Forecasting method of rural science and technology talents demand based on coupling algorithm

Qi Wang

doi:10.1117/12.2667984

28 March 2023 Forecasting method of rural science and technology talents demand based on coupling algorithm

Qi Wang

Proceedings Volume 12566, Fifth International Conference on Computer Information Science and Artificial Intelligence (CISAI 2022); 125664J (2023) https://doi.org/10.1117/12.2667984
Event: Fifth International Conference on Computer Information Science and Artificial Intelligence (CISAI 2022), 2022, Chongqing, China

Abstract

Because the existing methods are not comprehensive enough to consider the demand index of rural scientific and technological talents, there are some differences between the prediction results of talent demand and the actual situation. Based on this, this paper puts forward the research on the prediction method of rural science and technology talent demand based on a coupling algorithm. Considering the influence of the actual development level and development planning of rural areas on the demand for scientific and technological talents, this paper constructs a prediction index system of the demand for scientific and technological talents covering the development level and development goals of rural areas. PSO algorithm and BP neural network are used to predict the demand for scientific and technological talents. Among them, the particles of the PSO algorithm are used as the input parameters of the BP neural network, the number of nodes in the hidden layer is based on the prediction index system of scientific and technological talents demand. The fitness values of particles and nodes are calculated. After being sent to the output layer, the particle parameters are adjusted according to the expected values, and the particle parameters after two adjustments are calculated iteratively. The particle parameters at this time are taken as the prediction results of the demand for rural scientific and technological talents. The test results show that the error of the prediction results of the design method in this paper is always within 20 people. The error is positive. The relative error is not higher than 0. 014, which is superior to the comparison method to a great extent, and can realize the accurate prediction of the demand for scientific and technological talents.

Citation Download Citation

Qi Wang "Forecasting method of rural science and technology talents demand based on coupling algorithm", Proc. SPIE 12566, Fifth International Conference on Computer Information Science and Artificial Intelligence (CISAI 2022), 125664J (28 March 2023); https://doi.org/10.1117/12.2667984

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KEYWORDS

Technology

Particles

Human resources

Evolutionary algorithms

Algorithm development

Neural networks

Design and modelling

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