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A Minimum Crossed Entropy Model to Generate Information at Disaggregated Level

机译:最小跨熵模型,用于在分组级别生成信息

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Montado ecosystem in the south of Portugal, integrated in Mediterranean ecosystems, has been extensively used by man for agro-forestry-extensive grazing systems. Sustainable development of this Montado ecosystem demands a long-term perspective about the consequences of today's activities, but a definition of the homogeneous units among this heterogeneous ecosystem is absolutely needed. This paper demonstrates the adherence of the minimum crossed entropy model as a process conducting to dynamic spatial information generation and disaggregation. With this model, it will be possible to use the disposable information to generate data disaggregated to homogeneous units that can be used on the estimation of these territories' soil occupation. The results quality will be evaluated using the weighted prescription absolute deviation (DAPP) and measuring the quantity of information that is changed due to aggregation process by the use of a "Disagegation Information Gain" (DIG), based on the cross entropy between the observed values of soil occupation at aggregated and disaggregated level and on the crossed entropy between the soil occupation estimated by the disaggregation model and those observed at HSU disaggregated level.
机译:蒙特多生态系统在葡萄牙南部,集成在地中海生态系统中,由人类广泛使用农业林业广泛放牧系统。该蒙特多生态系统的可持续发展需要对当今活动的后果的长期视角,而是绝对需要这种异构生态系统中的均匀单位的定义。本文展示了最小交叉熵模型的依从性作为对动态空间信息生成和分类的过程。利用这种模型,可以使用一次性信息来生成分解的数据,该数据可以用于估计这些地区的土壤占据的均匀单元。使用加权处方绝对偏差(DAPP)来评估结果质量,并测量通过使用“脱离信息增益”(DIG)来测量由于观察到的交叉熵(DIC)而导致的聚合过程所改变的信息量分解模型估计土壤占用水平与分解模型估计的土壤占用的价值观,综合分解水平观察。

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