Two-sided matching based on I-BTM and LSGDM applied to high-level overseas talent and job fit problems

Yang, Qing; You, Xinshang; Zhang, Yiye

doi:10.1038/s41598-021-92057-7

Cited by 9 publications

(6 citation statements)

References 58 publications

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“…It can be seen that talents, especially high-level talents, have become an important strategic resource for the country's innovative development and an indispensable force for realizing the goals of the national government. At the same time, talents are an important group that can achieve major breakthroughs through policy adjustment [1][2][3][4][5].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of the Impact of the Introduction of Overseas High-Level Talents on the Development of Central Cities with Artificial Neural Network

Huang

2022

Security and Communication Networks

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For the central cities, the transformation and upgrading of the industrial structure, the continuous deepening of innovation capabilities, and the improvement of sustainable development capabilities, human resources are playing an increasingly important role. In the modern era, assembling an army of highly educated, high-quality, and highly talented personnel has become a practical demand of talent development strategy. In order to respond to national policies, keep up with the trend of the times, and give play to the comparative advantages of talent competition, the primary task of central cities is to do a good job in the introduction of overseas high-level talents. It is necessary for the central cities to establish a mechanism for the introduction of overseas high-level talents with the government as an important task and to formulate targeted talent introduction policies according to the local characteristics of the central cities. It is very important to evaluate the impact of the introduction of overseas high-level talents on the development of central cities so that the central cities can formulate talent introduction strategies according to the actual situation. This work uses an artificial neural network to evaluate the impact of the introduction of overseas high-level talents on the development of central cities. Aiming at the problem that the evaluation accuracy and computing efficiency of the deep learning-based method decrease due to the proliferation of neural network layers, and the improved residual network model is proposed. On the one hand, a multiscale feature fusion block is designed in the first layer of the network model, which can extract the multiscale feature information in the original special. On the other hand, the residual block is optimized and improved by using depthwise separable convolution to remove the computational burden on the network.

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Section: Introductionmentioning

confidence: 99%

Evaluation of the Impact of the Introduction of Overseas High-Level Talents on the Development of Central Cities with Artificial Neural Network

Huang

2022

Security and Communication Networks

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“…Liang et al 11 proposed an intervalvalued intuitionistic fuzzy bilateral matching model considering the level of automation to solve the human-machine position matching in intelligent production lines. Yang et al 12 constructed a new hybrid bilateral matching method based on I-BTM and LSGDM suitable for overseas high-level talents and position matching problems.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Person-position Matching Decision Method Based on Hesitant Fuzzy Number Information

Yue,

Liu,

Tao

2023

Preprint

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In view of the fact that people pay more and more attention to the principle of "getting the position according to the person" and "adapting the person to the position" in person-position matching, a dynamic person-position matching decision method based on hesitant fuzzy numbers is proposed. First, the dynamic person-position matching problem with the hesitant fuzzy numbers is described. Then, according to the hesitant fuzzy evaluation matrices of the positions and the candidates, the expected score matrices of bilateral subjects are calculated. Furthermore, based on the idea of the generalized optimal order method and the dominant correlation and the missing correlation coefficient, the satisfaction mean of both people and positions is calculated. According to the satisfaction mean, the growth satisfaction of each period is obtained, and then the exponential decay formula is used to determine the weights of the growth satisfaction. The dynamic satisfaction of bilateral subjects is calculated by aggregating the initial satisfaction mean and the growth satisfaction. On this basis, a stable person-position matching model considering dynamic satisfaction is established and then is solved to obtain the optimal stable person-position matching scheme. Finally, the feasibility and effectiveness of the proposed method are verified by the example analysis of person-position matching. The main contributions of this article are as follows: an effective calculation method for the missing correlation coefficient is presented; a novel effective calculation method for the dynamic satisfaction is proposed by introducing the correlation parameter to combine the missing correlation with the dominant correlation coefficient; an effective stable person-position matching model considering the dynamic satisfaction is established.

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“…Yang et al constructed a new hybrid bilateral matching method and a large-scale group decision-making method considering social network analysis. The decision-making information can be expressed more objectively and reasonably [17].…”

Section: Introductionmentioning

confidence: 99%

A Large-Scale Group Decision-Making Approach to Assess Water Resource Sustainability with Double-Level Linguistic Preference Relation

Yao

Zhou

Xiao

2023

Water

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With the rapid development of science and technology and the continuous progress of society, water resource sustainability has attracted much attention. The assessment process of water resource sustainability has become a hot topic. Because professional models cannot ensure the accuracy of evaluation results, expert judgment techniques are used to perform the assessment process. Meanwhile, to eliminate the biases and consider people’s cognitive processes in complex decision making, this study utilizes a large group of experts to evaluate the sustainability of water resources, which is called a large-scale group water resource sustainability assessment (LGWRSA). This study proposes the double-level linguistic preference relation (DLLPR) to enable experts to present more reasonable and intuitive linguistic opinions. Based on the DLLPR, this study presents a clustering method, a weighting method, and a comprehensive adjustment factor determination method. To prevent minority opinions and non-cooperative behaviors from interfering with the decision-making process and to make the decision-making process develop in an accurate and objective direction, a consensus model is developed to modify minority opinions and suggestions and manage non-cooperative behaviors. After a sufficient number of experts reach a consensus through the method proposed in this article, a more accurate evaluation result can be obtained. Finally, an actual LGWRSA problem is established to derive water resource sustainability expectations for four provinces, which validates the effectiveness of the proposed method. A comparative analysis is performed to illustrate the benefits of these methods and present their shortcomings.

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Two-sided matching based on I-BTM and LSGDM applied to high-level overseas talent and job fit problems

Cited by 9 publications

References 58 publications

Evaluation of the Impact of the Introduction of Overseas High-Level Talents on the Development of Central Cities with Artificial Neural Network

Evaluation of the Impact of the Introduction of Overseas High-Level Talents on the Development of Central Cities with Artificial Neural Network

Dynamic Person-position Matching Decision Method Based on Hesitant Fuzzy Number Information

A Large-Scale Group Decision-Making Approach to Assess Water Resource Sustainability with Double-Level Linguistic Preference Relation

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