分析回归模型和多层人工神经网络模型,以估算克里米亚松林的锥度和树木体积

IF 1.5 4区 农林科学 Q2 FORESTRY Iforest - Biogeosciences and Forestry Pub Date : 2024-02-29 DOI:10.3832/ifor4449-017
A. Sahin
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Analyzing regression models and multi-layer artificial neural network models for estimating taper and tree volume in Crimean pine forests
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来源期刊
CiteScore
3.30
自引率
0.00%
发文量
54
审稿时长
6 months
期刊介绍: The journal encompasses a broad range of research aspects concerning forest science: forest ecology, biodiversity/genetics and ecophysiology, silviculture, forest inventory and planning, forest protection and monitoring, forest harvesting, landscape ecology, forest history, wood technology.
期刊最新文献
Relationship between microbiological, physical, and chemical attributes of different soil types under Pinus taeda plantations in southern Brazil Exploring machine learning modeling approaches for biomass and carbon dioxide weight estimation in Lebanon cedar trees Analyzing regression models and multi-layer artificial neural network models for estimating taper and tree volume in Crimean pine forests Use of brassinosteroids to overcome unfavourable climatic effects on seed germination in Pinus nigra J. F. Arnold Forest fire occurrence modeling in Southwest Turkey using MaxEnt machine learning technique
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