
• 4.2 Determination of Coagulant Dose
• 4.3 Modeling of Artificial Neural Network
• 5 Experiment, Results and Discussion
• Methodology for Solving Forecasting Problems Based on Machine Learning Methods
• 2 Forecasting Methodology
• 3 Implementation of the Methodology
• 3.1 Implementation of Regression Models
• 3.2 Implementation of Models Based on Trees
• 3.3 Implementation of Neural Network Models
• 3.4 Discussion
• 4 Conclusions
• The Comprehensive Model of Using In-Depth Consolidated Multimodal Learning to Study Trading Strategies in the Securities Market
• 3.1 Market Indicators
• 3.2 Market Model
• 3.3 Environment
• 3.4 Sampling Rate
• 3.5 Depth Neural Network
• 3.6 Q-learning
• 3.7 Reinforcement Learning
• 3.8 Actor-critic Model
• 3.9 Advantage Actor Critic (A2C).
• 3.10 Deep Deterministic Policy Gradient (DDPG)
• 3.11 Proximal Policy Optimization (PPO)
• 3.12 Ensemble of Models
• 4 Experiment and Results
• 4.1 Training of Individual Models of the Ensemble
• 4.2 Training and Analysis of the Ensemble
• 4.3 Behavior of the Ensemble Model with High Market Turbulence
• 5 Discussion
• Mathematical and Computer Model of the Tree Crown Ignition Process from a Mobile Grassroots Fire
• 3 Problem Statement
• 4 Matherial and Methods
• Features of Complex Application of the Formal Method of EVENT-B for Development of Environmental Management Systems
• 2 Review of Literature
• 3.1 Features of Application of the Method of Formal Verification Model Checking
• 3.2 The Essence and Basic Principles of the Event-B Requirements Specification Method
• 3.3 The Essence and Basic Principles of Constructing FTA Failure Trees
• 3.4 The Essence and Basic Principles of the Method of Analysis of Functional Stability of FME (C) A
• 3.5 FMECA-Analysis of the Event-B Model
• 3.6 The Method of Alternating Parameter Changes (Gauss-Seidel Method) in the Environmental Management System
• 3.7 The Method of Random Blind Searches in the System of Ecological Management
• 4 Computer Simulation, Results and Discussion
• Ecology Objects Recognition by Optimized Inverse Filtration of Textured Background
• 4 The Method of Inverse Filtration Based on the Eigen Harmonic Decomposition
• 4.1 Object Recognition on Textured Background as Problem of Optimal Filtration
• 4.2 Eigen Harmonic Decomposition of Textured Image.
• 4.3 Development of IRF for Texture Recognition
• 4.4 Optimization of the IRF
• 4.5 Eigen Harmonic Decomposition for the IRF Design
• 5 Experiment
• 6 Results and Discussion
• Theoretical and Applied Aspects of Decision-Making Systems
• Information Technology to Assess the Enterprises' Readiness for Innovative Transformations Using Markov Chains
• 2 Related Works
• 4 Experiment, Results and Discussion
• Method to Find the Original Source of COVID-19 by Genome Sequence and Probability of Electron Capture
• 2 Material and Methods
• 2.1 Comparing Genome Sequences
• 2.2 Calculating the Probability of the Electron Capture
• 3 Results
• Leader-Follower Strategy of Fixed-Wing Unmanned Aerial Vehicles via Split Rejoin Maneuvers
• 2 Vehicle Model
• 3 Artificial Potential Field Function
• 3.1 Attractive Potential Field Functions
• 3.2 Repulsive Potential Field Functions
• 4 Design of the Acceleration Controllers
• 4.1 Lyapunov Function
• 4.2 Nonlinear Acceleration Controllers
• 5 Stability Analysis
• 6 Simulation Results and Discussion
• 6.1 Scenario 1: Arrowhead Formation in the Presence of Obstacles
• 6.2 Scenario 2: Double Platoon Formation in the Presence of Obstacles
• 7 Conclusion
• Prognostic Assessment of COVID-19 Vaccination Levels
• 4 Material and Methods
• Application of the Theory of Functional Stability in the Problems of Covering Territories by Sensory Networks
• 3.1 Criteria and Indicators of Functional Stability of a Complex System.
• 3.2 Sustainability of Information and Telecommunication Systems in Emergency Situations
• 3.3 Technique to Ensure the Functional Stability of the Coverage of Territories by Sensor Networks
• 3.4 Computer Simulation, Results and Discussion
• Adaptive Decision-Making Strategies in the Game with Environment
• 4 Experiments and Results
• System Analysis of the Internal and External Migration Processes in Ukraine
• 4.1 Statistical Analysis of the Population in Ukraine
• 4.2 Analysis of Internal Migration in Ukraine
• 4.3 Analysis of External Migration in Ukraine
• 5 Results and Discussions
• Associative Information Retrieval in Medical Databases
• 1 Introduction and Literature Review
• 3.1 Method and Basic Assumptions
• 3.2 Development of an Associative Information Retrieval Method Based on Determining the Degree of Similarity of Two Strings
• 3.3 Development of Criteria for the Similarity of Text Strings Based on the Selected Method
• 5 Conclusions and Future Work
• Analysis of Deep Learning Methods in Adaptation to the Small Data Problem Solving
• 2 Related Works and Problem Statement
• 3 Data Preparation in Machine Learning and Deep Learning
• 3.1 General View on the Pipeline of Data Preparation
• 3.2 Detection of Anomalies in Data
• 3.3 Data Augmentation
• 3.4 Perturbation Compensation and Stability of Classification Algorithms
• 3.5 Orthogonal Transformations in Machine and Deep Learning
• 4 Note on Implementation of Algorithms for the Task.
• 4.1 Overview of Libraries for Machine Learning Used in Study.

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ISBN

3-031-16203-X

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