Lecture Notes in Data Engineering, Computational Intelligence, and Decision Making
2022 International Scientific Conference "Intellectual Systems of Decision-Making and Problems of Computational Intelligence”, Proceedings
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Volodymyr Lytvynenko
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Book and Conference Proceedings
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Chapter and Conference Paper
Using Bayesian Networks to Estimate the Effectiveness of Innovative Projects
The paper proposes an application of Bayesian methodology to analyze the attachment effectiveness in the national economy. The methods for creation the BNs structure, their parametric learning, validation, and...
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Chapter and Conference Paper
Streaming Algorithm to the Decomposition of a Polyatomic Molecules Mass Spectra on the Polychlorinated Biphenyls Molecule Example
Mass spectrometry is one of the fundamental analytical techniques of our time. As a rule, the primary processing of mass spectrometric data in modern quadrupole mass spectrometers from leading manufacturers is...
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Chapter and Conference Paper
Prediction of Native Protein Conformation by a Hybrid Algorithm of Clonal Selection and Differential Evolution
The methods for protein structure prediction are based on the thermodynamic hypothesis, according to which the free energy of the “protein-solvent” system is minimal in the folded state of protein. By predicti...
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Chapter and Conference Paper
Comparative Analysis of Inductive Density Clustering Algorithms Meanshift and DBSCAN
The article presents an inductive model of objective clustering based on the MeanShift clustering technique. The algorithm for breaking an assortment of original data into two evenly powerful subsets is employ...
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Chapter and Conference Paper
Dynamic Bayesian Network Model of a Country’s Economic Extension
This paper presents the studies’ results on the probability-determined models development based on Bayesian networks to estimate the economic development measure of Ukraine. Considering that one of the difficu...
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Chapter and Conference Paper
Dynamic Bayesian Networks Application for Economy Competitiveness Situational Modelling
In the research, a dynamic BN (DBN) was designed to assess general trends in the level of regional competitiveness depending on economic detectors. This dynamic model is built on the basis of a trained, alread...
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Chapter and Conference Paper
Application of Inductive Bayesian Hierarchical Clustering Algorithm to Identify Brain Tumors
The article presents the results of research concerning development of inductive algorithm for hierarchical Bayesian clustering of gene expression of patients with two types of brain tumors and healthy individ...
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Chapter and Conference Paper
Dynamic Bayesian Networks Application for Evaluating the Investment Projects Effectiveness
In this paper, we propose a methodology for using dynamic Bayesian networks (DBN) in the tasks of assessing the success of an investment project. The methods of constructing DBN, their parametric learning, val...
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Chapter and Conference Paper
Some Features of the Numerical Deconvolution of Mixed Molecular Spectra
The direct method features of finding the weight coefficients of the mixed molecular spectrum components on the basis of their reference samples are considered in this paper. It has been established that the p...
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Chapter and Conference Paper
Dynamic Bayesian Networks in the Problem of Localizing the Narcotic Substances Distribution
This paper proposed a methodology for the use of static and dynamic Bayesian networks (BN) in the problems of localizing the distribution of narcotic substances. Methods for constructing the BN structure, the...
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Chapter and Conference Paper
Protein Tertiary Structure Prediction with Hybrid Clonal Selection and Differential Evolution Algorithms
The paper deals with the problem of protein tertiary structure prediction based on its primary sequence
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Chapter and Conference Paper
Expansion of the Capabilities of Chromatography-Mass Spectrometry Due to the Numerical Decomposition of the Signal with the Mutual Superposition of Mass Spectra
Numerical methods for expanding the field of applicability of chromatography-mass spectrometry in the case of poorly separated signals are considered. We found that the existence of additive noise in the initi...
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Chapter and Conference Paper
Hybrid Methods of GMDH-Neural Networks Synthesis and Training for Solving Problems of Time Series Forecasting
In this paper, for solving the problem of forecasting non-stationary time series, hybrid learning methods for GMDH-neural networks are proposed
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Chapter and Conference Paper
A Fuzzy Model for Gene Expression Profiles Reducing Based on the Complex Use of Statistical Criteria and Shannon Entropy
The paper presents the technology of gene expression profiles reducing based on the complex use of fuzzy logic methods, statistical criteria and Shannon entropy. Simulation of the reducing process has been pe...
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Chapter and Conference Paper
Model of the Objective Clustering Inductive Technology of Gene Expression Profiles Based on SOTA and DBSCAN Clustering Algorithms
The paper presents the hybrid model of the objective clustering inductive technology based on complex using of the self-organizing SOTA and the density DBSCAN clustering algorithms. The inductive methods of co...
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Chapter and Conference Paper
Objective Clustering Inductive Technology of Gene Expression Sequences Features
Technology of high dimensional data features objective clustering based on the methods of complex systems inductive modeling is presented in the paper. Architecture of the objective clustering inductive techno...
