System Analysis Principles Research Articles

The methodology for adaptive modeling and forecasting nonlinear and nonstationary processes

The study is directed towards development of systemic methodology for modeling and forecasting nonlinear and nonstationary processes in economy, finances and other areas of human activities. There exist multiple problems that are to be solved with the data of such type practically in all areas of human activities: such as constructing adequate models including estimation and forecasting state of a system under investigation; technical, economic and medical diagnostics; automatic control in technologies; moving objects control; financial and other risk estimation and management; risk factor interaction; control and monitoring of microclimate in greenhouses and industrial enterprises; decision making support in business; dynamic strategic planning in production; providing stability for critical economic infrastructure etc. The structure and parameter adaptation procedures for the regression and probabilistic models are proposed as well as respective information system architecture and functional layout are developed. The system development is based on the system analysis principles such as hie­rarchical architecture of the system, adaptive approach to model structure estimation, optimization of model parameter estimation procedures, functional completeness of the system providing for autonomous operation of the system, identification and taking into consideration of possible uncertainties available in the process of data processing and mathematical model development, application of appropriate sets of quality criteria that are guarantying high quality of intermediate and final results of data analysis. The possible uncertainties are inherent to data collecting, model constructing and forecasting procedures, and play the role of negative influence factors to the computational procedures of proposed information system. Reduction of their influence is favorable for enhancing the quality of intermediate and final results of computations. The illustrative examples of practical application of the methodology developed proving the system functionality are provided.

Peculiarities of justification of a representative set of requirements for intelligent vehicles

Introduction (problem statement and relevance). The key task of ensuring confidence in motor vehicles with elements of artificial intelligence (AI vehicles) is forming of a representative set of requirements compliance with which ensures the necessary guarantees of AI vehicle functionality and safety.Absence of generally accepted and statutory approaches to justification of the requirements content constrains application of artificial intelligence technologies in motor vehicles and, respectively, impedes creation and improvement of highly automated vehicles. The purpose of the study is to analyze the principles of forming of a representative set of requirements for AI vehicles. Methodology and research methods. The paper uses the principles of qualimetry adapted for the information systems based on machine learning algorithms, it also uses the methods of system analysis, mathematical statistics, combinatorics, set theory and propositional calculus principles. Scientific novelty and results. The approach is formulated to justify the statistically representative set of requirements for AI vehicles, and that allows adequate and accurate assessment of compliance of these systems with the expectations of the customers, developers, suppliers, regulatory authorities and other stakeholders. The structure of such expectations and priorities has been considered taking into account creation and application of AI systems. It is shown that stakeholder requirements apply to both the AI vehicle life cycle processes and the systems per se taking into account particular (given) conditions of their operation. Different significant factors, which variability sets the intended operating conditions, have been considered and conditions of representativeness of test data sets used for AI vehicle trials have been formulated. It is shown that, in order to reduce the dimensionality of space of the intended operating conditions, AI vehicles can be decomposed into separate functional subsystems and then into individual AI algorithms. The ways to perform such functional decomposition have been suggested. Practical significance.The principles of justification of the requirements content offered in the paper can be used in certification testing of artificial intelligence algorithms that are used in highly automated vehicles.

Uncertainties in data processing, forecasting and decision making

Forecasting, dynamic planning, and current statistical data processing are defined as the process of estimating an enterprise’s current state on the market compared to other competing enterprises and determining further goals as well as sequences of actions and resources necessary for reaching the goals stated. In order to perform high-quality forecasting, it is proposed to identify and consider possible uncertainties associated with data and expert estimates. This is one of the system analysis principles to be hired for achieving high-quality final results. A review of some uncertainties is given, and an illustrative example showing improvement of the final result after considering possible stochastic uncertainty is provided.

