CA2556985A1 - Method and system for automated location dependent probabilistic tropical cyclone forecast - Google Patents
Method and system for automated location dependent probabilistic tropical cyclone forecast Download PDFInfo
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- CA2556985A1 CA2556985A1 CA002556985A CA2556985A CA2556985A1 CA 2556985 A1 CA2556985 A1 CA 2556985A1 CA 002556985 A CA002556985 A CA 002556985A CA 2556985 A CA2556985 A CA 2556985A CA 2556985 A1 CA2556985 A1 CA 2556985A1
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01W—METEOROLOGY
- G01W1/00—Meteorology
- G01W1/10—Devices for predicting weather conditions
Abstract
A method for automated location dependent probabilistic tropical cyclone forecast. A plurality of new data records representative of alternative tracks are generated based on historical tracks by a first MonteCarlo-module. Points of the new data records are generated from points along the historical track by a dependent sampling process, whereas an intensity climatology is generated, based upon intensity data associated with at least some of the plurality of points along the historical tracks located within a certain grid cell. New intensity data are generated by a second MonteCarlo-module, from the intensity data associated with at least some of the plurality of points along the historical tracks by a MonteCarlo sampling process.
Claims (34)
1. Method for automated location dependent probabilistic tropical cyclone forecast, whereas data records of weather events are generated and location dependent probability values for specific weather conditions associated with the tropical cyclone are determined, characterised, in that data records representative of an historical track of a weather event are assigned to a year of occurrence of said weather event and are saved on a memory module of a calculating unit, said data records including a plurality of points representative of geographical positions and/or intensity of the event along the historical track, in that a plurality of new data records representative of alternative tracks are generated for each historical track by means of a fist MonteCarlo-module, wherein points of said new data records are generated from said points along the historical track by a dependent sampling process, in that a grid over a geographical area of interest is established by means of the calculation unit, said area including at least a portion of the plurality of historical tracks, and a intensity climatology for selected cells in the grid is generated, based upon the intensity data associated with at least some of the plurality of points along the historical tracks located within said selected grid cells, in that for each of said alternative tracks one or more new intensity data are generated by means of a second MonteCarlo-module, wherein the one or more new intensity data of the new data records of said alternative tracks are generated from the intensity data associated with at least some of the plurality of points along the historical tracks by a MonteCarlo sampling process, in that a distribution for a definable time period of the data records of the historical tracks is generates by means of a scaling table classifying the weather events by intensity and/or year of occurrence, and said distribution of said historical tracks are reproduced by a filtering module within the new or accumulated data records according to their assigned year, in that a wind field of each data record is generated based on a definable wind field profile, and a probability is assigned by a interpolation-module to each point in said grid, giving the probability of the occurrence of a specific wind strength at a given geographical location and time.
2. Method according to claim 1, characterized in, that for the weather events tropical cyclone events, in particular hurricane events or typhoon events or tropical storm events are used.
3. Method according to one of the claims 1 or 2, characterized in, that said data representative of intensity comprises atmospheric pressure data associated with at least some of the plurality of points along the historical track, said atmospheric pressure data defining an historical pressure profile of the historical track.
4. Method according to claim 3, characterized in, that the intensity climatology comprises a pressure climatology.
5. Method according to claim 4, characterized in, that the pressure climatology for at least one of the selected cells is a pressure distribution function.
6. Method according to one of the claims 3 to 5, characterized in, that said atmospheric pressure data includes an absolute pressure (P) and a derivative of absolute pressure with respect to time (dP/dT).
7. Method according to one of the claims 4 to 6, characterized in, that the pressure climatology for a selected cell in the grid is established from at least one of the atmospheric pressure data associated with the selected cell and the atmospheric pressure data associated with one or more cells adjacent the selected cell.
8. Method according to one of the claims 4 to 7, characterized in, that the pressure climatology for a selected cell is established from a weighted averaging of pressure data associated with the selected cell and pressure data associated with one or more cells adjacent a selected cell.
9. Method according to one of the claims 4 to 8, characterized in, that each cell in the grid is assigned a land/sea value, and wherein pressure data associated with an adjacent cell is used to establish the pressure climatology of a selected cell only if the adjacent cell and the selected cell have the same land/sea value.
10. Method according to one of the claims 4 to 9, characterized in, that one or more alternative pressure profiles for one or more of the historical tracks using the pressure climatology for the selected cells in the grid are generated.
