Work

Construction and Application of Agricultural Talent Training Model Based on AHP-KNN Algorithm

Year: 2023

Type: article

Abstract: At present, the gap of agricultural talents in China is continuously widening, and most enterprises lack agricultural core talents, which has caused great impact on the social economy. To solve this problem, an improved AHP-KNN algorithm is proposed by combining the analytic hierarchy process (AHP) and the optimized K-nearest neighbor algorithm, and an agricultural talent training model is proposed based on this algorithm. The results show that the classification accuracy and classification time of the improved AHP-KNN algorithm are 96.2% and 27.5 seconds, respectively, both of which are superior to the comparison algorithm. The result shows that the classification accuracy of agricultural talents can be improved by using this algorithm. Therefore, the model can be used to classify agricultural talents with the same characteristics into one class, carry out targeted training, and train all-round agricultural talents efficiently and quickly, so as to improve the serious shortage of agricultural talents at present.

Source: Journal of Applied Mathematics

DOI: 10.1155/2023/5745955

Authors: Shubing Qiu, Yong Liu, Xiaohong Zhou

Institutions: Shandong University, Anhui Polytechnic University, Hebei Jiaotong Vocational and Technical College

Language: English

Topic: AI and HR Technologies

Subfield: Organizational Behavior and Human Resource Management

Field: Business, Management and Accounting

Domain: Social Sciences

SDG: Zero hunger

Open Access status: gold

Estimated APC paid: $1,050