The improvement of the intelligent decision support system for forecasting non-linear non-stationary processes

The paper is focused on solving the modern scientific and applied problem related to development and practical use in Decision Support Systems (DSS) of information technologies directed towards forecasting of non-linear non-stationary processes (NNP) that take place in economy and finances as well as in many other areas of activities. Thus, object of study are non-linear non-stationary processes taking place in economy and financial sphere. The basic problem of the study is development of new mathematical models and methods of analysis and forecasting non-linear non-stationary processes in economy and finances, improvement of information decision support technologies that would help to enhance quality of forecast estimates and respective decisions in conditions of uncertainties and risk. The methods given in the paper are used for automating the process of intellectual data analysis that describe the processes under study and automatizing model constructing procedures. As a result of the study performed the information technology was developed to be used in DSS based upon system analysis principles, taking into consideration possible data uncertainties, regression and intellectual data analysis. The technology provides for constructing adequate models of the process under study and computing high quality forecast estimates. The particular feature of the approach proposed is that it provides for high quality of experimental results due to taking into consideration special features of non-linear non-stationary processes that take place in various spheres of activities and their evolution is influenced by many specific factors. The use of the technology proposed in decision support systems of enterprises, state governmental organs, and local self-government will create basis for effective solving the tasks of governing development of non-linear non-stationary processes that take place in many spheres of activities. The approaches proposed in the paper can be used in practice as separately as well as parts of existing information systems at enterprises and organizations.

COMPARATIVE ANALYSIS AND PERSPECTIVES OF TECHNOLOGY DEVELOPMENT CONSTRUCTION OF PREPARABLE-MONOLITHIC GLASS-TYPE FOUNDATIONS

The prospects of developing a semi-precast technology for constructing pocket-type foundations are considered. A collection and analysis of previous publications have been conducted. An evaluation of the current state of semi-precast pocket-type foundation technology has been made, outlinied its advantages in comparison with alternative precast and monolithic construction technologies. The main problems and prospects for further research of the technology have been identified. Several structural-technological solutions for semi-precast foundation construction have been presented, describing the features of each solution, identifying the advantages and disadvantages of their application in construction. The technological solution been viewed as a system from the perspective of system analysis principles, identified the main factors as subsystem elements that determine the technological aspects of each solution. Rules for identifying factors that influence the choice of structural-technological solutions have been outlined, using the example of studying the process of constructing semi-precast foundations. A sequence of actions for constructing a system of factors and criteria has been provided. Several criteria have been selected from subsystem elements as factors for comparative analysis and evaluation of structural-technological solutions. A comparative analysis of the effectiveness of the semi-precast technology and structural-technological solutions based on selected technological criteria has been provided in comparison to monolithic and precast technologies. A comparative analysis of technologies and structural-technological solutions based on the criteria of the system has been conducted, and the results have been systematized for further evaluation. The key differences, advantages, and disadvantages of each solution have been identified in comparison to alternative solutions, outlining the quality characteristics of the identified factors in application of given solutions. The most promising solution for further research has been identified and justified.

Methodological foundations for the system analysis principles application for modeling the phenomena of heat transfer in the technological cleaning process of tanks for oil products

The article is devoted to the determination of the methodological foundations for the application of the system analysis principles for modeling the phenomena of heat transfer in the technological cleaning process of tanks for oil products. The article deals with the spontaneous combustion problem of pyrophoric deposits in oil and gas industry and a method for solving it using the principles of system analysis. The process of spontaneous combustion of pyrophoric deposits has several stages, therefore, decomposition of this process and further analysis of its structure are relevant. On the basis of a system analysis, the process stages of the pyrophoric deposits‘ spontaneous combustion have been determined and general and specific tasks have been formulated.

Adaptive forecasting and financial risk estimation

The study is directed towards development of an adaptive decision support system for modeling and forecasting nonlinear nonstationary processes in economy, finances and other areas of human activities. The structure and parameter adaptation procedures for the regression and probabilistic models are proposed as well as the respective information system architecture and functional layout are developed. The system development is based on the system analysis principles such as adaptive model structure estimation, optimization of model parameter estimation procedures, identification and taking into consideration of possible uncertainties met in the process of data processing and mathematical model development. The uncertainties are inherent to data collecting, model constructing and forecasting procedures and play a role of negative influence factors to the information system computational procedures. Reduction of their influence is favourable for enhancing the quality of intermediate and final results of computations. The illustrative examples of practical application of the system developed proving the system functionality are provided.