11. Method according to one of the claims 3 to 10, characterized in, that one or more pressure profiles for one or more of the alternative tracks are generated.
12. Method according to one of the claims 4 to 11, characterized in, that one or more alternative pressure profiles for one or more of the alternative tracks using the pressure climatology for the selected cells of the grid are generated.
13. Method according to one of the claims 3 to 12, characterized in, that at least one of the alternative pressure profiles for the historical tracks, the pressure profiles for the alternative tracks, and the alternative pressure profiles for the alternative tracks are modified based, at least in part, on the historical pressure profile along the historical track of the associated weather event.
14. Method according to one of the claims 1 to 13, characterized in, that said dependent sampling process is a directed random walk process.
15. Method according to one of the claims 1 to 14, characterized in, that at least some of the plurality of alternative tracks have starting points that differ from a starting point of the historical track upon which said alternative tracks are based.
16. Method according to one of the claims 1 to 15, characterized in, that data representative of alternate tracks based on said historical track are generated by:
i) generating a series of random tuples (x r,y r) for a historical point (x,y) of the historical track;
ii) calculating a sum of random deviations (x',y') of the random tuples along the historical track; and iii) adding the sum of random deviations (x',y') to the historical point (x,y) of the historical track to produce alternative points along the alternative tracks.
i) generating a series of random tuples (x r,y r) for a historical point (x,y) of the historical track;
ii) calculating a sum of random deviations (x',y') of the random tuples along the historical track; and iii) adding the sum of random deviations (x',y') to the historical point (x,y) of the historical track to produce alternative points along the alternative tracks.
17. Method according to one of the claims 1 to 16, characterized in, that a longitude and a latitude are assigned to said data representative of a track of an historical weather event whereas said longitude and said latitude define each of a plurality of points along said track.
18. Method according to one of the claims 1 to 17, characterized in, that said data records include data records representative of a plurality of historic tracks, and said new data records include include data records representative a plurality of alternative tracks for more than one of said plurality of historical tracks.
19. Method according to one of the claims 1 to 18, characterized in, that said data representative of an historical track comprises at least:
i) longitude and latitude of a plurality of points representative of the historical track;
ii) an azimuth angle for at least some of the points along the historical track;
iii) celerity for at least some of the points along the historical track;
iv) a rate of change of azimuth angle for at least some of the points along the historical track; and v) a rate of change of celerity for at least some of the points along the historical track.
i) longitude and latitude of a plurality of points representative of the historical track;
ii) an azimuth angle for at least some of the points along the historical track;
iii) celerity for at least some of the points along the historical track;
iv) a rate of change of azimuth angle for at least some of the points along the historical track; and v) a rate of change of celerity for at least some of the points along the historical track.
20. Method according to one of the claims 1 to 19, characterized in, that at least one subset of the data representative of the alternative tracks for use in the probabilistic data set is selected.
21. Method according to one of the claims 1 to 20, characterized in, that a variance of said alternative points of said data records representative of alternative tracks from a respective historical point in accordance with one or more physical laws is limited.
22. Method according to one of the claims 1 to 21, characterized in, that said data records comprise data representative of a plurality of historical tracks and data representative of atmospheric pressure associated with at least some of the plurality of points along the historical tracks, said atmospheric data defining historical pressure profiles of the historical tracks, and that said new data records comprise a plurality of alternative tracks for more than one of said plurality of historical tracks, whereas:
i) One or more alternative pressure profiles for one or more of the historical tracks are generated;
ii) One or more pressure profiles for one or more of the alternative tracks are generated; and iii) One or more alternative pressure profiles for one or more of the alternative tracks are generated.
i) One or more alternative pressure profiles for one or more of the historical tracks are generated;
ii) One or more pressure profiles for one or more of the alternative tracks are generated; and iii) One or more alternative pressure profiles for one or more of the alternative tracks are generated.
23. Method according to claim 22, characterized in, that at least one subset of data from the data representative of the historical tracks is extracted, the alternative tracks, and the pressure profiles, based on climatological conditions for a selected time period.
24. Method according to one of the claims 3 to 23, characterized in that a plurality of alternative pressure profiles associated with the track of the historical weather event are generated.
