Application Of Genetic Models Research Articles

Model for generating data from navigation sensors for assessing the spatial position of objects

When selecting or developing new algorithms for assessing the spatial position of objects based on data from consumer navigation equipment (CNA) of global navigation satellite systems (GNSS) and data from inertial MEMS modules, the task of generating test model input data that meets certain conditions arises. Such conditions include, for example, the requirements for limited time increments of elements of spatio-temporal trajectories and ease of formation of their characteristic sections. The characteristic sections of spatio-temporal trajectories can be sections of a stationary position – sections of “Rest” or sections of rectilinear movement. The importance of forming these areas is due to the need to test the potential capabilities of compared or developed algorithms for assessing the spatial position of objects to ensure an improvement in their accuracy characteristics in the presence of such areas in various conditions. A data generation model is proposed for comparing algorithms for estimating the spatial position of objects, which ensures that the time increments of elements of spatio-temporal trajectories are limited in time and the simple formation of their characteristic sections is met. The model is based on the selection of a set of specified parameters that would allow, on the one hand, to form characteristic sections of spatio-temporal trajectories, and, on the other hand, to obtain model output data of NAP GNSS and inertial MEMS modules. The selected set of specified model parameters is determined through a set of analytically specified functions with sequential calculation of their parameters, which is much simpler compared to traditional approaches that involve solving boundary value problems of optimal control with restrictions on the type of control functions or the construction and application of genetic models and algorithms. The use of the developed model makes it possible to generate test model input data for the selection or development of new algorithms for assessing the spatial position of objects, implemented in devices that include CNA of GNSS and inertial MEMS modules and produce results both in real time and in delayed time. The effectiveness of the proposed solution is confirmed by the criterion of suitability under the considered conditions.

Benchmarking model based on genetic mechanisms in project management

The application of knowledge accumulated in the fundamental mechanisms of wildlife is a global trend in the development of project ma-nagement. This trend requires additional research on the development of exis-ting methodologies, knowledge systems, and genetic mechanisms of project and program management. Convergence (oncoming) of knowledge systems of various branches and benchmarking are mechanisms that transfer knowledge and best practice between domains. The authors proposed a classification of convergence mechanisms for further transfer of knowledge − benchmarking between different domains. Four principles of constructing and developing methodologies for project management based on transfer of knowledge and best practice are formulated. These are the principles of the necessary diversity (Ashby), the coherence of methodologies, convergence, integration and harmonization, the focus on the result and product. They are given basic definitions and application of genetic models in creation of methodologies of project management. The model of application of genetic mechanisms of the matrix model of knowledge (mRNA), models and methods of project management is proposed. The benchmarking model of genetic mechanisms and information in project management is defined as a sequence of matrix RNA processing steps. The following steps that are described in the interpretation of project management methodologies are initiation, transcription, processing and transport, translation, splicing, modification, product formation, and termination. Considered approach has a significant impact on the development of the competence of project managers, taking into account the creation and production of fundamentally new knowledge and management mechanisms.