Improvement of Methods for the Study of Population Health Using Algebraic Models of Constructive Logic

2015 ◽  
Vol 22 (3) ◽  
pp. 8-14 ◽  
Author(s):  
Хромушин ◽  
Viktor Khromushin ◽  
Китанина ◽  
K. Kitanina ◽  
Аверьянова ◽  
...  
Keyword(s):  
Expert Systems ◽  
Mathematical Models ◽  
Population Health ◽  
Algebraic Model ◽  
Compact Representation ◽  
Constructive Logic ◽  
Algebraic Models ◽  
Source Data ◽  
Support Of Research ◽  
The Mathematical Model

Algebraic model of constructive logic is developed in Russia and is used for many years in medicine and biology for multivariate analysis and for building expert systems. In the process of improving the algorithm of the algebraic model of constructive logic and software, the methods of the study of population health with the use of these models are improved. The tasks of providing a compact representation of the mathematical model are solved, the version of algorithms and programs with different reaction to incomplete source data is created, an analytical and methodological support of research is developed. The article presents the results of practical work to improve the working methods of the study of population health. It covers the issues of verification of source data, an obtainment a compact mathematical models, the valuation and completeness of the source data, the main highlight of the resulting components, the exclusion of inconsistencies in the source data, the absorption of the analyzed factors, the principles of the analysis of the factors in mathematical models and principles of construction of expert systems. The authors showed that the classical and modernized versions of the algebraic model of constructive logic have their applications and are not exclusive of each other. This article also provides recommendations and explanations that facilitate the realization of analytical studies using algebraic models of constructive logic.

Identification Method of Restrictions of Treatment Method Using Algebraic Model of Constructive Logic on the Example of Hyperbaric Oxygen Therapy in Oncological Pathology

2015 ◽  
Vol 22 (3) ◽  
pp. 79-86 ◽  
Author(s):  
Дзасохов ◽  
Aleksey Dzasokhov ◽  
Хромушин ◽  
Viktor Khromushin ◽  
Китанина ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Hyperbaric Oxygen ◽  
Hyperbaric Oxygen Therapy ◽  
Oxygen Therapy ◽  
Algebraic Model ◽  
Total Power ◽  
Constructive Logic ◽  
Number Of Patients ◽  
The Mathematical Model ◽  
Oncological Pathology

Mathematical device of algebraic model of constructive logic has been used for many years for multivariate analysis in medicine and biology most often to identify causal relationships. This mathematical apparatus can be used for more complex analysis schemes for the purpose of determining the contingent of patients who require this method of treatment. The proposed method is a two-step analysis using algebraic model of constructive logic with different specified purposes and subsequent analysis of the resulting final components of the mathematical model. As a result, it is possible to identify restrictions and to quantify the number of patients who need to analyzed method of treatment. The proposed method is explained by an analytical study of hyperbaric oxygen therapy in oncological pathology. Analysis of the results revealed 7,87-39,35% of patients requiring hyperbaric oxygen therapy. The authors revealed the restrictions presented resulting final components of the mathematical model in the form of limits of detection of the combined factors. The equity analysis of values of the resulting components of the mathematical model is associated with the need to calculate the maximum possible total power of the resulting components of the mathematical model, used in expert systems.

Optimization of the Algebraic Model of Constructive Logic

10.12737/2691 ◽  
2014 ◽  
Vol 8 (1) ◽  
pp. 1-11 ◽  
Author(s):  
Хромушин ◽  
Oleg Khromushin ◽  
Хромушин ◽  
Viktor Khromushin ◽  
Дзасохов ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Oxygen Therapy ◽  
Model Identification ◽  
Algebraic Model ◽  
Constructive Logic ◽  
Top Down ◽  
Number Of Components ◽  
Depth Analysis ◽  
The Mathematical Model ◽  
Oncological Pathology