МЕТОДИКА ПОБУДОВИ МОДЕЛЕЙ ГЕТЕРОСКЕДАСТИЧНИХ ПРОЦЕСІВ

The aim of the study is to improve the method of construction of heteroscedastic models of time series, which is based on the use of correlation analysis of data and multitude of statistical characteristics of the model. Methodology is based on the principles of systematic data analysis in application to the estimation of structure and parameters of models using statistical data. For modelling of heteroscedastic time series models need to solve the following tasks: to apply system analysis principles to formulate the modeling methodology, to ensure proper modeling data preparation, to evaluate the structure and parameters of the models, and to form a criterion base for the correct selection of the best candidate models from the set of candidates evaluated. The technique of constructing models of heteroskedastic processes is improved, which ensures obtaining adequate models of the dynamics of dispersion with the presence of informative data. An example of constructing an adequate model of the dispersion dynamics of the heteroscedastic process is given. Computational experiments aimed at modeling the conditional dispersion dynamics are performed. The efficiency of the proposed technique for modeling non-stationary variance processes is illustrated. The obtained characteristics of the constructed GARCH - models indicate that they can be used to predict conditional variance in practice. The possibility of applying a systematic approach to the construction of heteroskedastic time series models is shown, and the sequence of operations is performed when constructing models of this type. A new model of the studied financial process has been constructed to provide high quality short-term volatility forecast. The proposed methodology ensures the construction of models of acceptable adequacy, provided the completeness and informativeness of the statistics presented in time series.

ADAPTIVE MODELING AND FORECASTING OF NONLINEAR NONSTATIONARY PROCESSES

The study is directed towards development of adaptive decision support system for modeling and forecasting nonlinear nonstationary processes in economy, finances and other areas of human activities. The structure and parameter adaptation procedures for the regression and probabilistic models are proposed as well as respective information system architecture and functional layout are developed. The system development is based on the system analysis principles such as adaptive model structure estimation, optimization of model parameter estimation procedures, identification and taking into consideration of possible uncertainties met in the process of data processing and mathematical model development. The uncertainties are inherent to data collecting, model constructing and forecasting procedures and play a role of negative influence factors to the information system computational procedures. Reduction of their influence is favorable for enhancing the quality of intermediate and final results of computations. The illustrative examples of practical application of the system developed proving the system functionality are provided.

Decision support system for forecasting financial processes on the basis of system analysis principles

A concept is proposed for solving the problem of adaptive forecasting that is based on the system analysis methodology and combined use of preliminary data processing techniques, mathematical and statistical modeling, forecasting and optimal state estimation of the processes under study. The cyclical adaptation of a structure and model parameters on the basis of a set of statistical characteristics of a process under study provides a possibility for reaching high quality estimates of forecasts under condition that data is informative. To identify and take into consideration possible stochastic, structural and parametric uncertainties it is proposed to use optimal and digital filtering and data mining methods such as Bayesian networks, adaptive BN, particle filter and other instruments. Possible parametric uncertainties are minimized with application of several alternative parameter estimation techniques such as LS, RLS, ML and Markov chains Monte Carlo sampling. The conducted study suggests that the proposed methodology can be applied to the analysis of a wide class of real life processes including nonlinear nonstationary processes in finances, economy, ecology and demography.

Personal information rights and freedoms within the modern society

The authors ascertain the correlation between the freedom of information use and both the freedom of speech and the right to information. There was applied the entire toolbox of interrelated and complementary universal scientific and specific methods inherent to philosophic research. The research methodology rests on the system and structure-functional analysis principles. The notions of information, freedom, justice and law are closely interlinked. When exercising freedom one inevitably makes his or her choice from among the available actions while relying on the previously obtained information. The human information rights that are, in their turn, a part of the overall notion of the law enjoys an exceptional role within the freedom of information. Far from being exhausted by the freedom of speech and the right to information, the freedom of information also includes various other aspects. It concerns the entire information and communication sphere at large. The freedom of information is not reduced to any certain type of socially-oriented information. The notion of the right to information goes beyond the right to access information while both of them take on the same social roles and are often terminologically interchangeable.

