REVEALING THE RELATION BETWEEN INDEPENDENT VARIABLES AND DRYINGTIME IMPLEMENTED IN TORKSIM BY MEANS OF ARTIFICIAL NEURAL NETWORKS: APRELIMINARY STUDY

Bogdan BEDELEAN

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REVEALING THE RELATION BETWEEN INDEPENDENT VARIABLES AND DRYINGTIME IMPLEMENTED IN TORKSIM BY MEANS OF ARTIFICIAL NEURAL NETWORKS: APRELIMINARY STUDY

机译：通过人工神经网络揭示托克辛中独立变量与干燥时间之间的关系：辅助研究

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The purpose of this study was to reveal by means of artificial neural networks (ANN) the relation that is inside Torksim software between the independent variables (wood species, density, temperature, green moisture content, air velocity and drying schedule) and drying time in order to be incorporated in spreadsheet programs, which are used in sawmills for production planning. Different configurations of the ANN model were tested to find out the optimal structure. The optimal structure of the ANN model was 6-6-1 and was figured out based on both, the mean relative error (MRE= 1.30%) and coefficient of determination (R2=0.998). The ANN model presented in this paper is capable to discover the valuable relation between independent variables and drying time in TORKSIM software. Consequently, it can be easily and fast integrated in spreadsheet programs that are used for production planning.

机译：这项研究的目的是通过人工神经网络（ANN）揭示Torksim软件内部独立变量（木材种类，密度，温度，绿色水分，空气速度和干燥时间表）与干燥时间之间的关系。为了将其合并到电子表格程序中，该程序可在锯木厂用于生产计划。测试了ANN模型的不同配置，以找出最佳结构。 ANN模型的最佳结构为6-6-1，并根据平均相对误差（MRE = 1.30％）和确定系数（R2 = 0.998）得出。本文提出的ANN模型能够在TORKSIM软件中发现自变量与干燥时间之间的宝贵关系。因此，可以轻松，快速地将其集成到用于生产计划的电子表格程序中。

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《Pro Ligno》 |2013年第4期|共8页
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Bogdan BEDELEAN;
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REVEALING THE RELATION BETWEEN INDEPENDENT VARIABLES AND DRYINGTIME IMPLEMENTED IN TORKSIM BY MEANS OF ARTIFICIAL NEURAL NETWORKS: APRELIMINARY STUDY

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