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Construction and Empirical Study of Rural Poverty Early Warning System Based on EGM-Markov Model
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Baosheng ZHANG, Xueting MA, Juntong LI
Science Technology and Industry | 2025, 25(14) : 261 - 265
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Science Technology and Industry | 2025, 25(14): 261-265
Governance & Performance
Construction and Empirical Study of Rural Poverty Early Warning System Based on EGM-Markov Model
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Baosheng ZHANG, Xueting MA, Juntong LI
Affiliations
  • School of Economics and Management, Harbin Normal University, Harbin 150025, China
Published: 2025-07-25
Outline
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The overall victory in the battle against poverty indicates that China has comprehensively solved the problem of poverty, but some residents still have the risk of returning to poverty. In order to avoid this phenomenon as much as possible, the Party Central Committee clearly proposed to actively establish a monitoring mechanism to prevent returning to poverty. It constructs the rural poverty return monitoring index system and EGM-Markov poverty return risk early warning model, forecasts the development trend and divides the early warning level, and takes YS County of Heilongjiang Province as a case to verify the feasibility of the model. In addition to establishing a long-term assistance mechanism, stimulating the endogenous motivation of the poor is very important to avoid returning to poverty.

return to poverty  /  EGM-Markov model  /  early warning mechanism  /  dynamic monitoring
Baosheng ZHANG, Xueting MA, Juntong LI. Construction and Empirical Study of Rural Poverty Early Warning System Based on EGM-Markov Model[J]. Science Technology and Industry, 2025 , 25 (14) : 261 -265 .
Year 2025 volume 25 Issue 14
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Article Info
  • Receive Date:2024-11-28
  • Online Date:2025-09-15
  • Published:2025-07-25
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  • Received:2024-11-28
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Affiliations
    School of Economics and Management, Harbin Normal University, Harbin 150025, China
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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