artificial neural network

Intelligent system of passenger flows dynamiC 2D-visualization for public transport routes

In order to increase the attractiveness of public transport for urban residents, a software product has been created for transport companies that, by visualizing passenger traffic, helps to improve the quality of public transport services provided within the city. The paper analyses existing and current scientific developments and literature sources, which show the advantages and disadvantages of a large number of different algorithms and methods, approaches, and methods for solving problems of 2D- visualization of passenger flows on public routes.

Method of Stabilizing Technologically Optimal Parameters of Vibration Field of Adaptive Vibrating Technological Machines by Means of Neural Network Pid Regulator

Aim. Development of the optimal method of controlling the dynamic parameters of vibratory drives of adaptive vibrating technological machines (AVTM). Method. The work is based on the creation of a direct neural network model of AVTM and the use of hybrid neuro-PID control technology to form a corrective effect based on the proportional-integral-differential law at each control cycle, to minimize feedback error on the amplitude of vibration of the vibrating machine. Results.

NEURAL NETWORK MODEL FOR IDENTIFICATION OF MATERIAL CREEP CURVES USING CUDA TECHNOLOGIES

This pa­per addres­ses the prob­lem of iden­tif­ying rhe­olo­gi­cal pa­ra­me­ters of wo­od using ar­ti­fi­ci­al neu­ral net­works with pa­ral­lel le­ar­ning al­go­rithm using Python prog­ram­ming lan­gua­ge, Cha­iner fra­me­work and CU­DA techno­logy. An in­tel­li­gent system for iden­ti­fi­ca­ti­on of rhe­olo­gi­cal pa­ra­me­ters of wo­od has be­en de­ve­lo­ped. The system cre­ated con­ta­ins the most user-fri­endly in­ter­fa­ce, all the ne­ces­sary set of to­ols for au­to­ma­ti­on of the pro­cess of vis­ua­li­za­ti­on and analysis of da­ta.

Using artificial neural networks during allocating goods in warehouse

Efficiency of storage affects the flow of material in the enterprise as well as on the functioning of the entire supply chain. One of the factors hindering decision – making in the area of storage is the allocation of goods in the storage area. Therefore the aim of this research is to describe the use of artificial neural network in decision making arrangement of goods in the warehouse. The subject of this research is the distribution of goods in the warehouse. I use simulation as a method of research, which was conducted on a case study.