The main aspects of medical supply in armed forces of NATO member countries

Introduction. Nowadays medical supply system of Ukrainian military men does not fully correspond to the current needs of the troops, and has to be improved. Further direction of Ukrainian Armed Forces development demands functioning medical service on the ground of logistics management concept.Aim. In order to form the unified methodological approach to the optimization of logistics management of pharmaceutical provision of Ukrainian Armed Forces, a review of foreign and domestic scientific sources and the existing legal framework on this issue will be done.Materials and Methods. On this issue the review of foreign and domestic scientific sources and the existing legal framework has done to reach the aim of our work. Investigation methods were bibliographic and analytical ones. Results. In these review the peculiarities of military medical services of the armed forces of several NATO member countries have been studied, the main aspects of medical supply in the armed forces of NATO countries have been considered. The results of these studies indicate the need of advanced research, using the method of system analysis, structural organization and conceptual principles of logistics management of pharmaceutical provision in the armed forces of the Alliance countries. In the future, it is necessary to choose the system of logistics management of medical supply which is the most efficient and the closest in structure to the Ukrainian system and apply the best international practices of optimization flow of processes. The integration of the two models – Ukrainian and European ones helps to minimize the cost of reforming the system of logistics and standardization of Ukrainian Armed Forces.Conclusion. It was revealed that each of country – NATO member has its own system of organization of medical supply of troops, but existing NATO standards of medical support and common terminology databases allow all Alliance members, if necessary, work together. The need of development of a conceptual model of optimization of management of flow processes in the medical supply of Ukrainian Armed Forces in accordance with NATO standards has been found. Also the necessity of regulatory fixation of developed model in the domestic legislative framework and practice of military health care of Ukraine exists. It provides the opportunities and new trends of development of medical support logistic systems directed on the strengthening of Ukrainian Armed Forces fighting efficiency.

THE PRODUCTIVITY ANALYSIS OF DISCRETE INFORMATION TRANSFER SYSTEM NEAR THE SHANNON BORDER

Background . The channel capacity and productivity assessments give a chance for system analysis principles development in applied information theory for telecommunication. The central task in the bounds of proposed research is the study of discrete communication channel (DCC) productivity. Objective . The main task of current study is the analysis of discrete communication channel productivity through identification of the regularities in reliability behavior of modulation multi-position keying signals. Integral productivity assessment is the efficiency metric of communication channel resources usage. Methods . Solving the main task of research generates bases on the finding the informational abilities of DCC. These informational abilities of DCC are expressed by channel capacity and productivity per one bit of information. Finally, the interdependence between channel capacity and productivity expressed via the information efficiency parameter ηС is the integral productivity estimation for DCC. The case of multiposition keying with its varieties (QPSK, QAM-16, and QAM-64) creates significantly bigger interest. Results . The model of discrete information transfer system that includes source of discrete information, discrete communication channel with noises, defined method of signal forming and method of transmitted signal processing is proposed. The regularities of the channel capacity change and productivity of a discrete communication channel are established. Conclusions . The hypothesis of the existence of extremes (upper limits) performance of DCС in discrete information transfer system without limitations on the received signals reliability is practically substantiated. Quantitative assessment to the discrete communication channel capacity and productivity extrema are presented. For achieving required reliability is noiseimmunity coding as the recognized tool in the Shannon theory. Key words : information theory; productivity; channel capacity; information efficiency.

DSS FOR IMPLEMENTING SYSTEMIC APPROACH TO FORECASTING

A computer based decision support system is proposed the basic tasks of which are modeling and forecasting of financial processes and credit risk estimation. The system is developed on the basis of system analysis principles, i.e. it has hierarchic architecture, there exists the possibility for taking into consideration some stochastic and information uncertainties, forming alternatives for models and forecasts, and tracking the computing procedures during all stages of data processing. A modular architecture is implemented that provides a possibility for the further easy enhancement and modification of the system functional possibilities with new forecasting and parameter estimation techniques, and the risk models. High quality of final result is achieved thanks to appropriate tracking of the computing procedures at all stages of data processing: preliminary data processing, model constructing, and forecasts estimation with appropriate sets of statistical quality criteria. Example is given for modeling selected processes and credit risk estimation. The example presented shows that the system developed has good perspectives for practical use.

