유전 알고리즘을 활용하여 다중 지표 물리 과정 조합이 가능한 지면모델에서의 지표 물수지 시뮬레이션을 개선하는 방법
    3.
    发明公开
    유전 알고리즘을 활용하여 다중 지표 물리 과정 조합이 가능한 지면모델에서의 지표 물수지 시뮬레이션을 개선하는 방법 有权
    使用NOLH土地表面模型与多种物理选项和微观遗传算法的表面水模拟的改进方法

    公开(公告)号:KR1020140066423A

    公开(公告)日:2014-06-02

    申请号:KR1020120133619

    申请日:2012-11-23

    CPC classification number: Y02A90/16 G06F17/5009 G06N3/126

    Abstract: The present invention relates to a method for optimally improving a surface water simulation for physics options by using a micro genetic algorithm of a genetic algorithm in a Noah multi-physics options model. The present invention not only improves the accuracy of the model but also maximizes the accuracy of the model in a wide target area for water variables with large deviation according to the difference of a coating state and surface soil like evapotranspiration and runoff.

    Abstract translation: 本发明涉及通过在诺亚多物理选项模型中使用遗传算法的微遗传算法来最佳地改善物理选项的表面水模拟的方法。 本发明不仅提高了模型的精度,而且根据涂层状态和表面土壤的差异,如蒸散量和径流量,在较大偏差的水分变量的广泛目标区域中最大化模型的精度。

    동아시아에 최적화된 기후·환경 통합 예측 시스템 및 방법
    4.
    发明公开
    동아시아에 최적화된 기후·환경 통합 예측 시스템 및 방법 审中-实审
    东亚气候和环境综合预测系统和方法的优化

    公开(公告)号:KR1020170128151A

    公开(公告)日:2017-11-22

    申请号:KR1020170059561

    申请日:2017-05-12

    Abstract: 동아시아에최적화된기후-환경통합예측시스템이개시된다. 기후·환경통합예측방법은식생의전자수송속도의상한을고려하여상기식생의광합성을통한탄소의합성과정을모의하는단계; 상기식생의순 1차생산량(NPP: net primary productivity)을이용한상기탄소의분배과정을모의하는단계; 및상기탄소의합성과정및 상기탄소의분배과정을고려하여기후및 환경의변화, 또는상기기후및 환경의변화에따른농산물의변화를예측하는기후모형을결정하는단계를포함할수 있다.

    Abstract translation: 披露了针对东亚进行优化的气候 - 环境综合预测系统。 天气,环境集成预测方法,包括以下步骤:考虑通过植被的光合作用上模拟植被碳的合成的电子传输速度; 使用植被净初级生产力(NPP)模拟碳分配过程; 并且其可以包括考虑到合成处理和分配中的碳的碳的处理确定的气候模式根据天气和环境,或者在天气和环境的变化而变化,以预测在农产品的变化的步骤。

    탄소분배체계를 가지는 예단적 낙엽수림 모의 시스템

    公开(公告)号:KR101722850B1

    公开(公告)日:2017-04-05

    申请号:KR1020150129647

    申请日:2015-09-14

    CPC classification number: Y02P80/21

    Abstract: 본발명의실시예에따른예단적낙엽수림모의시스템은낙엽수림의총일차생산량을산출하는광합성모의부, 낙엽수림의호흡량을산출하는호흡모의부및 탄소분배모의부를포함할수 있다. 탄소분배모의부는개체당연간순일차생산량에기초하여잎의상대생장비율과뿌리의상대생장비율을각각산출하는상대생장비율산출부, 면적당연간순일차생산량, 잎의상대생장비율, 잎의순환율을기초로잎의연중최대생물량을산출하고면적당연간순일차생산량, 뿌리의상대생장비율, 뿌리의순환율을기초로뿌리의연중최대생물량을산출하는연중최대생물량산출부, 잎의생물량과잎의연중최대생물량에기초하여잎의생산량비율을산출하고뿌리의생물량, 뿌리의연중최대생물량및 잎의생산량비율에기초하여뿌리의생산량비율을산출하며, 잎의생산량비율과뿌리의생산량비율에기초하여줄기의생산량비율을산출하는생산량비율산출부및 순광합성량에잎의생산량비율, 뿌리의생산량비율과줄기의생산량비율을각각곱하여잎 생산량, 뿌리생산량및 줄기생산량을각각산출하는구성요소별생산량산출부를포함할수 있다.

