2 research outputs found
Π ΠΎΠ·ΡΠΎΠ±ΠΊΠ° Π΄Π΅ΡΠΊΡΠΈΠΏΡΠΈΠ²Π½ΠΎΡ Π±ΡΠ½Π°ΡΠ½ΠΎΡ ΠΌΠΎΠ΄Π΅Π»Ρ ΡΠ° ΡΡ Π·Π°ΡΡΠΎΡΡΠ²Π°Π½Π½Ρ Π΄Π»Ρ ΡΠ΄Π΅Π½ΡΠΈΡΡΠΊΠ°ΡΡΡ ΡΠΊΡΠΏΡΠ΅Π½Ρ ΡΠΎΠΊΡΠΈΡΠ½ΠΈΡ ΡΡΠ°Π½ΠΎΠ±Π°ΠΊΡΠ΅ΡΡΠΉ
In the paper, a descriptive model of system dynamics for binary data is presented. Binary or dichotomous data are widely spread across various fields of research β in decision making and data mining, marketing, solving of many natural, social and technical problems. The initial data for building the model is a set of states of an autonomous dynamical system with components taking binary values. At the same time, the time order of the states is permissible. The following objectives were stated: to identify the relationships between the components of the system defining its dynamics; on the basis of the identified dynamics, to recover the true order of the system states; to apply the developed model to the problem of visual identification of cyanobacteria in water areas using digital photography.To solve the problem, we used a mathematical model that enables to describe the relationships between components and transitions between the system states at a simple-for-understanding level. The principle of parsimony underlies the model. According to this principle, the most appropriate model is described by the simplest relations in the sense defined in the work.As the case study, the problem of recognizing clumps of cyanobacteria from digital satellite imagery was considered. This is a complex, practically important problem that does not have a satisfactory experimental and theoretical solution at the moment. Applying system approaches to the measured colorimetric parameters of digital photography, we developed the index for identification of such clumps. This index uses the parameters of the digital RGB model of (various parts of) an image and allows us to reveal clumps of cyanobacteria on digital images