The scientific work describes the algorithms for processing the multispectral water coastal imagery from satellite sensing data with the aim of identifying the phytoplankton population of a spotted structure: determining the contour, distributing color gradation and as a result - determining the concentration of phytoplankton distribution inside the zones and mass centers. Such characteristics let determine the speed of changing contours spots and their concentration, the mass center shift as a consequence of the water masses movement and the processes of phytoplankton growing and dying. All these may be done on the base of the processed image series of the same water area over different time (different dates). The combination of LBP and neural network methods are observed as algorithms for image processing and the results of computer experiments are presented.
The purpose of the study covers theoretical analysis and mathematical modeling of alternating current measuring transducers based on magnetodielectric cores for automation systems in oil refineries. The paper describes the analytical study of the magnetization curve, creation of the equivalent circuit and thus obtained mathematical model of a transducer, numerical study of the proposed transducer, as well as the contrastive analysis of transducers currently used to measure the current.
The paper presents the solution of task on the minimum cost data flow in static and dynamic setting based on evolutionary algorithms. The distinctive feature of the algorithm is the use of joint evolution, choice of evolution models (use of micro-, macro- and metaevolutions), adjustment to external environment, hierarchical management of genetic and evolutionary search, local search of solutions and application of all modified genetic operators based on evolutionary strategy and search methods. The paper illustrates the example of task on the recommended data flow and a method of adjusting the data transfer process to recommended parameters.
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