AGENT-BASED MODELING OF SOCIAL-POLITICAL SYSTEMS AND PROCESSES: HISTORY OF DEVELOPMENT AND FUTURES FOR PRACTICAL APPLICATION
UDC 32.019.5, 323.2, 324, 327, 329, 519.682
The article provides an overview of agent-based models that reproduce the structure of socio-political systems and dynamics of international processes and socio-political phenomena. The effectiveness and futures of the practical application of agent-based modeling in the field of political knowledge are scientifically proved. An analysis of the conceptual and construction features of agent-based models considered in the scientific review demonstrates the advantages of agent-based modeling for realization applied interdisciplinary projects and research tasks based on the synthesis of several disciplines within the framework of public and political knowledge: political sociology and political psychology, history and archeology, international relations and social culturology. The potentialities and advantages of agent-based modeling in the aspect of its applied meaning for hypothetical testing in the framework of political analysis are shown. A brief history of the practical application of agent-based modeling in the field of political knowledge is presented through a retrospective and structural analysis of models created by prominent political scientists, sociologists and economists, and the impact of their work on the further development of the scientific field is shown. Conclusions regarding the futures for the practical application of simulation in the field of political sciences related with the participation of supercomputer technologies to simulate large-scale socio-political systems, as well as international processes and scenarios that occur on a global scale are presented.
The article has been prepared with the support of the Russian Science Foundation (Grant № 19-18-00240)
Keywords: socio-political systems and processes, elections, political analysis, revolutions, international relations, agent-based modeling.
AUTOMATIC CONTROL OF A CONTINUOUS ROBOT USING THE FABRIK ALGORITHM
V.V. Danilov, D.Y. Kolpashchikov, N.V. Laptev
Nowadays transcatheter minimally invasive surgery has gained popularity due to the shorter rehabilitation period of patients and lower risks during such interventions. However, this type of surgery is manually performed by surgeons and clinicians, which requires a high skill of specialists. Additionally, transcatheter surgery takes a lot of time and thereby increases the risk of medical error. The robotic solutions available today are expensive and inaccessible to most hospitals, clinics and medical centers. A solution of this problem may be the development of a simple automated control system, the usage of which will increase accuracy, repeatability, and reduce the risks related to the human factor. A medical catheter represents a manipulator that can bend in any point of its structure. This structural feature allows these manipulators to work in places with complex geometry, including the anatomical structures of the human body. In this regard, catheters have found their application in many fields, including medicine and industry. However, the control of this type of robots is complicated by the presence of flexible links tending to infinity. For positioning and orientation of continuous robots, forward and inverse kinematics algorithms are used. One of the most promising approaches is the Forward And Backward Reaching Inverse Kinematics algorithm (FABRIK). In this regard, this paper presents a fast and reliable system without feedback and based on the FABRIK algorithm for automatic control of a continuous robot.
Keywords: continuous robot, catheter, automation, positioning, FABRIK.
VERIFICATION OF THE SIMULATION MODEL OF THE ADAPTIVE RATE FULL ECHO ROUTING ALGORITHM DEVELOPED IN THE ANYLOGIC SIMULATION ENVIRONMENT
The mesh topology and point-to-point exchange wireless networks actualize the task of developing algorithms that increase the efficiency of routing these networks. An important feature of these networks is to use the limited battery life devices. The algorithm development taking into account battery level is an urgent task as this factor is one of the important factors affecting the network as a whole. Preview articles the author developed a new Adaptive Rate Full Echo routing algorithm, which is based on the Q-Routing algorithm, using the reinforced machine learning methods. In addition the previous author works a simulation model was presented in the Anylogic simulation system, where the developed algorithm simulation results were performed. The simulation model Verification is a necessary condition for the correctness and reliability of the data received in it. This article presents the results of checking the adequacy of the developed simulation model of the Adaptive Rate Full Echo algorithm by comparing the simulation results with the results of field tests.
Keywords: special network, routes, algorithm, delivery time, simulation, verification of the simulation model, network loss time connectivity.
DEVELOPMENT OF A CONCEPTUAL MODEL OF OPERATIONAL – ANALYTICAL DATA MARTS
A.P. Raevich, B.S. Dobronets
The storages integrated with analytical systems are focused on dimensional data modeling, which provides quick execution of analytical queries, but has significant drawbacks when working with big data. The article proposes an approach to constructing a conceptual model of operational-analytical data marts, which allows combining the concepts of operational data marts and analytical data marts. Operational data marts are information slices of narrowly focused, thematic information, which designed to solve the problem of operational access to big data sources through the consolidation and ranking of information resources in terms of demand. In contrast to operational data marts that are dependent from sources, analytical data marts are considered as independent data sources created by users in order to provide data structuring for the tasks being solved. The paper provides a comparison of approaches to the construction of analytical queries based on linear queries and associative relationships. The results obtained in this work are used in building a BI cluster on the basis of fast design, analytics, development and implementation of business process models which are performed with using prepared operational-analytical data marts.
Keywords: business intelligence systems, operational-analytical data marts, associative data model.
DYNAMIC MODELLING OF MANIPULATOR USING ADAPTIVE NEURO
FUZZY INFERENCE SYSTEM
UDC 004.896, 004.942
Thu Rain, Yan Naing Soe
The dynamic modelling of manipulator is essential for the design, simulation and control system of manipulator. Researchers have proposed different techniques for dynamic modelling of manipulators. The commonly used methods to formulate the dynamic equations of motion for manipulators are Newton-Euler and Lagrange-Euler methods. Because of these methods are numerical recursive methods, they are computationally expensive and not suitable to use directly in real time applications. In this paper, we proposed the adaptive neuro fuzzy inference system-based method to construct the input-output mapping for the dynamic equations of motion of a 5 degree-of-freedom manipulator. The dynamic model of the manipulator is computed using Newton-Euler dynamic formulation to create the training data sets for the adaptive neuro fuzzy inference system. The proposed method is tested in generating the required torques for a point-to point trajectory. Results show that the proposed method can perform within shorter operational time and its performance is comparable to Newton-Euler method. The proposed method can be used for the rigid-body manipulators whose dynamical characteristics are known.
Keywords: dynamic modelling, Newton-Euler method, adaptive neuro fuzzy inference system, manipulator dynamics.