基于圖神經(jīng)網(wǎng)絡的林分空間結構優(yōu)化

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中圖分類號：S750 文獻標識碼：A DOI：10.7525/j.issn.1006-8023.2025.03.002

Abstract：The optimizationof stand spatial structure is akey issue inachieving sustainable forest management.Traditionaloptimizationmethodsoftenexhibitloweficiencyinhandlingcomplexspatialrelationshipsandlarge-scaledata.This study proposed a stand spatial structure optimization method basedon Graph Atention Networks （GAT）.An integrated spatial structure evaluation system was established using the entropy-weighted mater-element analysis method，and a graph neural network modelwas constructedbasedonstanddata fromthe Tanglin ForestFarmof the Xinqing Forestry bureauin northern Yichun，Heilongjiang Province.Themodel wasapplied to perform multi-objectiveoptimization analysis of stand spatial structure. Experimental results showed that at a 2 5 % harvesting intensity，the integrated spatial structure index improvedfrom4.336 to 7.256. The GAT model demonstrated superior performance incapturing complex spatial relationships andoptimizing multi-objectivetasks.This study provides aninnovativeandintellgentapproach foroptimizing standspatial structure and managing forests，contributing to the enhancementofforest ecosystem health and stability.

Keywords：Stand spatial structure；graph neural networks；mattr-element analysis；graph atention network；entropy weighting method

0 引言

森林生態(tài)系統(tǒng)是地球上最重要的生態(tài)系統(tǒng)之一，不僅為人類提供豐富的資源，還在調節(jié)氣候、保持水土和防風固沙等方面發(fā)揮著重要作用1。（剩余15752字）