CLASSIFICATION OF FACTORS INFLUENCING THE COMPETITIVENESS OFSMALL CONSTRUCTION ENTERPRISES

The state of the question. The article explores the concept of competitiveness and classified the factors affecting the competitiveness of construction companies. Purpose. To study the theoretical foundations of competition to determine the possibility of accounting and business reputation of the organization, as well as to analyze and evaluate existing proposals for methods competitiveness of construction companies. Methodology . Used in the work system analysis principles and methods of research: theoretical, synthesis and comparison. Results. The results of the research used in the development of theoretical principles of adaptive management of industrial enterprises. Practical implications . Development of theoretical and methodological tools of assessment, methods of improving and maintaining the competitiveness of construction companies.

Adaptive short-term forecasting of selected financial processes

A computer based system is proposed for adaptive modeling and forecasting of financial and economic processes, that is constructed with application of system analysis principles. A hierarchical structure of decision making process during forecasts estimation was taken into consideration and the methods were used for describing uncertainties of structural, parametric and statistical nature. To estimate model structure and parameters several mutually supporting estimation techniques were used as well as optimal state estimation procedure for dynamic systems that allowed take into consideration some types of structural and statistical uncertainties. Probabilistic modeling methods make it possible to consider uncertainties of probabilistic type. The problem of short term forecasting for gold price is considered as an example using a set of constructed regression models and Kalman filter for generating optimal estimates of states. The best forecasting results were achieved with optimal filter and autoregression models with trends. Also the models were constructed for conditional variance that provided acceptable quality forecasts for variance (volatility) that could be used for constructing decision making rules in trading operations.

A ‘bottom‐up’ approach for endo‐PK/PD analysis

A 'bottom-up' PK/PD analysis approach employing system analysis principles of convolution/deconvolution and special nonparametric estimation procedures is presented to resolve the complex 'endo-PK/PD' of the endogenous form of recombinant drugs using erythropoietin (EPO) as an example. A novel cellular deconvolution algorithm is presented that facilitates the identification of the functional relationship between the variables involved in EPO's complex PK/PD. Five sheep each underwent two phlebotomies spaced 4-6 weeks apart when their hemoglobin levels were reduced from 12 g/dl to 3-4 g/dl. EPO levels and reticulocyte counts were frequently sampled. The data were analysed using end-constrained cubic splines. The rate of reticulocyte production was determined using the novel deconvolution methodology. The erythroid progenitor cells activation rate by EPO was estimated from the reticulocyte production rate using a lag-time parameter which determines the delay in the reticulocyte appearance in the blood relative to the activation of erythroid progenitors. Hysteresis minimization combined with cellular deconvolution was employed to determine the population PK/PD transduction function relating the progenitor activation rate to EPO concentrations in a nonparametric manner without assuming a specific structure. The proposed approach provides a rational informative starting point for developing parametric PK/PD models to resolve the complex endo-PK/PD of recombinant drugs.

A Database-Centric and Web-Automatic Hypertext Application Design Method

With the evolution of World Wide Web from the simple delivery mechanism to a platform for complex business applications, Web-based business computing is already seen as a new competitive business weapon. The potential commercial payoff of WWW application attracts more and more organizations to build their own web sites and develop business-to-business or business-to-consumer applications on the Internet. Designing Web applications has become a critical corporate strategic issue. However, current methods of modeling and designing hypertext applications are in chaotic and ad-hoc nature. These approaches lack the stringent and rigorous system analysis and design principles. Special efforts are needed to develop a formal method to support the modeling and design of hypertext applications. This research aims to tackle this important issue and propose an effective and efficient design alternative. We build a toolkit prototype that implements the design method we present. This toolkit is easy to use and to integrate with SQL compliant database systems.We develop a Web hypertext design method called the database-centric Web hypertext design method (DWHDM) to approach Web page requirements analysis, Web hypertext navigation design, Web page template generation, and hypertext information system maintenance. We adopt UML class diagram, state diagram, and sequence diagram to capture user requirements and application characteristics. We use a relational or object-relational database system to serve as the integrating design repository.