25. Method according to claim 24, characterized in that a plurality of alternative pressure profiles is generated by means of the Monte-Carlo module by:
(i) Identifying a point of occurrence of an absolute pressure minimum along the track of the historical weather event;
(ii) Selecting an alternative pressure value at the point identified in step (i);
(iii) Adjusting pressure values at a plurality of other points along the track of the historical weather event, in accordance with the selected alternative pressure value, to create an alternative pressure profile; and (iv) Repeating steps (i), (ii), and (iii) to produce a plurality of alternative pressure profiles associated with the track of the historical weather event.
(i) Identifying a point of occurrence of an absolute pressure minimum along the track of the historical weather event;
(ii) Selecting an alternative pressure value at the point identified in step (i);
(iii) Adjusting pressure values at a plurality of other points along the track of the historical weather event, in accordance with the selected alternative pressure value, to create an alternative pressure profile; and (iv) Repeating steps (i), (ii), and (iii) to produce a plurality of alternative pressure profiles associated with the track of the historical weather event.
26. Method according to claim 24, characterized in that data representative of a plurality of alternative tracks are generated based on said track of the historical weather event, said data including a plurality of alternative points representative of geographical positions along said alternative tracks.
27. Method according to claim 26, characterized in that a plurality of alternative pressure profiles associated with at least some of said plurality of alternative tracks are generated.
28. Method according to claim 27, characterized in that said plurality of alternative pressure profiles associated with said plurality of alternative tracks are generated by:
(i) Identifying a point of occurrence of an absolute pressure minimum along one of said alternative tracks;
(ii) Selecting an alternative pressure value at the point identified in step (d);
(iii) Adjusting pressure values at a plurality of other points along said alternative track, in accordance with the selected alternative pressure value, to create an alternative pressure profile; and (iv) Repeating steps (i), (ii), and (iii) to produce a plurality of alternative pressure profiles associated with said plurality of alternative tracks.
(i) Identifying a point of occurrence of an absolute pressure minimum along one of said alternative tracks;
(ii) Selecting an alternative pressure value at the point identified in step (d);
(iii) Adjusting pressure values at a plurality of other points along said alternative track, in accordance with the selected alternative pressure value, to create an alternative pressure profile; and (iv) Repeating steps (i), (ii), and (iii) to produce a plurality of alternative pressure profiles associated with said plurality of alternative tracks.
29. Method according to claim 28, characterized in that a plurality of alternative pressure profiles associated with at least some of the plurality of alternative tracks are generated by:
(i) Identifying a pressure value at a first position along the historical track, and setting a pressure value at a corresponding position along an alternative track equal to the identified pressure value;
(ii) Determining a percentile of pressure change along the historical track between said first location and a second location;
(iii) Varying the percentile by a selected amount;
(iv) Determining a pressure value at a second location of the alternative track based upon the varied percentile;
(v) Repeating steps (i), (ii), (iii), and (iv) for additional points along the alternative track to create an alternative pressure profile associated with the alternative track; and (vi) Repeating steps (i), (ii), (iii), (iv), and (v) to create pressure profiles for other ones of the plurality of alternative tracks.
(i) Identifying a pressure value at a first position along the historical track, and setting a pressure value at a corresponding position along an alternative track equal to the identified pressure value;
(ii) Determining a percentile of pressure change along the historical track between said first location and a second location;
(iii) Varying the percentile by a selected amount;
(iv) Determining a pressure value at a second location of the alternative track based upon the varied percentile;
(v) Repeating steps (i), (ii), (iii), and (iv) for additional points along the alternative track to create an alternative pressure profile associated with the alternative track; and (vi) Repeating steps (i), (ii), (iii), (iv), and (v) to create pressure profiles for other ones of the plurality of alternative tracks.
30. Method according to claim 28, characterized in that the percentile is varied by approximately plus/minus fifteen percent.
31. Method according to claim 29, characterized in additional alternative pressure profiles are generated by means of the Monte-Carlo module by:
(i) selecting a different position along the historical track as a starting point, and/or (ii) varying the percentile by a different amount.
(i) selecting a different position along the historical track as a starting point, and/or (ii) varying the percentile by a different amount.
32. Method according to one of the claims 1 to 31, characterized in, that as basis for the scaling table the Saffir-Simpson Hurricane Scale is used.