The authors proposed and evaluated options of optimization of the algebraic model of constructive logic, designed to construct multichannel non-linear mathematical model often used in Russia in the in-depth analysis in medicine and biology. In the basis of optimization of this model are procedures for finding duplicate cases (rows base), relevant to the achievement of goals, and excluding those resulting components that are duplicated other cases the resulting components. Procedures for reviewing the results of the components of a top-down or bottom-up and comparing the numbers corresponding to achievement of objectives are the basis of optimization. If all the numbers viewing the resulting component will be present in other watched the resulting components, then it is removed as redundant. As a result of identifying and eliminating redundant coatings target lines are reducing the number of resulting parts. Reduction of number of resulting components is achieved by identifying and eliminating redundant coatings target lines. The results of two variants of optimization of mathematical model are shown on the example of the mathematical model identification features of the method of oxygen therapy in the treatment of oncological pathology. The authors suggested the possibility of practical use of various optimization algorithms to choose model with a minimal number of components of the resulting/

Formation of analytical data for multivariate analysis using algebraic model of constructive logic

2015 ◽  
pp. 0-0 ◽  
Author(s):  
S. Fedorov ◽  
K. Kitanina ◽  
V. Khromushin ◽  
O. Khromushin
Keyword(s):  
Mathematical Model ◽  
Multivariate Analysis ◽  
Analytical Data ◽  
Algebraic Model ◽  
Constructive Logic ◽  
Optimum Yield ◽  
Joint Influence ◽  
Source Data ◽  
Age Cohort ◽  
Input Table

Mathematical device of algebraic model of constructive logic has been used for many years for multivariate analysis in medicine and biology. The resulting mathematical model is represented by a set of output components in the form of factors indicating the detection restrictions, which are united by the sign of con-junction (indicating joint influence). Each resulting component is characterized by a capacity, which is the es-sence of the number of rows in the table with the same factors and their intervals of definition. These capacities characterize the degree of influence of the resulting component on the overall result. The input table must not contain contradictions (when the goal is achieved and not achieved when the same values of the factors). For this purpose, the computer program provides for an exception to those target lines, which coincide with non-target rows. However, this is not always acceptable in cases of a large number of matching target lines and unit numbers of non-target rows or vice versa, because a large number of cases is excluded because of a single non-target rows or single target lines. These contradictions arise, primarily, due to the probabilistic nature of the cases. This is clearly seen in the monitoring of mortality. In this article the authors propose three ways optimum yield conflicting source data, based on the excess multiplicity of frequencies matching target and non-target cases and estimates of confidence intervals. The pro-posed methods are examined by analyzing data on deaths of persons aged 18 years and older, residents of the Tula region for 2007-2014 (total 208269 cases). An age cohort 45-54 years is a goal of study. The application of methods of optimum yield conflicting source data is a necessity, which not only im-proves the mathematical model, but, in some cases, is the only way to perform multivariate analysis. All pro-posed methods have their own scope of use, depending on the circumstances.

Improvement of the Algorithm of Algebraic Constructive Logic Model

2015 ◽  
Vol 22 (2) ◽  
pp. 11-19 ◽  
Author(s):  
Хромушин ◽  
Oleg Khromushin ◽  
Хромушин ◽  
Viktor Khromushin ◽  
Китанина ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Multivariate Analysis ◽  
Final Stage ◽  
Detection Limits ◽  
Algebraic Model ◽  
Logic Model ◽  
Constructive Logic ◽  
Partial Overlap ◽  
The Mathematical Model ◽  
Better Than

For many years, algebraic constructive logic model is used for multivariate analysis in medicine and biology. The classic version of this model includes the exclusion of contradictory accounts, i.e. when the target is achieved and not achieved in the presence of the same values of the factors. In this case, the lines as appropriate to achieving target, and its failure are removed, including significant proportions. Another feature of this algorithm is the partial overlap of the intervals to determine the factors resulting in components in achieving a target and not achieving despite the exclusion of contradictory accounts. The authors explain this by the fact that the classical algorithm generates the detection limits of the factors in resulting components with some capture values that are related to the lines of not achieving the target (up to inappropriate values). To some extent this reduces the accuracy of the mathematical model. A further feature of the algorithm is the necessary to optimize mathematical model by excluding re-coating lines. This is acceptable, but not optimal. This requires additional procedures at the final stage of formation of the mathematical model. The proposed version of the algebraic model of constructive logic allows to eliminating the above drawbacks. This is achieved the measure of approximation and a way of combining the cases in the resulting components. The proposed algorithm was tested using specially designed software that allows to exclude controversial cases and to form a mathematical model. Testing showed that the proposed algorithm is better than the classic version and meets the objectives of multivariate analysis in medicine and biology.