A System Approach to Pharmacodynamics. Input-Effect Control System Analysis of Central Nervous System Effect of Alfentanil

Virtually all biological variables, including those affected by drugs, are subject to adaptive self regulation. In the description of the pharmacodynamics (PD) of drugs, it may be necessary to consider the endogenous control system (ECS) as an integral part of the PD. A PDECS model based on system analysis principles is presented and tested on PD data for alfentanil considering the central nervous system activity quantified by a power spectrum analysis of the electroencephalogram. The model was tested in terms of a proposed relative prediction performance criterion that measures the accuracy of future predictions relative to how well the model describes (fits) the past effect data. A mean value of 80% (standard deviation, 28) for relative prediction performance indicates that the model performs well when challenged by the complex multiple infusion scheme used in the test. The overshoot phenomenon observed in the data is considered by the PDECS model as a ECS-based tolerance phenomenon. The proposed development of tolerance is modeled as a variable gain in the ECS processing that influences the effect. Although the development and loss of tolerance is determined by a single rate constant in the tolerance model, the rates of increase and decrease of tolerance may be substantially different. Contrary to other PD tolerance models, the proposed PDECS approach models the tolerance in terms of an effect deviation from an ECS set point. The intrinsic (no tolerance) effect of the drug is isolated in terms of an open loop (no feedback) effect.

Estimation of amobarbital plasma-effect site equilibration kinetics. Relevance of polyexponential conductance functions

The time delay between drug plasma concentrations and effect has been modeled most commonly by the effect compartment approach, assuming first-order monoexponential equilibrium kinetics between plasma and effect site. So far this assumption has not been rigorously probed. The purpose of the present investigation was to model the delay between amobarbital plasma concentrations and EEG effect using a new approach based on system analysis principles. This approach models the equilibrium between plasma and effect site without assuming a specific kinetic structure. Assuming linear distribution kinetics between plasma and effect site, the relationship between the two variables may be described by a convolution type of linear operation, involving a conductance function phi(t), which is approximated by a sum of exponentials. Six male Wistar-derived rats received an iv infusion of amobarbital at a rate of 10 mg/kg per min until isoelectric periods of 5 sec or longer appeared on the EEG. Frequent arterial blood samples were obtained and EEG was continuously quantified using aperiodic analysis. The amplitudes in the 2.5-30 Hz frequency band were used as EEG effect measure. The delay between plasma concentrations and EEG effect was best modeled by a biexponential conductance function. The use of a biexponential conductance function resulted in a significant further reduction (41 +/- 10%) in hysteresis when compared to a monoexponential function, indicating that the assumption of simple first-order monoexponential equilibration kinetics is inadequate. The use of a biexponential conductance function also resulted in a significantly different shape of the effect site concentration-EEG effect relationship and hence the estimated pharmacodynamic parameters, when compared with a monoexponential function. This relationship showed a biphasic behavior, with EEG effects being maximal at amobarbital concentrations of 29.6 +/- 1.3 mg/L. At 80.2 +/- 2.0 mg/L the EEG effect was reduced 50% below baseline values. A comparison was made with the equilibration between amobarbital plasma and cerebrospinal fluid (CSF) concentrations. Six male Wistar-derived rats received an iv infusion of amobarbital, 10 mg per min for 15 min. Arterial blood and CSF samples were taken simultaneously at regular intervals. The equilibration between plasma and CSF concentrations was best fitted by a monoexponential conductance function. Significant differences in equilibration profiles of CSF and effect site with the plasma site were observed. To reach 50% equilibrium the effect site requires 2.5 +/- 0.3 min and the CSF 3.5 +/- 0.2 min, to reach 95% the values were, respectively, 90 +/- 27 and 15 +/- 1 min. This suggests that CSF is kinetically distinguishable from the effect site.