Abstract. The paper addresses classification and formal definition of neurocomputer systems for robotic complexes, based on the types of associations among their elements. We suggest analytical expressions for performance evaluation in neural computer information processing, aimed at development of methods, algorithms and software that optimize such systems.
Currently, people in different media sources is actively discussing the negative effects of computers and robotic systems that can affect various aspects of people's lives, significantly limiting it. This article describes the terms: "machine learning", "artificial intelligence", "neural networks"; some prerequisites and possibilities of using artificial intelligence systems in various areas of society are considered. The detailed analysis of the necessary computing devices for solving the problems of digital transformation of organizations is presented. Concrete examples of the use of artificial intelligence systems in modern sectors of the economy, at enterprises and in institutions. This paper gives examples of the use of decision support systems based on artificial intelligence technologies in various fields. As possible computing devices for accelerating neural network operations, graphics cards, specialized neural network accelerators, and neuromorphic processors are considered. The article notes that the architecture of neural network computers is more promising than the classical one Neumann architectures currently used due to the possibility of highly parallel operation and very low energy consumption in the process of solving problems. As a result of the analysis of the technologies used, the authors substantiate the conclusion that a neural network is software and ideally suited for solving the issues of digital modernization of an organization. A neural network, learning from specific examples given by humans, is able clearly fulfill the tasks set before it and, if necessary, make decisions independently. With the introduction of artificial intelligence systems in the organization, there will be significant savings in material and labor resources as a result of reduced decisionmaking time.
The possibility of using digital technology in the utilization of the non-cereal part of the crop as fertilizer is being considered. The algorithm of the analytical unit of the machine for utilization of the non-cereal part of the crop (AdU NCHU) as a fertilizer is presented, on the basis of which a software module was developed. This machine allows one to perform a set of operations in one pass, converting plant residues lying in the swath into organic fertilizer. The performance of the analytical unit and software in the field was assessed. Based on the obtained data, models of straw rolls were built, which were compared and the total deviation in the indicators did not exceed 3.8%. The range of pressure values varied from 0.18 to 0.26 MPa. Field tests of the software module of the analytical unit AdU NChU showed reliable and adequate operation.
The paper discusses the issues and problems of applying multiprocessor computing systems in Industry 4.0 industrial automation systems. The examples of tasks that are effectively solved with their help are shown: control and diagnostics tasks, rolling production tasks, sign identification problems. The developed software is considered in the form of the NP Studio software platform for the development, operation and optimization of industrial automation systems. The block diagram of the software platform and the functionality of each of the subsystems are described. An example of using the neuroprocessor system for the implementation of the hexapod control task is shown.
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