Unlock instant, AI-driven research and patent intelligence for your innovation.

Prediction method of fluctuating wind speed based on artificial bee colony optimization lssvm

A technology of artificial bee colony optimization and pulsating wind speed, which is applied in the direction of instruments, calculations, character and pattern recognition, etc., can solve the problems of slow convergence speed and low prediction accuracy of LSSVM, and achieve fast convergence speed, improve training speed, and improve performance Effect

Inactive Publication Date: 2019-02-22
SHANGHAI UNIV
View PDF4 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to provide a fluctuating wind speed prediction method based on artificial bee colony optimization LSSVM to solve the problems of low prediction accuracy and slow convergence speed of LSSVM

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Prediction method of fluctuating wind speed based on artificial bee colony optimization lssvm
  • Prediction method of fluctuating wind speed based on artificial bee colony optimization lssvm
  • Prediction method of fluctuating wind speed based on artificial bee colony optimization lssvm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0053] The implementation of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0054] Artificial Bee Colony (ABC) is a meta-heuristic intelligent algorithm, which is inspired by the foraging behavior of bees and used to solve numerical optimization problems. ABC is mainly composed of the following three parts: Employed Bees, Onlookers and Scouts. In each cycle, the number of leading bees = the number of following bees = the number SN of solutions in the group, and the number of scout bees is 1.

[0055] When the ABC algorithm solves the optimization problem, the position of the food source represents a feasible solution of the problem to be optimized, and the process of bees collecting honey is also the process of searching for the optimal solution. In the algorithm, first initialize and generate SN solutions, and each solution x i (i=1, 2, ... SN) are all D-dimensional vectors. At the beginning of the algorithm...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention provides a fluctuating wind speed prediction method based on artificial bee colony optimization LSSVM, which comprises the following steps: firstly, using the ARMA numerical simulation method to simulate and generate the fluctuating wind speed time-history samples of the vertical space points, and the fluctuating wind speed time-history samples of the space points It is divided into two parts, the training set and the test set, which are normalized respectively; the least squares support vector machine fluctuating wind speed prediction model is established, and the artificial bee colony algorithm is used to find the optimal LSSVM model parameter combination to minimize the model prediction error. The root mean square error, correlation coefficient and convergence times are used as evaluation indicators, and compared with the results of least squares support vector machine and particle swarm optimization least squares support vector machine (PSO‑LSSVM) data-driven technology.

Description

technical field [0001] The invention relates to a data-driven fluctuating wind speed prediction method, in particular to a fluctuating wind speed prediction method based on artificial bee colony optimization LSSVM (Least Squares Support Vector Machine, Least Squares Support Vector Machine). Background technique [0002] Support Vector Machine (SVM) is a data-based machine learning algorithm developed on the basis of VC dimension and structure risk minimization principle, which has the characteristics of small samples, nonlinearity, high dimensionality and high prediction accuracy. When SVM deals with function approximation or prediction problems, it describes the problem as a convex optimization problem, based on Mercer's theorem, through nonlinear mapping The input sample points are nonlinearly mapped from the input space to the high-dimensional feature space, and then the loss function is selected, and the minimum value of the loss function is solved in the high-dimension...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/62
CPCG06F18/2411
Inventor 张永康李春祥
Owner SHANGHAI UNIV