Application of Long-Term Poverty Alleviation Mechanism in Chengde From the Perspective of Big Data Based on Computational Neural Model Fuzzy Algorithm

Application of Long-Term Poverty Alleviation Mechanism in Chengde From the Perspective of Big Data Based on Computational Neural Model Fuzzy Algorithm

Yanjie Zhu, Chunzheng Fu
DOI: 10.4018/IJITWE.333897
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Abstract

In order to consolidate the poverty alleviation achievements of impoverished counties, villages, and households, it is necessary to establish and improve stable poverty alleviation mechanisms. This article takes the Chengde region as the research object, and based on a large number of domestic and foreign poverty alleviation literature, combined with relevant poverty alleviation theories, uses fuzzy algorithms under big data to study and analyze the long-term mechanism of poverty alleviation and return prevention in the Chengde region. A multi classifier model with limited fuzzy rules is proposed to address the issues of low efficiency and long modeling time in existing fuzzy rule classification algorithms. When minimizing the cost function during model training, the cost function is fuzzy, thereby improving efficiency. The results indicate that the long-term poverty alleviation mechanism in Chengde from the perspective of fuzzy algorithm big data has profound strategic and theoretical significance for poverty alleviation.
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Literature Review

Big data has played an important role in achieving comprehensive victory in poverty alleviation. Next, it should give full play to the power of big data in consolidating and expanding the achievements of poverty alleviation and seriously solving the problem of data island. Over the years, many localities and departments have established various data information platforms, but due to administrative barriers and other problems, most of these data platforms are self-contained and have not yet achieved unity, effective collection, and sharing. This not only increases the information statistics of departments at all levels and wastes governance resources but also intensifies the information asymmetry between the upper and lower governments and different government departments, thus affecting the accuracy of the data information consolidated by the poverty alleviation achievements.

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