设施番茄栽培中光谱—热环境自适应光照管理:深度学习与帕累托决策融合框架(Adaptive spectral–thermal illumination management for protected tomato cultivation: a fused deep learning and pareto-based decision framework)
提出融合深度学习与帕累托决策的设施番茄自适应补光管理框架。
该框架以CNN-ELM预测光合速率、MOEA/D权衡产量与能耗,110天试验中LED碳排降38.4%、净光合速率升22.6%、可收产量增31.7%,但结论仅限验证工况,外推需谨慎。