Evaluation and Image Analysis of Enterprise Human Resource Management Based on the Simulated Annealing-Optimized BP Neural Network

With the continuous development of social economy and the intensification of social competition, human resource management plays a more and more important role in the whole resource system. How to give full play to the advantages of human resources has become the key issue of human resource manageme...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Bo Zhao, Yuanlin Xu, Jun Cheng
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi Limited 2021
Materias:	Computer applications to medicine. Medical informatics R858-859.7 Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571
Acceso en línea:	https://doaj.org/article/51775795613f45a2bf59656a45547e2a
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:51775795613f45a2bf59656a45547e2a
record_format	dspace
spelling	oai:doaj.org-article:51775795613f45a2bf59656a45547e2a2021-11-15T01:19:36ZEvaluation and Image Analysis of Enterprise Human Resource Management Based on the Simulated Annealing-Optimized BP Neural Network1687-527310.1155/2021/3133065https://doaj.org/article/51775795613f45a2bf59656a45547e2a2021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/3133065https://doaj.org/toc/1687-5273With the continuous development of social economy and the intensification of social competition, human resource management plays a more and more important role in the whole resource system. How to give full play to the advantages of human resources has become the key issue of human resource management evaluation. However, the current human resource management evaluation system has some problems, such as poor timeliness, one-sidedness, and subjectivity. Therefore, this paper proposes a BP image neural network optimized based on the simulated annealing algorithm to realize enterprise human resource management evaluation and image analysis. Through the learning of different time series samples, the average weight distribution scheme of main indicators is obtained, in which the average weight proportions of c1, c2, c3, and c4 are 25.5%, 24.8%, 17.9%, and 31.9%, respectively. In the comprehensive evaluation of enterprise employees, the error between the actual output and expected output is less than 4.5%. The results show that the BP image neural network based on simulated annealing algorithm has high accuracy in the image analysis and evaluation of enterprise human resource management. The output analysis results meet the actual needs of the enterprise and the personal development of employees and provide a decision-making scheme for the evaluation of enterprise human resource management.Bo ZhaoYuanlin XuJun ChengHindawi LimitedarticleComputer applications to medicine. Medical informaticsR858-859.7Neurosciences. Biological psychiatry. NeuropsychiatryRC321-571ENComputational Intelligence and Neuroscience, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Computer applications to medicine. Medical informatics R858-859.7 Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571
spellingShingle	Computer applications to medicine. Medical informatics R858-859.7 Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571 Bo Zhao Yuanlin Xu Jun Cheng Evaluation and Image Analysis of Enterprise Human Resource Management Based on the Simulated Annealing-Optimized BP Neural Network
description	With the continuous development of social economy and the intensification of social competition, human resource management plays a more and more important role in the whole resource system. How to give full play to the advantages of human resources has become the key issue of human resource management evaluation. However, the current human resource management evaluation system has some problems, such as poor timeliness, one-sidedness, and subjectivity. Therefore, this paper proposes a BP image neural network optimized based on the simulated annealing algorithm to realize enterprise human resource management evaluation and image analysis. Through the learning of different time series samples, the average weight distribution scheme of main indicators is obtained, in which the average weight proportions of c1, c2, c3, and c4 are 25.5%, 24.8%, 17.9%, and 31.9%, respectively. In the comprehensive evaluation of enterprise employees, the error between the actual output and expected output is less than 4.5%. The results show that the BP image neural network based on simulated annealing algorithm has high accuracy in the image analysis and evaluation of enterprise human resource management. The output analysis results meet the actual needs of the enterprise and the personal development of employees and provide a decision-making scheme for the evaluation of enterprise human resource management.
format	article
author	Bo Zhao Yuanlin Xu Jun Cheng
author_facet	Bo Zhao Yuanlin Xu Jun Cheng
author_sort	Bo Zhao
title	Evaluation and Image Analysis of Enterprise Human Resource Management Based on the Simulated Annealing-Optimized BP Neural Network
title_short	Evaluation and Image Analysis of Enterprise Human Resource Management Based on the Simulated Annealing-Optimized BP Neural Network
title_full	Evaluation and Image Analysis of Enterprise Human Resource Management Based on the Simulated Annealing-Optimized BP Neural Network
title_fullStr	Evaluation and Image Analysis of Enterprise Human Resource Management Based on the Simulated Annealing-Optimized BP Neural Network
title_full_unstemmed	Evaluation and Image Analysis of Enterprise Human Resource Management Based on the Simulated Annealing-Optimized BP Neural Network
title_sort	evaluation and image analysis of enterprise human resource management based on the simulated annealing-optimized bp neural network
publisher	Hindawi Limited
publishDate	2021
url	https://doaj.org/article/51775795613f45a2bf59656a45547e2a
work_keys_str_mv	AT bozhao evaluationandimageanalysisofenterprisehumanresourcemanagementbasedonthesimulatedannealingoptimizedbpneuralnetwork AT yuanlinxu evaluationandimageanalysisofenterprisehumanresourcemanagementbasedonthesimulatedannealingoptimizedbpneuralnetwork AT juncheng evaluationandimageanalysisofenterprisehumanresourcemanagementbasedonthesimulatedannealingoptimizedbpneuralnetwork
_version_	1718428921666469888

Evaluation and Image Analysis of Enterprise Human Resource Management Based on the Simulated Annealing-Optimized BP Neural Network

Ejemplares similares