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    • 3. 发明授权
    • Statistical-deterministic approach to natural disaster prediction
    • 统计确定性自然灾害预测方法
    • US07734245B2
    • 2010-06-08
    • US11388185
    • 2006-03-23
    • Sai RavelaKerry A. Emanuel
    • Sai RavelaKerry A. Emanuel
    • G01V3/00G01V7/00G06G7/48G09B9/56G01S13/00
    • G01W1/10G06Q10/04G06Q50/26Y10S706/93Y10S706/931
    • A combined statistical-deterministic approach to methods and systems for assessing risk associated with natural disasters, in particular, hurricane wind risk. One example of a method of predicting wind speed distribution within a predetermined distance from a point of interest includes steps of statistically synthesizing a large plurality of wind storm tracks that pass within a predetermined radius of the point of interest, running a deterministic simulation of wind intensity along each one of the large plurality of wind storm tracks to produce an output representative of wind speed distribution along each track, and using the output to estimate an overall wind speed probability distribution from a combination of the wind speed distributions along each track within the predetermined distance from the point of interest.
    • 对用于评估与自然灾害有关的风险的方法和系统的综合统计确定性方法,特别是飓风风险。 在距离兴趣点的预定距离内预测风速分布的方法的一个示例包括统计合成在目标点的预定半径范围内通过的大量多个风暴轨道的步骤,运行风强度的确定性模拟 沿着每个所述多个风暴轨道中的每一个产生表示沿着每个轨道的风速分布的输出,并且使用所述输出来从所述预定的每个轨道内的每个轨道的风速分布的组合估计总体风速概率分布 距离兴趣点的距离。
    • 4. 发明授权
    • Rainfall, snowfall forecast apparatus and method
    • 降雨,降雪预报装置及方法
    • US5406481A
    • 1995-04-11
    • US266541
    • 1994-06-28
    • Kazuhiko ShinozawaNoboru SoneharaTadasu Uchiyama
    • Kazuhiko ShinozawaNoboru SoneharaTadasu Uchiyama
    • G01S13/95G01S15/88G01W1/10G06F15/54
    • G01W1/10G01S15/885G01S13/95Y10S706/931
    • An apparatus is presented for providing a short time range forecast with relative high accuracy from weather radar images of cloud reflection data by incorporating physical properties of cloud in the forecasting method. The method consists of defining a plurality of lattice points on a radar image, and multiplying the reflection data from a group of neighboring lattice points obtained at a specific past point in time with selected coefficients. The products of multiplication are summed, and transformed into image data by specific function based on the properties relating to cloud. Squared errors of the difference between the computational reflection data and the observed reflection data are iterated to a value below a predetermined threshold value to select the coefficients, and these coefficients are used to provide forecasting of reflection data at a specific future point in time.
    • 提出了一种通过在预测方法中结合云的物理属性来提供来自云反射数据的天气雷达图像的相对高精度的短时间范围预测的装置。 该方法包括在雷达图像上定义多个格点,并将来自在特定过去时间点获得的一组相邻格点的反射数据与所选择的系数相乘。 乘法乘积相加,并根据与云相关的属性通过特定函数转换为图像数据。 将计算反射数据和观察到的反射数据之间的差的平方误差迭代到低于预定阈值的值以选择系数,并且这些系数用于在特定的未来时间点提供反射数据的预测。
    • 6. 发明申请
    • Statistical-deterministic approach to natural disaster prediction
    • 统计确定性自然灾害预测方法
    • US20070168155A1
    • 2007-07-19
    • US11388185
    • 2006-03-23
    • Sai RavelaKerry Emanuel
    • Sai RavelaKerry Emanuel
    • G01W1/00G06F17/18
    • G01W1/10G06Q10/04G06Q50/26Y10S706/93Y10S706/931
    • A combined statistical-deterministic approach to methods and systems for assessing risk associated with natural disasters, in particular, hurricane wind risk. One example of a method of predicting wind speed distribution within a predetermined distance from a point of interest includes steps of statistically synthesizing a large plurality of wind storm tracks that pass within a predetermined radius of the point of interest, running a deterministic simulation of wind intensity along each one of the large plurality of wind storm tracks to produce an output representative of wind speed distribution along each track, and using the output to estimate an overall wind speed probability distribution from a combination of the wind speed distributions along each track within the predetermined distance from the point of interest.
    • 对用于评估与自然灾害有关的风险的方法和系统的综合统计确定性方法,特别是飓风风险。 在距离兴趣点的预定距离内预测风速分布的方法的一个示例包括统计合成在目标点的预定半径范围内通过的大量多个风暴轨道的步骤,运行风强度的确定性模拟 沿着每个所述多个风暴轨道中的每一个产生表示沿着每个轨道的风速分布的输出,并且使用所述输出来从所述预定的每个轨道内的每个轨道的风速分布的组合估计总体风速概率分布 距离兴趣点的距离。
    • 7. 发明授权
    • Weather forecast apparatus and method based on recognition of echo
patterns of radar images
    • 基于识别雷达图像回波模式的天气预报装置和方法
    • US5796611A
    • 1998-08-18
    • US538723
    • 1995-10-03
    • Keihiro OchiaiHideto SuzukiNoboru Sonehara
    • Keihiro OchiaiHideto SuzukiNoboru Sonehara
    • G01S7/41G01S13/95G01W1/10G06F17/10
    • G01W1/10G01S13/95G01S7/417Y10S706/931
    • The present invention provides a weather forecast apparatus and a method for the same, to systematically classify a measured radar image based on results of pattern classification of past radar images so as to use the classified radar image. In the present invention, rapid forecasting is possible by making the FNN model previously learn based on data of each class (and indexes for forecast times) obtained by classification of past weather data for every resembling pattern. In addition, a calculation procedure for improving the classifying ability of patterns can be established by varying the procedure for calculating feature quantities with regard to the radar image by using the learning of the TNN model. Furthermore, systematic classification of a pre-learned image can be realized by performing self organization with regard to compound feature quantities extracted from a radar image in the PNN model, a typical example of which is a competitive learning model.
    • 本发明提供一种天气预报装置及其方法,基于过去的雷达图像的模式分类的结果对测量的雷达图像进行系统分类,以便使用分类的雷达图像。 在本发明中,通过使FNN模型先前基于通过对于每个类似模式的过去天气数据的分类获得的每个类别(和预测时间的索引)的数据来进行快速预测是可能的。 另外,可以通过使用TNN模型的学习改变用于计算关于雷达图像的特征量的过程来建立用于提高图案分类能力的计算过程。 此外,可以通过对PNN模型中的雷达图像提取的复合特征量进行自组织来实现预先学习的图像的系统分类,其典型的例子是竞争性学习模型。