Optimization of the Stand Structure in Secondary Forests of Pinus yunnanensis Based on Deep Reinforcement Learning

• Published in: Forests Vol. 15; no. 12; p. 2181
• Main Authors: Zhao, Jian, Wang, Jianmming, Yin, Jiting, Chen, Yuling, Wu, Baoguo
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.12.2024
• Subjects: Adaptability; Algorithms; Analysis; Competition; Data collection; Deep learning; Environmental protection; Forest management; Forests; Homogeneity; Linear programming; Multiple objective analysis; Neighborhoods; Objective function; Optimization; Optimization models; Pinus yunnanensis; Spatial discrimination learning; Stand structure; Structural health monitoring; Structure-function relationships; Sustainability management; Sustainable forestry; Trees; China

This study proposes a multi-objective stand structure optimization scheme based on deep reinforcement learning, demonstrating the strengths of deep reinforcement learning in solving multi-objective optimization problems and providing innovative insights for sustainable forest management. Using the P...