International Scholarly Research Notices

Research Article

Individual Growth Model for Eucalyptus Stands in Brazil Using Artificial Neural Network

Table 4

Architecture of artificial neural networks trained to obtain the mortality probability, height and diameter at future ages, and respective statistics.


ANN	Input variables	Number of neurons (Layers)				CV %	RMSE	Bias	Bias %	AMD
ANN	Input variables	Input	Hidden	Output		CV %	RMSE	Bias	Bias %	AMD

Mortality probability

	, , CLA, IID₁	4	9	1	0.744	43.1	0.034	0.0004	−16.91	0.0255
	IID₂	1	3	1	0.579	52.3	0.041	0.0051	−15.84	0.0305
	, , CLA, IID₃	4	8	1	0.799	38.6	0.030	0.0009	−12.73	0.0235
	, , CLA, IID₄	4	5	1	0.711	45.2	0.037	0.0112	4.01	0.0286
	, CLA, IID₅	3	4	1	0.790	39.3	0.031	0.0000	−16.34	0.0244

Height (Ht₂)

	, Ht₁, IID₁	3	6	1	0.993	3.0	0.626	−0.0011	−0.12	0.4370
	, , , Ht₁, IID₂	5	6	1	0.993	2.9	0.592	−0.0089	−0.17	0.4069
	, , , Ht₁, IID₃	5	7	1	0.994	2.6	0.532	0.0001	−0.07	0.4048
	, , , Ht₁, IID₄	5	7	1	0.995	2.5	0.526	−0.0028	−0.10	0.3979
	, , , Ht₁, IID₅	5	9	1	0.993	2.9	0.608	0.0028	−0.14	0.4222

Diameter ()

	, , , IID₁	4	5	1	0.990	4.6	0.618	−0.0048	−0.31	0.4089
	, , , , IID₂	5	7	1	0.990	4.4	0.601	−0.0118	−0.42	0.3986
	, , IID₃	3	4	1	0.993	3.8	0.523	0.0008	−0.31	0.3913
	, , , , IID₄	5	5	1	0.993	3.7	0.508	−0.0021	−0.25	0.3821
	, , , , IID₅	5	6	1	0.988	4.9	0.667	0.0013	−0.28	0.5049

: annual mortality probability; Ht₂: height at a future age (m); ₂: diameter at a future age (cm); and : current and future ages (months); : site index (m); CLA: diameter class in which the tree was (cm); and Ht₁: current diameters (cm) and heights (m); and IID₁ to IID₅: competition indices.