    식생 변동을 조절하는 예측 기상 인자들을 이용한 연간 식생 변동 예측 방법 및 장치
    7.
    发明授权
    식생 변동을 조절하는 예측 기상 인자들을 이용한 연간 식생 변동 예측 방법 및 장치 有权
    使用先验气象因素预测植被变化的方法和装置调整植被变率

    公开(公告)号:KR101410770B1

    公开(公告)日:2014-06-24

    申请号:KR1020130035823

    申请日:2013-04-02

    CPC classification number: G06Q50/02 A01G7/00

    Abstract: According to the present invention, an annual vegetation predicting method includes: a step of separately analyzing a correlation between a plurality of meteorological factors and the main ingredients of a plant activity phase mode (PM) and a plant activity intensity mode (AM) which are disassembled from the past vegetation index through an empirical orthogonal function analyzing method; a step of separately selecting at least one predictive meteorological factor determined to have a statistically meaningful correlation among the meteorological factors based on the correlative analysis of each prediction of plant activity intensity and plant activity phase; and a step of separately predicting the plant activity intensity and the plant activity phase based on the past data relating to the plant activity intensity and the plant activity phase, and the present and past data for the selected prediction meteorological factor.

    Abstract translation: 根据本发明,年度植被预测方法包括:分别分析多个气象因子与植物活动相模式(PM)和植物活动强度模式(AM)的主要成分之间的相关性的步骤,其为 通过经验正交函数分析方法从过去植被指数中拆除; 基于对植物活动强度和植物活动期的每个预测的相关分析,分别选择确定为具有气象因素之间具有统计意义的相关性的至少一个预测气象因子的步骤; 以及基于与植物活动强度和植物活动期相关的过去数据以及所选预测气象因子的当前和过去数据分别预测植物活动强度和植物活动期的步骤。

    다중 물리 조합 모델과 최적화 알고리즘과의 결합을 통한 최적의 독립 모델 축출 방법
    9.
    发明公开
    다중 물리 조합 모델과 최적화 알고리즘과의 결합을 통한 최적의 독립 모델 축출 방법 有权
    通过多方案模型和遗传算法联合获得最佳优化模型的方法

    公开(公告)号:KR1020140066351A

    公开(公告)日:2014-06-02

    申请号:KR1020120133461

    申请日:2012-11-23

    CPC classification number: G06N3/126 G01N33/18

    Abstract: The present invention relates to a method for obtaining a best independent model and improving simulation accuracy which maximizes the simulation accuracy for a single or a plurality of target variables in an available physics parameterization technique by applying a model optimization algorithm to a multi-physics model. The present invention can use a minimized computing system resource capable of maximizing the simulation accuracy of the single or the plurality of target variables among the physical parameterization schemes.

    Abstract translation: 本发明涉及一种用于获得最佳独立模型并提高模拟精度的方法,其通过将模型优化算法应用于多物理模型,使可用物理参数化技术中的单个或多个目标变量的模拟精度最大化。 本发明可以使用能够最大化物理参数化方案中的单个或多个目标变量的模拟精度的最小化计算系统资源。

    수치모델에 접합 가능한 유전알고리즘 인터페이스 시스템
    10.
    发明公开
    수치모델에 접합 가능한 유전알고리즘 인터페이스 시스템 有权
    基于使用遗传算法的大气数值模型预测精度的系统与方法

    公开(公告)号:KR1020120092963A

    公开(公告)日:2012-08-22

    申请号:KR1020110012922

    申请日:2011-02-14

    Inventor: 박선기

    CPC classification number: G01W1/10 G01W1/14 G06F19/18

    Abstract: PURPOSE: A genetic algorithm interface system applicable for a numerical model is provided to improve the accuracy of rainfall forecast by being applied for a weather forecasting model. CONSTITUTION: A system for forecasting rainfall includes a data inputting part(110), a model inputting part(120), a first parameter generating part(130), an ETS storing part(140), a second parameter generating part(150), and a convergence analyzing part(160). Rainfall data is input into the data inputting part. A forecasting model based on convective parameterization is inputted into the model inputting part. The first parameter generating part generates arbitrary parameters based on the input rainfall data. The ETS storing part stores rainfall forecast by implementing the forecasting model based on the parameters. The second parameter generating part evaluates the stored ETS based on a genetic algorithm and generates enhanced second parameters. The convergence analyzing part implements the forecasting model based on the second parameters and analyzes the convergence of parameter values.

    Abstract translation: 目的:提出适用于数值模型的遗传算法接口系统,通过应用天气预报模型提高降雨预报的准确性。 一种用于预报降雨的系统,包括数据输入部分(110),模型输入部分(120),第一参数产生部分(130),ETS存储部分(140),第二参数产生部分(150) 和收敛分析部(160)。 降雨数据输入到数据输入部分。 基于对流参数化的预测模型输入到模型输入部分。 第一个参数产生部分根据输入的降雨数据生成任意参数。 ETS存储部分通过实施基于参数的预测模型存储降雨预报。 第二参数生成部分基于遗传算法对存储的ETS进行评估,并生成增强的第二参数。 收敛分析部分基于第二参数实现预测模型,并分析参数值的收敛性。

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