Modeling method for support vector machine for bridge crane through bulged ring crossover operation RNA-GA

Abstract

The invention discloses a modeling method for a support vector machine for a bridge crane through bulged ring crossover operation RNA-GA, and belongs to the field of intelligent modeling. The modelingmethod comprises the following steps: 1) acquiring the sampling data input and output by a bridge crane system through an experiment or field acquisition, and taking the error square sum of the expected output and the actual output as the target function of the RNA-GA; 2) abstracting out the modeling method for the support vector machine for the bridge crane through the bulged ring crossover operation RNA-GA through the enlightening of the molecular bulged ring structure of RNA; 3) setting the running parameters of an algorithm; and 4) running the bulged ring crossover RNA-GA to acquire the optimal values of the parameter estimation of a support vector machine model with the least square estimation model for the position of the bridge crane and a support vector machine model with the least square estimation model for the oscillating angle of the bridge crane separately, and substituting the optimal values into the support vector machine models with the least square estimation models to form a bridge crane model. The modeling method for the support vector machine has the advantages of being high in convergence rate, high in accuracy, and the like, and is also applicable to modelingfor other complex systems.

Description

technical field [0001] The invention relates to an intelligent optimization modeling method, in particular to a support vector machine modeling method for a bridge crane operating RNA-GA with a protruding ring crossover. Background technique [0002] Bridge crane is a kind of large-scale engineering handling equipment, which is widely used in the handling of goods in industrial enterprises, buildings, ports and many other places, and occupies a pivotal position in the construction of the national economy. At present, most of the crane operations are completed by professionals. The biggest problem faced by this control method is the load swing caused by the movement of the crane and external interference. Or environmental collisions cause safety accidents. With the rapid development of science and technology, overhead cranes are developing in the direction of automation and intelligence, so it is urgent to establish a high-precision overhead crane model. The commonly used t...

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Problems solved by technology

[0006] Aiming at the shortcomings of the traditional bridge crane mechanism modeling method, which is complex and not high in precision, the present invention proposes a support vector machine modeling method for bridge cranes with protruding ring cross operation RNA-GA, and uses protruding ring cross operation RNA-GA It is used to obtain the estimated value of the least squares support vector machine (LSSVM) model parameters, and establish the position least squares support vector machine (LSSVM) model and swing angle least squares support vector machine (LSSVM) model of the overhead crane. The built model can well reflect the nonlinear characteristics of the actual system

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