Forecasting Catastrophic Events in Technology, Nature and Medicine

This book presents a methodology for forecasting events and phenomena occurring in technology and natural environments. The methodology is based on forecasting the individual state of the control object, which is carried out based on the analysis of the trend behavior of the controlled parameter (symptom of the disease). The methodology helps determining the time of the onset of a destructive earthquake, its strength and the coordinates of the epicentre, predicting the time of the descent of glaciers and landslides long before the event. In medicine, the methodology predicts the severity of a disease and forecast of its aggravation.

Examines the methodology for predicting rare events and phenomena

Helps to determine the actual moment of the onset of technological disasters

Provides a comprehensive presentation of information from data collection to their assessment

Autorentext

Anton Panda is Professor at FMT TU KoSice as well as auditor of quality system management at Technical University in KoSice. He deals with production technologies, experimental methods and bearing production. He is a member of the Polish Academy of Sciences.

Volodymyr Nahornyi is a Senior Lecturer in the Department of Computer Science, Section of Information Technology of Design in Sumy State University. He develops courses such as CAD/CAM systems integration, mobile programming, methods and tools for processing visual information, and technologies for creating software products.

Inhalt

List of used symbols and abbreviations

1

Introduction

2

Analysis of current state of forecasting objects and phenomena

2.1 Problem statement

2.2 Current state of the problem

3 Specification of problems solutions 3.1

General statements

3.2

Forecasting tool

3.3

Time series forecasting 3.4 Forecast model development

3.4.1

Development of the analytical expression of a forecast model..

3.4.2

Instability compensation of forecasting mechanical systems resource

3.4.3 Evaluation of reliability of the mechanical systems resource forecast 3.4.3.1

Correlation method

3.4.3.2

Evaluation of statistical significance of a forecast model

4

Application of the developed forecasting methodology in various spheres of human activity 4.1 Resource forecasting in technology

4.1.1

State of the forecasting problem in technology

4. 2 Forecasting the resource of large-scale products using a centrifugal pump as an example 4.3

Forecasting the resource of small-scale products using a hydro turbine as an example

4.3.1

Derivation of the analytical expression for the "membership function"

4.3.2

Determination of normative boundaries of the linguistic variable a COND

4.3.3

Evaluation of criticality degree of the turbine condition

4.4

Forecasting individual resource of the aircraft engine

4.5 Forecasting individual resource of the cutting tool 4.5.1

General statement

4.5.2

Monitoring the state of the cutting tool according to the sound generated by the cutting process

4.5.3

Adaptive control of cutting conditions based on individual resource forecast of the cutting tool

4.5.3.1

General statements

4.5.3.2

Algorithm of adaptive control of the cutting process

4.5.3.3

Hardware and software system of the cutting process adaptive control

4.6

Forecasting in medicine

4.6.1

Subject of research and research procedure

4.6.2

Results of research and their assessment

4.6.2.1

Short-term forecasting

4.6.2.2

Long-term forecasting

4.7

Earthquake prediction

4.7.1

roblem statement

4.7.2

Initial data

4.7.3

Methodology for preparing initial data for forecasting 4.7.4 Forecasting Method

4.7.4.1

The forecasting of the moment of the occurrence earthquake and its epicenter's coordinates

4.7.4.2

Earthquake strength forecasting

4.7.5

Results 4.7.5.1 The verification results of forecasting methods

4.7.5.1.1

Earthquake forecast verification near Hokkaido

4.7.5.1.1.1

Verification earthquake date prediction

4.7.5.1.1.2

Verification prediction of the earthquake epicenter coordinates

4.7.5.1.1.3

Verification prediction of the earthquake strength

4.7.5.1.2

Earthquake prediction verification in the area of Fukushima

4.7.5.1.2.1

Verification earthquake date prediction

4.7.5.1.2.2

Verification prediction of the earthquake epicenter coordinates

4.7.5.1.2.3

Verification prediction of the earthquake strength

4.7.6

The approbation results of the prediction method

4.7.6.1

Earthquake predicting time

4.7.6.2

Prediction of the earthquake epicenter coordinates

4.7.6.3 Predicting the strength of a ripening earthquake 5

Conclusion 6 References