Correction to: Construction and case verification of rural environmental value‑added evaluation system

Wan, Ajun; Qi, Xuejiao; Yue, Weidong; Tu, Runqiu

doi:10.1007/s10668-021-01762-w

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“…The logic behind it is to move away from urban-rural division and toward urban-rural integration, which is the process of integrating the city and the countryside into an organic whole [ 1 , 2 ]. In this context, some rural areas with abundant natural or humanistic tourism resources have achieved remarkable results by promoting new rural construction through rural tourism, which not only opens up a new field of tourism development, but also serves as an important tool for promoting new socialist rural construction [ 3 ]. Building a new socialist countryside is a critical strategic task for adapting to the “three rural issues,” realising the goal of a prosperous society, and establishing a harmonious socialist society.…”

Section: Introductionmentioning

confidence: 99%

[Retracted] Interactive Model of Rural Tourism and New Socialist Countryside Construction Using Deep Learning Technology

Chen

2022

Journal of Environmental and Public Health

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China has proposed two major measures to address the “three rural issues”: the first is to abolish the agricultural tax, which has been in place for over 2000 years; the second is to propose the construction of a new socialist countryside, which would mark the end of the old era and the beginning of the new. As a result, this paper employs in-depth learning technology to enhance rural tourism development and the creation of a new socialist countryside. This paper investigates deep-learning-based rural tourism and the creation of a new socialist countryside. Because MSE and MAE reflect the prediction error score, the lower the value, the better the recommendation accuracy. The MSE value of the machine learning algorithm is 2.456, the MSE value of the data mining algorithm is 2.324, and the MSE value of the convolution neural network algorithm is 2.102, when the number reaches 80. It can be concluded that the convolution neural network algorithm proposed in this paper has the lowest MSE and MAE values of the three methods, implying that the convolution neural network algorithm is the best of the three. The use of the convolution neural network algorithm to implement the scientific concept of development and the construction of a new socialist countryside is an important part of creating a harmonious society that fully meets the central government’s objectives and requirements for the construction of a new socialist countryside.

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Section: Introductionmentioning

confidence: 99%

[Retracted] Interactive Model of Rural Tourism and New Socialist Countryside Construction Using Deep Learning Technology

Chen

2022

Journal of Environmental and Public Health

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Correction to: Construction and case verification of rural environmental value‑added evaluation system

Cited by 1 publication

References 1 publication

[Retracted] Interactive Model of Rural Tourism and New Socialist Countryside Construction Using Deep Learning Technology

[Retracted] Interactive Model of Rural Tourism and New Socialist Countryside Construction Using Deep Learning Technology

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