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EN
The paper presents statistical research results regarding the occurrence of which dangerous aviation events in 1919-2018. The source of the information about the events was the AviationSafetyNetwork website. With the use of Excel 2016 and Statistica v. 12 computer programs, five-time intervals were identified in which hazardous aviation incidents took place.Characterizing the distribution of these events in all periods, due to the technological advancement and capabilities of airplanes, the distribution of dangerous events in the last three periods was compared. The following tests were used to verify the statistical hypotheses: , Shapiro-Wilk, Brown-Forsythe, Kruskal-Wallis. When choosing the appropriate test, the following factors were taken into account: the type of measurement scale, the dependence/independence of samples, and their number. The standard significance level was assumed to be α = 0.05. The consequences and repeatability of aviation events in the identified time intervals were analyzed. The research questions that were posed were the following: in which seasons of the year, months, days of the month, and days of the week did the most dangerous events deaths occur? How often did dangerous events take place? Was the distribution of events similar in the identified periods? The results of the conducted research allowed to identify five periods in which hazardous events took place and demonstrate that in particular periods the distribution of hazardous air events in subsequent seasons, months, and days of the week was not the same.
2
Content available remote Civil aviation flight safety: pilot properties soft computing
EN
Commercial competition leads to aviation accidents. It forces airlines to reduce the cost of purchasing, leasing, and maintenance of aircraft. The air carrier saves on professional training of personnel, on an arbitrary increase in the workload standards, on the use of flight crews with minimal and untenable experience in chronic fatigue conditions. Theory and methods of the characteristics of specialists remain uncertain. Statistical data and expertise may be piecewise-defined, inaccurate, and inconsistent. It is necessary to establish indicators and values of acceptable accuracy using fuzzy measures to calculate the dependability of flight crews based on workload and experience. It is proposed soft computing, statistical and expert methods for calculating the properties of a person and social groups in the management of dangerous professions. It makes it possible to calculate the dependability of the pilot properties with an assessment of flight safety risk levels for making management decisions. The results of the work are new standards for the workload of flight crews recommended for civil aviation. Results are obtained in qualitative methods for calculating efficiency, security, and risk states in the management of organizational objects as airlines. Indicators for air transport risk management standards and decision-making tools were obtained. Calculated indicators of pilot dependability values are a model for developing the airline's strategy, for quantitative assessments of flight specialists, standardizing professional activities, and managing training costs.
EN
According to the statistics the human factor is one of the main causes of the aviation accidents. The authors of the article explain what human factor means and describe the well known safety models as SHELL model, 5-M model and Reason’s model. Afterwards they try to analyze the Tenerife aviation accident by use of SHELL model.
PL
Według danych statystycznych, czynnik ludzki jest jedną z głównych przyczyn wypadków lotniczych. Autorki artykułu wyjaśniają, co oznacza „czynnik ludzki” i opisują dobrze znane modele bezpieczeństwa, takie jak: model SHELL, model 5-M i model Reasona. Następnie próbują zanalizować wypadek na Teneryfie przy pomocy modelu SHELL.
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