Value Analysis and Realization of Artistic Intervention in Rural Revitalization Based on the Fuzzy Clustering Algorithm

Liang, Jingqiu

doi:10.1155/2022/3107440

Cited by 11 publications

(6 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This study used the FCM method and user collaborative filtering to solve the data sparsity problem. The results of experiments on the dataset show that FCM and collaborative-filtering algorithms can solve data sparsity problems and improve the accuracy of recommendations [31].…”

Section: Literature Reviewmentioning

confidence: 99%

Determining rural development priorities using a hybrid clustering approach: a case study of South Sulawesi, Indonesia

2023

IJATEE

View full text Add to dashboard Cite

South Sulawesi province implements a village assistance program. The program aims to ensure the successful implementation of village development activities, reduce urbanization, and address development problems in rural areas. This research discusses finding alternative solutions to determining the priority status of villages that need assistance from experts. Village assistance is an activity in the context of developing self-sufficiency and feasibility of

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Determining rural development priorities using a hybrid clustering approach: a case study of South Sulawesi, Indonesia

2023

IJATEE

View full text Add to dashboard Cite

show abstract

“…Literature [8] suggests that rural areas establish a brand that is in line with contemporary aesthetics and meets the needs of modern people's diverse lives. This paper solves and establishes a semisupervised fuzzy C-mean clustering using the SSFCM-HPR algorithm using the HPR multiplier method.…”

Section: Related Researchmentioning

confidence: 99%

Analysis of the Practical Path of Vocational Education Serving Rural Revitalization by Digital Means and Philosophy of Technology

Tian

2023

Applied Mathematics and Nonlinear Sciences

View full text Add to dashboard Cite

In this paper, based on digital means and technical philosophy, the histogram algorithm in the Light GBM model is used to calculate the floating point values of the raw data for the analysis of vocational education service for rural revitalization so that each of its features is converted into a histogram. In order to prevent the feature training overfitting problem of the Light GBM model, the LightGBM model is optimized by the iterative tree MPA algorithm, and the prediction model of returning to poverty risk based on IMPA-LightGBM is constructed. Starting from the current situation of vocational education service for rural revitalization, we put forward research hypotheses to realize the research design of vocational education accurate poverty alleviation service for rural revitalization and carry out an example analysis of vocational education service for rural revitalization combined with digital technology. The results show that in terms of model performance, the WAPE values of the return-to-poor risk values obtained from the prediction of the IMPA-LightGBM model are all lower than 5.5%, so the prediction effect is relatively satisfactory, and the return-to-poor risk values of poverty-eradicating households can be effectively predicted. On the practice road analysis, the standard deviation (SD) of the rural revitalization development index in China as a whole decreased from 0.63 to 0.52, which means that the differences in rural revitalization among provinces are decreasing. This study explores the synergistic development of the community of interest between vocational education and rural revitalization through the cultivation of new vocational farmers.

show abstract

“…Rural revitalization is the goal of modernization. Literature [16] uses the HPR multiplier method to solve and establish a semi-supervised fuzzy C-mean clustering of the SSFCM-HPR algorithm, which effectively solves the problem of data sparsity, improves the accuracy of the rural revitalization of the financial recommendations, and puts forward a new development idea and guidance method for sustainable rural development. Literature [17] establishes the important service subjects of agricultural big data platforms on the basis of a comprehensive technology acceptance model, analyzes the impact of big data services on farmers' revitalization, effectively improves the willingness of farmers to adopt and utilize agricultural big data of great practical significance, and proves that the factors affecting the behavior and attitude of agricultural personnel.…”

Section: ) Rural Revitalizationmentioning

confidence: 99%

Development path of rural financial services for rural revitalization based on big data analysis

Cheng

2023

Applied Mathematics and Nonlinear Sciences

View full text Add to dashboard Cite

This paper is based on big data analysis technology to process the data related to rural construction and analyze the rural financial service development measurement after constructing the rural financial service indicator system combined with the principal component analysis method. The entropy value method is utilized to measure the constructed rural development index system and assess the development level of rural financial services for rural revitalization. On this basis, the benchmark regression model of rural financial services and rural revitalization is constructed, descriptive statistics are carried out, and the development effect of rural financial services on rural revitalization is analyzed after passing the smoothness test to explore its development path. The results show that the development measure of rural financial services from 1978 to 2021 rises from less than 0.5 to more than 0.7, and the development index of rural revitalization also rises by about 0.1, and the levels of both rural financial services and rural revitalization are rising. The mean value of the rural revitalization index is 0.282, the minimum value of the rural revitalization index is 0.143, and the maximum value is 0.494, and all the variables of rural financial services on rural revitalization are significant at the 1% level, with a significant impact. Based on this study, rural financial reform is synergistically promoted in three major aspects, namely, coordinating all kinds of financial organizations, innovating financial support for agricultural products and strengthening financial supervision and prevention.

show abstract

Value Analysis and Realization of Artistic Intervention in Rural Revitalization Based on the Fuzzy Clustering Algorithm

Cited by 11 publications

References 12 publications

Determining rural development priorities using a hybrid clustering approach: a case study of South Sulawesi, Indonesia

Determining rural development priorities using a hybrid clustering approach: a case study of South Sulawesi, Indonesia

Analysis of the Practical Path of Vocational Education Serving Rural Revitalization by Digital Means and Philosophy of Technology

Development path of rural financial services for rural revitalization based on big data analysis

Contact Info

Product

Resources

About