obtained by aerospace methods. Additionally, digital photography can be performed in the conditions of insufficient visibility (due to precipitation, fog, and other factors), for imitation of which in the case study the original image was distorted by the digital noise.The studied model can find useful applications in the areas requiring binary dynamical data insightsΠΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½Π° Π΄Π΅ΡΠΊΡΠΈΠΏΡΠΈΠ²Π½Π°Ρ Π΄ΠΈΠ½Π°ΠΌΠΈΡΠ΅ΡΠΊΠ°Ρ ΠΌΠΎΠ΄Π΅Π»Ρ Π±ΠΈΠ½Π°ΡΠ½ΡΡ
Π΄Π°Π½Π½ΡΡ
, ΠΏΠΎΠ·Π²ΠΎΠ»ΡΡΡΠ°Ρ ΠΏΠΎ ΠΈΡΡ
ΠΎΠ΄Π½ΡΠΌ Π½Π°Π±Π»ΡΠ΄Π΅Π½ΠΈΡΠΌ Ρ Π½Π°ΡΡΡΠ΅Π½Π½ΡΠΌ Π²ΡΠ΅ΠΌΠ΅Π½Π½ΡΠΌ ΠΏΠΎΡΡΠ΄ΠΊΠΎΠΌ Π²ΠΎΡΡΡΠ°Π½ΠΎΠ²ΠΈΡΡ ΠΈΡΡ
ΠΎΠ΄Π½ΡΠΉ ΠΏΠΎΡΡΠ΄ΠΎΠΊ Π½Π° ΠΎΡΠ½ΠΎΠ²Π°Π½ΠΈΠΈ ΠΏΡΠΈΠ½ΡΠΈΠΏΠ° ΠΏΠ°ΡΡΠΈΠΌΠΎΠ½ΠΈΠΈ. ΠΠΎΠ΄Π΅Π»Ρ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½Π° Π΄Π»Ρ Π½Π°Ρ
ΠΎΠΆΠ΄Π΅Π½ΠΈΡ ΡΠΈΡΡΠ΅ΠΌΠ½ΡΡ
ΠΊΠΎΠ»ΠΎΡΠΈΠΌΠ΅ΡΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΠΎΠ², ΠΈΡΠΏΠΎΠ»ΡΠ·ΡΠ΅ΠΌΡΡ
Π΄Π»Ρ ΠΎΠ±ΡΠ°Π±ΠΎΡΠΊΠΈ ΠΈΠ·ΠΎΠ±ΡΠ°ΠΆΠ΅Π½ΠΈΠΉ, ΡΠΊΠΎΠΏΠ»Π΅Π½ΠΈΠΉ ΡΠΎΠΊΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΡΠΈΠ°Π½ΠΎΠ±Π°ΠΊΡΠ΅ΡΠΈΠΉ Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ Π°Π½Π°Π»ΠΈΠ·Π° ΠΊΠΎΠΌΠΏΠΎΠ½Π΅Π½ΡΠΎΠ² RGB-ΠΌΠΎΠ΄Π΅Π»ΠΈ ΡΠΈΡΡΠΎΠ²ΠΎΠΉ ΡΠΎΡΠΎΠ³ΡΠ°ΡΠΈΠΈΠΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½Π° Π΄Π΅ΡΠΊΡΠΈΠΏΡΠΈΠ²Π½Π° Π΄ΠΈΠ½Π°ΠΌΡΡΠ½Π° ΠΌΠΎΠ΄Π΅Π»Ρ Π±ΡΠ½Π°ΡΠ½ΠΈΡ
Π΄Π°Π½ΠΈΡ
, ΡΠΎ Π΄ΠΎΠ·Π²ΠΎΠ»ΡΡ ΠΏΠΎ Π²ΠΈΡ
ΡΠ΄Π½ΠΈΠΌ ΡΠΏΠΎΡΡΠ΅ΡΠ΅ΠΆΠ΅Π½Π½ΡΠΌΠΈ Π· ΠΏΠΎΡΡΡΠ΅Π½ΠΈΠΌ ΡΠ°ΡΠΎΠ²ΠΈΠΌ ΠΏΠΎΡΡΠ΄ΠΊΠΎΠΌ Π²ΡΠ΄Π½ΠΎΠ²ΠΈΡΠΈ Π²ΠΈΡ
ΡΠ΄Π½ΠΈΠΉ ΠΏΠΎΡΡΠ΄ΠΎΠΊ Π½Π° ΠΏΡΠ΄ΡΡΠ°Π²Ρ ΠΏΡΠΈΠ½ΡΠΈΠΏΡ ΠΏΠ°ΡΡΠΈΠΌΠΎΠ½ΡΡ. ΠΠΎΠ΄Π΅Π»Ρ Π·Π°ΡΡΠΎΡΠΎΠ²Π°Π½Π° Π΄Π»Ρ Π·Π½Π°Ρ
ΠΎΠ΄ΠΆΠ΅Π½Π½Ρ ΡΠΈΡΡΠ΅ΠΌΠ½ΠΈΡ
ΠΊΠΎΠ»ΠΎΡΠΈΠΌΠ΅ΡΡΠΈΡΠ½ΠΈΡ
ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΡΠ², Π²ΠΈΠΊΠΎΡΠΈΡΡΠΎΠ²ΡΠ²Π°Π½ΠΈΡ
Π΄Π»Ρ ΠΎΠ±ΡΠΎΠ±ΠΊΠΈ Π·ΠΎΠ±ΡΠ°ΠΆΠ΅Π½Ρ ΡΠΊΡΠΏΡΠ΅Π½Ρ ΡΠΎΠΊΡΠΈΡΠ½ΠΈΡ
ΡΡΠ°Π½ΠΎΠ±Π°ΠΊΡΠ΅ΡΡΠΉ Π½Π° ΠΎΡΠ½ΠΎΠ²Ρ Π°Π½Π°Π»ΡΠ·Ρ ΠΊΠΎΠΌΠΏΠΎΠ½Π΅Π½ΡΡΠ² RGB-ΠΌΠΎΠ΄Π΅Π»Ρ ΡΠΈΡΡΠΎΠ²ΠΎΡ ΡΠΎΡΠΎΠ³ΡΠ°ΡΡ