33. System for automated location dependent tropical cyclone forecast, by means of which data records of weather events are generated and location dependent probability values for specific weather conditions associated with the tropical cyclone are determined, characterised, in that the system comprises a calculation module for assigning data records representative of an historical track of a weather event to a year of occurrence of said weather event and a memory module for saving the data records onto, said data records including a plurality of points representative of geographical positions and/or intensity of the event along the historical track, in that the system comprises a MonteCarlo-module for generating a plurality of new data records representative of alternative tracks for each historical track, wherein points of said new data records are generated from said points along the historical track by a dependent sampling process, in that the calculation module comprises means for establishing a grid over a geographical area of interest, said area including at least a portion of the plurality of historical tracks, and for generating a intensity climatology for selected cells in the grid, based upon the intensity data associated with at least some of the plurality of points along the historical tracks located within said selected grid cells, in that the system comprises a scaling table for generating a distribution for a definable time period of the data records of the historical tracks, which scaling table classifies the weather events by intensity and/or year of occurrence, and a filtering module for reproducing said distribution of said historical tracks within the new or accumulated data records according to their assigned year, in that the system comprises definable wind field profile for generating a wind field of each data record, and a interpolation-module for assigning a probability to each point in said grid, giving the probability of the occurrence of a specific wind strength at a given geographical location and time.
34. A computer program product which is able to be loaded in the internal memory of a digital computer and comprises software code sections with which the steps according to one of the claims 1 to 32 are able to be carried out when the product runs on a computer, the neural networks being able to be generated using software and/or hardware.
Applications Claiming Priority (3)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US10/787,791 US7219015B2 (en) | 2004-02-26 | 2004-02-26 | Methods for generating data set |
| US10/787,791 | 2004-02-26 | ||
| PCT/EP2004/050981 WO2005083471A1 (en) | 2004-02-26 | 2004-06-01 | Method and system for automated location dependent probabilistic tropical cyclone forecast |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CA2556985A1 true CA2556985A1 (en) | 2005-09-09 |
| CA2556985C CA2556985C (en) | 2010-10-19 |
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| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CA2556985A Active CA2556985C (en) | 2004-02-26 | 2004-06-01 | Method and system for automated location dependent probabilistic tropical cyclone forecast |
Country Status (10)
| Country | Link |
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| US (3) | US7219015B2 (en) |
| EP (1) | EP1721193B1 (en) |
| JP (1) | JP4512635B2 (en) |
| CN (1) | CN1922508B (en) |
| AT (1) | ATE362119T1 (en) |
| AU (1) | AU2004316579B2 (en) |
| CA (1) | CA2556985C (en) |
| DE (1) | DE602004006444T2 (en) |
| DK (1) | DK1721193T3 (en) |
| WO (1) | WO2005083471A1 (en) |
Families Citing this family (50)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7110884B2 (en) * | 2001-05-15 | 2006-09-19 | Earthworks Solutions, Inc. | Methods in the engineering design and construction of earthen fills |
| US20120078515A1 (en) * | 2002-09-16 | 2012-03-29 | Earthwork Solutions, Llc | Engineering design and construction of earthen fills |
| US8229766B2 (en) | 2004-07-30 | 2012-07-24 | Risk Management Solutions, Inc. | System and method for producing a flexible geographical grid |
| US7707050B2 (en) | 2004-03-11 | 2010-04-27 | Risk Management Solutions, Inc. | Systems and methods for determining concentrations of exposure |