scholarly journals Modelling the COVID-19 pandemic in context: an international participatory approach

2020 ◽  
Vol 5 (12) ◽  
pp. e003126
Author(s):  
Ricardo Aguas ◽  
Lisa White ◽  
Nathaniel Hupert ◽  
Rima Shretta ◽  
Wirichada Pan-Ngum ◽  
...  
Keyword(s):  
Mathematical Models ◽  
Low Income ◽  
Scientific Evidence ◽  
Participatory Approach ◽  
Middle Income ◽  
Middle Income Countries ◽  
Containment Measures ◽  
History Of ◽  
High Degree ◽  
The Mathematical Model

The SARS-CoV-2 pandemic has had an unprecedented impact on multiple levels of society. Not only has the pandemic completely overwhelmed some health systems but it has also changed how scientific evidence is shared and increased the pace at which such evidence is published and consumed, by scientists, policymakers and the wider public. More significantly, the pandemic has created tremendous challenges for decision-makers, who have had to implement highly disruptive containment measures with very little empirical scientific evidence to support their decision-making process. Given this lack of data, predictive mathematical models have played an increasingly prominent role. In high-income countries, there is a long-standing history of established research groups advising policymakers, whereas a general lack of translational capacity has meant that mathematical models frequently remain inaccessible to policymakers in low-income and middle-income countries. Here, we describe a participatory approach to modelling that aims to circumvent this gap. Our approach involved the creation of an international group of infectious disease modellers and other public health experts, which culminated in the establishment of the COVID-19 Modelling (CoMo) Consortium. Here, we describe how the consortium was formed, the way it functions, the mathematical model used and, crucially, the high degree of engagement fostered between CoMo Consortium members and their respective local policymakers and ministries of health.

ASSESSMENT OF THE DEPENDENCE OF THE AVERAGE LIFE EXPECTANCY OF THE POPULATION RESIDING IN THE TULA REGION IN THE AREAS WITH A HIGH CONTENT OF HEA VYMETALS IN THE SOIL

2021 ◽  
Vol 1 (1) ◽  
pp. 53-63
Author(s):  
KHROMUSHIN V.A. ◽  
◽  
VOLKOV A.V. ◽  
KHADARTSEV A.A. ◽  
◽  
...  
Keyword(s):  
Heavy Metals ◽  
Life Expectancy ◽  
Respiratory Diseases ◽  
Causes Of Death ◽  
Algebraic Model ◽  
Constructive Logic ◽  
Average Life ◽  
Average Life Expectancy ◽  
Lead Zinc ◽  
Regional Mortality

The article presents the relevance of the problem, defines the research purpose: to compare the average life expectancy of the population in the areas of the Tula region with different contents of heavy metals in the class of causes of death “Respiratory diseases ”. The authors used the data of the regional mortality register, the results of analyzes of the content of heavy metals (copper, lead, zinc, nickel) in the soil by atomic absorption spectroscopy, and the calculation of the average life expectancy by the algebraic model of constructive logic. The results indicate a decrease in average life expectancy due to the presence of heavy metals in the soil, but the average life expectancy in both contaminated and non-contaminated areas is gradually increasing.

scholarly journals NECESSITY TO IMPROVE THE MATHEMATICAL MODEL OF FREIGHT CARS TO STUDY CASES OF ITS DERAILMENTS

2020 ◽  
pp. 442-451
Author(s):  
А.V. Batig ◽  
A. Ya. Kuzyshyn
Keyword(s):  
Mathematical Model ◽  
Mathematical Models ◽  
Computer Experiment ◽  
Rolling Stock ◽  
Software Systems ◽  
Freight Car ◽  
The Stability ◽  
The Many ◽  
The Impact ◽  
The Mathematical Model

