Forecasting the weight of bridge cranes using data analysis methods
Keywords:
neural network, bridge crane, crane weight, automation, calculationAbstract
The article presents a new method for solving the scientific and practical problem of automated calculation of the weight of general-purpose bridge cranes. Numerical data on the weight of existing cranes are given in the form of tables and structured depending on the load capacity and span. Hypotheses of mathematical statistics were used, which made it possible to distribute the results according to the normal law under the condition of the same accuracy of the obtained data. Based on these assumptions, the least squares method was applied, which made it possible to construct a function of two variables that determines the dependence of the crane weight on the span and load capacity, combining these parameters. A formula was obtained that makes it possible to programmatically calculate the weight of cranes. Based on statistical data, a neural network was built, which, similarly to traditional statistical methods, finds the weight of bridge cranes. The quality of the obtained result was assessed using traditional statistical methods and using a neural network. The work of the statistical model and neural network in the area beyond the data definition area was studied. The article substantiates the advantages of the proposed method.
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