| US7783543B2 (en) | 2004-12-21 | 2010-08-24 | Weather Risk Solutions, Llc | Financial activity based on natural peril events |
| US7783544B2 (en) | 2004-12-21 | 2010-08-24 | Weather Risk Solutions, Llc | Financial activity concerning tropical weather events |
| US7584133B2 (en) * | 2004-12-21 | 2009-09-01 | Weather Risk Solutions Llc | Financial activity based on tropical weather events |
| US7783542B2 (en) | 2004-12-21 | 2010-08-24 | Weather Risk Solutions, Llc | Financial activity with graphical user interface based on natural peril events |
| US7584134B2 (en) * | 2004-12-21 | 2009-09-01 | Weather Risk Solutions, Llc | Graphical user interface for financial activity concerning tropical weather events |
| US7693766B2 (en) | 2004-12-21 | 2010-04-06 | Weather Risk Solutions Llc | Financial activity based on natural events |
| WO2007056873A2 (en) * | 2005-11-15 | 2007-05-24 | Swiss Reinsurance Company | Automated trigger system with regenerative time-controlled trigger indices for monitoring devices in multi-stage coverage of damages systems for nascent and/or occurring cyclones and corresponding method |
| US7734245B2 (en) * | 2006-01-13 | 2010-06-08 | Sai Ravela | Statistical-deterministic approach to natural disaster prediction |
| US20070221743A1 (en) * | 2006-03-23 | 2007-09-27 | Weinzapfel Robert A | Methods of calculating impact time for storms |
| US20070225915A1 (en) * | 2006-03-23 | 2007-09-27 | Weinzapfel Robert A | Methods of characterizing storms |
| JP5044243B2 (en) * | 2007-03-08 | 2012-10-10 | 一般財団法人電力中央研究所 | Damage function creation method, apparatus and program, and typhoon damage prediction method, apparatus and program |
| US7970543B2 (en) * | 2008-03-18 | 2011-06-28 | The United States Of America, Represented By The Secretary Of Commerce | Predicting tropical cyclone destructive potential by integrated kinetic energy according to the Powell/Reinhold scale |
| US8204846B1 (en) | 2008-04-18 | 2012-06-19 | Wsi, Corporation | Tropical cyclone prediction system and method |
| US8160995B1 (en) | 2008-04-18 | 2012-04-17 | Wsi, Corporation | Tropical cyclone prediction system and method |
| US8224768B1 (en) | 2008-04-18 | 2012-07-17 | Wsi, Corporation | Tropical cyclone prediction system and method |
| US20100082253A1 (en) * | 2008-09-26 | 2010-04-01 | Buchanan William E | Strategic management system to stop the development of hurricanes and abate the intensity of tropical storms and hurricanes |
| US8983808B2 (en) * | 2008-10-15 | 2015-03-17 | The United States Of America, As Represented By The Secretary Of The Navy | Automated mesh generation and editing tools |
| US8655924B2 (en) * | 2008-10-15 | 2014-02-18 | The United States Of America, As Represented By The Secretary Of The Navy | System and method for providing structured data to a structured or unstructured grid |
| US8098542B2 (en) * | 2009-01-05 | 2012-01-17 | Pgs Geophysical As | Combined electromagnetic and seismic acquisition system and method |
| US8346682B2 (en) * | 2009-01-23 | 2013-01-01 | The United States Of America, As Represented By The Secretary Of The Navy | Information assisted visual interface, system, and method for identifying and quantifying multivariate associations |
| US8280633B1 (en) | 2009-02-10 | 2012-10-02 | Strategic Design Federation W, Inc. | Weather risk estimation system and method |
| US10068178B2 (en) * | 2010-01-13 | 2018-09-04 | Oath, Inc. | Methods and system for associating locations with annotations |
| WO2011088473A2 (en) * | 2010-01-18 | 2011-07-21 | The Regents Of The University Of California | System and method for identifying patterns in and/or predicting extreme climate events |
| BR112012017807A8 (en) * | 2010-01-19 | 2017-10-10 | Swiss reinsurance co ltd | method and system for automated location-dependent natural disaster detection and prediction |
| CN101933448B (en) * | 2010-07-26 | 2012-09-05 | 北京师范大学 | Method for manufacturing tropical cyclone wind zone |
| US9230219B2 (en) * | 2010-08-23 | 2016-01-05 | Institute Of Nuclear Energy Research Atomic Energy Council, Executive Yuan | Wind energy forecasting method with extreme wind speed prediction function |
| CN102132662B (en) * | 2011-01-10 | 2012-10-17 | 北京师范大学 | Improved method for making tropical cyclone wind zone |