One of the most important problems that pose a serious threat to the functioning of railways is the problem of freight cars derailment. However, according to statistics, the number of cases of the derailments of freight cars in trains annually grows. Тo prevent such cases, the necessary preventive measures are developed, and to study the causes of their occurrence, a significant number of mathematical models, programs and software systems created by leading domestic and foreign scientists. Studies of such mathematical models by the authors of this work have led to the conclusion that they are not sufficiently detailed to the extent that it is necessary for analyze the reasons of its derailment. At the same time, an analysis of the causes of the rolling stock derailments on the railways of Ukraine over the past five years showed that in about 20 % of cases they are obvious, and in 7 % of cases they are not obvious and implicitly expressed. The study of such cases of rolling stock derailment during an official investigation by the railway and during forensic railway transport expertises requires the use of an improved mathematical model of a freight car, which would allow a quantitative assessment of the impact of its parameters and rail track on the conditions of railway accidents. Therefore, taking into account the main reasons that caused the occurrence of such railroad accidents over the last five years on the railways of Ukraine, the article selected the main directions for improving the mathematical model of a freight car, allowing to cover all the many factors (explicit and hidden) and identify the most significant ones regarding the circumstances of the derailment rolling stock off the track, established on the basis of a computer experiment. It is proposed in the mathematical model of a freight car to take into account the guiding force, the value of which is one of the main indicators of the stability of the rolling stock. The authors of the article noted that not taking into account the influence of the guiding forces on the dynamics of the freight car can lead to an erroneous determination of the reasons for the rolling stock derailment or even to the impossibility of establishing them.

scholarly journals Analysis on Present Mathematical Model for Predicting the Crop Production

2020 ◽  
Vol 9 (12) ◽  
pp. 168-170
Keyword(s):  
Mathematical Model ◽  
Mathematical Models ◽  
Real World ◽  
Crop Production ◽  
Ghg Emissions ◽  
Data Set ◽  
Factors Affecting ◽  
The Government ◽  
The Mathematical Model ◽  
Government Website

India is a worldwide agriculture business powerhouse. Future of agriculture-based products depends on the crop production. A mathematical model might be characterized as a lot of equations that speak to the conduct of a framework. By using mathematical model in agriculture field, we can predict the production of crop in particular area. There are various factors affecting crops such as Rainfall, GHG Emissions, Temperature, Urbanization, climate, humidity etc. A mathematical model is a simplified representation of a real-world system. It forms the system using mathematical principles in the form of a condition or a set of conditions. Suppose we need to increase the crop production, at that time the mathematical model plays a major role and our work can be easier, more significant by using the mathematical model. Through the mathematical model we predict the crop production in upcoming years. .AI, ML, IOT play a major role to predict the future of agriculture, but without mathematical models it is not possible to predict crop production accurately. To solve the real-world agriculture problem, mathematical models play a major role for accurate results. Correlation Analysis, Multiple Regression analysis and fuzzy logic simulation standards have been utilized for building a grain production benefit depending model from crop production. Prediction of crop is beneficiary to the farmer to analyze the crop management. By using the present agriculture data set which is available on the government website, we can build a mathematical model.

BASIC MATHEMATICAL MODELS AND AN APPROXIMATE METHOD OF FILTRATION THEORY

2021 ◽  
pp. 25-31
Author(s):  
Alla A. Mussina
Keyword(s):  
Mathematical Model ◽  
Porous Media ◽  
Mathematical Models ◽  
Heterogeneous Porous Media ◽  
Effective Management ◽  
Filtration Theory ◽  
New Device ◽  
Scientific Papers ◽  
The Mathematical Model ◽  
Inhomogeneous Liquids

The article defines the basic concepts of filtration theory and provides an overview of the existing mathematical models of inhomogeneous liquids in porous media. The paper considers the Stefan problem. The number of scientific papers devoted to the study of porous structures has recently increased. This is primarily due to the fact that the prob-lems of oil and uranium production have been identified, and the solution of environmental problems is overdue. Therefore, a new device is needed to develop models of liquid filtration. With the advent and development of computer technology, it has become easier to solve problems that require numerical methods for their solution. Understanding the movement of fluids and the mechanism of dissolution of rocks under the action of acids in heterogeneous porous media is of great importance for the extraction and production of oil and the effective management of these processes. The article examines the mathematical model of the theory of isothermal filtration. Possible variants of the solva-bility of the model are shown. The research scheme consists of the output of a mathematical model, the formulation of the problem, one variant of the solution of the problem, the algorithm of the numerical method of solving the problem.

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