The paper implemened forest resources data updated by designing survey database of resource (including subcompartment database and tree species database) and database of resource(including changed database of subcompa...The paper implemened forest resources data updated by designing survey database of resource (including subcompartment database and tree species database) and database of resource(including changed database of subcompartment and changed database of tree species) change,compartementalized database of resource survey into two processes—stand growing naturally without interference and stand changing caused by the interference of environment.The data of natural forest resources was updated by applying interrelation between database and adopting different types of growth and management models respectively on the base of network database language—PowerBulider and Visual C as well.展开更多
大数据环境下的多源数据呈现出数据量大、数据种类多、数据变化快的特点,这些特点对数据更新提出了新的挑战。通过分析大数据下多源数据的特点,定义了演化数据的概念,基于此建立了大数据的动态变频遍历更新模型。首先通过抽象数据的演...大数据环境下的多源数据呈现出数据量大、数据种类多、数据变化快的特点,这些特点对数据更新提出了新的挑战。通过分析大数据下多源数据的特点,定义了演化数据的概念,基于此建立了大数据的动态变频遍历更新模型。首先通过抽象数据的演化方式,建立了演化数据的势与稳定性概念,从而推导出更一般的代数意义上的演化运算工具;其次通过将运算工具导入大数据数据更新的实际应用中,推导出基于概率的变频遍历与动态权值模型;最后通过实验验证了在大数据环境下动态变频遍历模型(Dynamic Frequency Conversion Traversal,DFCT)对多源数据具有较高的更新效率。展开更多
文摘The paper implemened forest resources data updated by designing survey database of resource (including subcompartment database and tree species database) and database of resource(including changed database of subcompartment and changed database of tree species) change,compartementalized database of resource survey into two processes—stand growing naturally without interference and stand changing caused by the interference of environment.The data of natural forest resources was updated by applying interrelation between database and adopting different types of growth and management models respectively on the base of network database language—PowerBulider and Visual C as well.
文摘大数据环境下的多源数据呈现出数据量大、数据种类多、数据变化快的特点,这些特点对数据更新提出了新的挑战。通过分析大数据下多源数据的特点,定义了演化数据的概念,基于此建立了大数据的动态变频遍历更新模型。首先通过抽象数据的演化方式,建立了演化数据的势与稳定性概念,从而推导出更一般的代数意义上的演化运算工具;其次通过将运算工具导入大数据数据更新的实际应用中,推导出基于概率的变频遍历与动态权值模型;最后通过实验验证了在大数据环境下动态变频遍历模型(Dynamic Frequency Conversion Traversal,DFCT)对多源数据具有较高的更新效率。
