RESUMOObjetivou-se avaliar e aplicar as redes neurais artificias (RNA) para estimar o diâmetro (di) ao longo do fuste (hi) em um plantio de Eucalyptus sp., e com isso comparar com o método de regressão linear por um polinômio do quinto grau (PQG). Foram cubadas 74 árvores pelo método absoluto e destrutivo, coletando diâmetros (di) a várias alturas (hi). Para realizar a modelagem de predição dos diâmetros, a base de dados foi dividida em um conjunto de treinamento e outro de teste. O PQG foi ajustado por meio do software estatístico R considerando o método dos mínimos quadrados ordinários como procedimento de ajuste. As variáveis utilizadas para estimar os diâmetros (di) das árvores pelo método do PQG foram: Dap (diâmetro a 1,30m), di, hi e Ht (altura total). A RNA do tipo perceptron de múltiplas camadas foi implementada no software Scilab com o auxílio do ANN toolbox. As variáveis utilizadas para o treinamento da RNA foram obtidas por meio de combinações com diferentes operações matemáticas nos dados de Dap, hi e Ht. As estatísticas MAPE, MAD, MSD, RSME (%) foram aplicadas nos dados estimados com a finalidade de analisar os desvios frente aos dados observados e realizar a comparação entre os métodos utilizados. Considerando uma comparação aplicada dos métodos, foi calculado o volume e a quantificação do sortimento por árvore, usando como base as estimativas geradas. A RNA em geral apresentou boas estatísticas e um melhor gráfico residual. Conclui-se que ambas as metodologias mostraram-se eficientes para alcançar os objetivos propostos, assim as RNA podem ser consideradas como uma boa alternativa de uso e aplicação. PALAVRAS-CHAVE: Afilamento, Inteligência Artificial. Manejo florestal ENCICLOPÉDIA BIOSFERA, Centro Científico Conhecer -Goiânia, v.11 n.22; p. 2015 2420 FORECAST DIAMETERS ALONG THE STEM BY ARTIFICIAL NEURAL NETWORKSABSTRACT This study aimed apply and evaluate the artificial neural networks (ANN) to estimate the diameter (di) along the stem (hi) in a plantation of Eucalyptus sp., and after compare with the linear regression method for the fifth polynomial degree (QGP). Seventy four trees were cubed by the absolute and destructive method. The diameters (di) were collect at different heights (hi). To model the prediction of diameters, was necessary divided the database into a training set and other for test We adjusted the QGP and used the statistical software R considering the method of ordinary least squares as adjustment procedures. The variables used to model by regression QPG were: Dap (diameter 1,30m), di, hi and Ht (overall height). The ANN perceptron type multilayer was implemented in Scilab software with the help of ANN toolbox. The variables used for the training of ANN were obtained by an combinations with different mathematical operations on data Dap, hi and Ht.The statistics, MAP,MAD, MSD, RSME (%) were applied on the estimated data for the purpose of analyzing the deviations compared to the observed data and compare the methods used. Considering a apply comparison of the methods, the volum...

The objective of this study was to identify the best regions for allocation of a forestry outgrower scheme, and the most efficient transportation system, using a mathematical programming model to minimize the wood supply costs in three Brazilian states. The forest outgrower scheme is a partnership between producers and forest companies, without land acquisition by the companies. Forest producers are recognized as an important source of growth for forest production. In order to achieve successful partnerships, the company needs to plan its hiring. In this study, the partnerships are made through formal contracts and the model does not allow breach of contract. Six scenarios were modeled and evaluated based on the total cost of the objective function, average wood cost (USD/m3), average transport distance (km) and processing time. The mathematical model showed its efficiency, effectiveness, and flexibility in generating scenarios to support company managers in the decision-making and to avoid breach of contract. Hiring planning benefits both sides as it ensures the company’s production and provides financial security to forest producers. In addition, the model suggests alternatives such as the differential pricing of wood according to the location of the regions and the formation of homogeneous blocks of contracting/renewal of outgrower schemes around the pulp mill.

Scheduling problems are tasks of the operational routine in companies, which demand an optimal solution to support the decision. However, these problems have not been frequently investigated in forestry science. Therefore, it was proposed to describe a mathematical formulation for silviculture optimization under scheduling restriction of the workforce /sequencing of tasks (SSRCMM). Seeking the most suitable method to solve this combinatorial problem, two strategies were compared: i) Integer Linear Programming (ILP) and ii) simulated annealing (SA). The main criteria to assess strategies’ performance were to provide feasible solutions at an acceptable processing time and final project cost. The instance approached is a real problem outlined in 32 stands and five silvicultural tasks scheduled within a 40-day deadline. Three objective functions were also tested, defining case studies (S) to attend to the recurring managers’ decisions by minimizing: S1 – project cost, S2 – makespan, and S3 – workforce usage. The results reveal a robust model to support the forest planner in operational-level tasks. The ILP achieved the optimal solution only for the minimization of the project cost (S1) due to the delay in processing time of the other case studies. Thus, the SA stands out as an efficient method to solve the SSRCMM by providing satisfactory solutions in a reduced time. All the objective functions fitted properly with their proposed goals. The makespan and workforce usage functions increased by US$1,820.29 (S2) and US$2,146.39 (S3) from the S1, respectively, to finish the project earlier and reduce the oscillation of workforce usage over the days. Facing these findings, it is suggested that future researchers incorporate other challenges in decision-making, involving a multi-objective formulation or methods to reveal new insights for forest management and planning.