| WO2013126866A1 (en) | 2012-02-24 | 2013-08-29 | B3, Llc | Systems and methods for comprehensive insurance loss management and loss minimization |
| FR2990681B1 (en) * | 2012-05-16 | 2014-06-13 | Ingenierie De Rech S Et D Etudes En Hydrodynamique Navale Par Abreviation Sirehna Soc D | METHOD FOR PREDICTING AT LEAST ONE MOVEMENT OF A SHIP UNDER THE EFFECT OF THE WAVE |
| CN102681035B (en) * | 2012-05-18 | 2013-12-25 | 福建四创软件有限公司 | Method for realizing error prediction by combining tangent method and tropical cyclone prediction path |
| CN103955009B (en) * | 2014-04-25 | 2016-03-09 | 宁波市气象台 | A kind of method extracting Objective Typhoon forecast information from numerical forecasting product |
| KR101646587B1 (en) * | 2014-08-19 | 2016-08-10 | 울산과학기술원 | Hybrid seasonal prediction of the Western North Pacific Tropical Cyclone Activity |
| CN104965993B (en) * | 2015-07-17 | 2019-01-25 | 南京信息工程大学 | A kind of hybrid perturbation method based on sized set transform |
| CN105425320B (en) * | 2015-11-10 | 2018-01-05 | 中国科学院深圳先进技术研究院 | Tropical cyclone triggers the probability forecast method and system of coastal area strong wind |
| CN106570215B (en) * | 2016-10-13 | 2019-08-06 | 北京航空航天大学 | A kind of tropical cyclone dynamic emulation method based on time-varying meteorological data |
| CN108427834A (en) * | 2018-02-13 | 2018-08-21 | 中国气象科学研究院 | Engineering typhoon fining numerical simulation system based on mesoscale model and method |
| CN109086540B (en) * | 2018-08-14 | 2022-11-11 | 中国科学院遥感与数字地球研究所 | Method and device for constructing tropical cyclone path forecasting model |
| CN109325960B (en) * | 2018-11-20 | 2021-07-09 | 南京信息工程大学 | Infrared cloud chart cyclone analysis method and analysis system |
| CN109444989B (en) * | 2018-12-28 | 2020-07-07 | 中山大学 | Typhoon forecasting method, typhoon forecasting system, readable storage medium and readable storage equipment |
| CN109993282B (en) * | 2019-03-28 | 2020-06-12 | 北京航空航天大学 | Typhoon wave and range prediction method |
| CN111220786A (en) * | 2020-03-09 | 2020-06-02 | 生态环境部华南环境科学研究所 | Method for rapidly monitoring organic pollution of deep water sediments |
| CN111427100B (en) * | 2020-03-30 | 2021-09-03 | 广州数鹏通科技有限公司 | Typhoon center positioning method and device and typhoon path generation method |
| CN111523087B (en) * | 2020-04-10 | 2021-04-16 | 北京航空航天大学 | Typhoon intensity long-term change trend analysis method |
| CN112394424B (en) * | 2020-09-28 | 2022-04-26 | 南京信息工程大学 | Method for monitoring regional extreme rainfall event |
| WO2022266910A1 (en) * | 2021-06-24 | 2022-12-29 | 清华大学 | Typhoon activity prediction method and apparatus, device, and storage medium |
| CN113344136B (en) * | 2021-07-06 | 2022-03-15 | 南京信息工程大学 | Novel anticyclone objective identification method based on Mask R-CNN |
Family Cites Families (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6493633B2 (en) * | 1996-06-04 | 2002-12-10 | Robert O. Baron, Sr. | Systems and methods for distributing real-time site specific weather information |
| JP3226468B2 (en) * | 1996-11-29 | 2001-11-05 | 東京海上火災保険株式会社 | Damage assessment system due to wind disaster |
| US5978738A (en) * | 1997-02-13 | 1999-11-02 | Anthony Brown | Severe weather detector and alarm |
| US7424409B2 (en) * | 2001-02-20 | 2008-09-09 | Context-Based 4 Casting (C-B4) Ltd. | Stochastic modeling of time distributed sequences |
| JP2002296362A (en) * | 2001-03-29 | 2002-10-09 | Songai Hokenryoritsu Santeikai | System and method of evaluating damages due to wind by typhoon composited using stochastic technique |
| JP2003085361A (en) * | 2001-07-03 | 2003-03-20 | Tokio Marine & Fire Insurance Co Ltd | Design support system, computer program, and method for derivative |
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| US20070093964A1 (en) | 2007-04-26 |
| US7219015B2 (en) | 2007-05-15 |
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| CN1922508B (en) | 2010-05-05 |
| EP1721193A1 (en) | 2006-11-15 |
| AU2004316579A1 (en) | 2005-09-09 |
| US7359799B2 (en) | 2008-04-15 |
| CA2556985C (en) | 2010-10-19 |
| US20050192751A1 (en) | 2005-09-01 |
| JP4512635B2 (en) | 2010-07-28 |
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