WO2000063789A3 - Method for prognosing the course of a data sequence and device for carrying out said method - Google Patents

Method for prognosing the course of a data sequence and device for carrying out said method Download PDF

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Publication number
WO2000063789A3
WO2000063789A3 PCT/EP2000/002784 EP0002784W WO0063789A3 WO 2000063789 A3 WO2000063789 A3 WO 2000063789A3 EP 0002784 W EP0002784 W EP 0002784W WO 0063789 A3 WO0063789 A3 WO 0063789A3
Authority
WO
WIPO (PCT)
Prior art keywords
course
data sequence
prognosing
carrying
influencing variables
Prior art date
Application number
PCT/EP2000/002784
Other languages
German (de)
French (fr)
Other versions
WO2000063789A2 (en
Inventor
Martin Kuehrer
Original Assignee
Siemens Ag Oesterreich
Martin Kuehrer
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Siemens Ag Oesterreich, Martin Kuehrer filed Critical Siemens Ag Oesterreich
Priority to AU42916/00A priority Critical patent/AU4291600A/en
Publication of WO2000063789A2 publication Critical patent/WO2000063789A2/en
Publication of WO2000063789A3 publication Critical patent/WO2000063789A3/en

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/08—Insurance
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/049—Temporal neural networks, e.g. delay elements, oscillating neurons or pulsed inputs
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G06N3/086—Learning methods using evolutionary algorithms, e.g. genetic algorithms or genetic programming

Abstract

The invention relates to a method for prognosing the course of a data sequence. Said prognosis is made by means of a neuronal network on the basis of the course of presumed influencing variables. A set of influencing variables is selected from the presumed influencing variables by applying a genetic algorithm. Said set of influencing variables constitutes the input values of the neuronal network for the prognosis of the further course of the data sequence.
PCT/EP2000/002784 1999-04-16 2000-03-30 Method for prognosing the course of a data sequence and device for carrying out said method WO2000063789A2 (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
AU42916/00A AU4291600A (en) 1999-04-16 2000-03-30 Method for prognosing the course of a data sequence and device for carrying out said method

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
AT68499 1999-04-16
ATA684/99 1999-04-16

Publications (2)

Publication Number Publication Date
WO2000063789A2 WO2000063789A2 (en) 2000-10-26
WO2000063789A3 true WO2000063789A3 (en) 2001-03-22

Family

ID=3497097

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/EP2000/002784 WO2000063789A2 (en) 1999-04-16 2000-03-30 Method for prognosing the course of a data sequence and device for carrying out said method

Country Status (2)

Country Link
AU (1) AU4291600A (en)
WO (1) WO2000063789A2 (en)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US10242407B1 (en) 2013-09-24 2019-03-26 Innovative Market Analysis, LLC Financial instrument analysis and forecast

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP0528399A2 (en) * 1991-08-19 1993-02-24 Toyoda Koki Kabushiki Kaisha Method and apparatus for learning of neural network
WO1996024033A1 (en) * 1995-01-31 1996-08-08 Matsushita Electric Industrial Co., Ltd. Proportion predicting system and method of making mixture
US5727128A (en) * 1996-05-08 1998-03-10 Fisher-Rosemount Systems, Inc. System and method for automatically determining a set of variables for use in creating a process model

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP0528399A2 (en) * 1991-08-19 1993-02-24 Toyoda Koki Kabushiki Kaisha Method and apparatus for learning of neural network
WO1996024033A1 (en) * 1995-01-31 1996-08-08 Matsushita Electric Industrial Co., Ltd. Proportion predicting system and method of making mixture
US5727128A (en) * 1996-05-08 1998-03-10 Fisher-Rosemount Systems, Inc. System and method for automatically determining a set of variables for use in creating a process model

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
FURUHASHI T ET AL: "Evolutionary fuzzy modeling using fuzzy neural networks and genetic algorithm", PROCEEDINGS OF IEEE INTERNATIONAL CONFERENCE ON EVOLUTIONARY COMPUTATION, 13 April 1997 (1997-04-13), XP002115857 *
HINES J W ET AL: "Signal validation using an adaptive neural fuzzy inference system", NUCLEAR TECHNOLOGY,US,AMERICAN NUCLEAR SOCIETY, LA GRANGE PARK, IL, vol. 119, no. 2, August 1997 (1997-08-01), pages 181 - 193, XP002115856, ISSN: 0029-5450 *

Also Published As

Publication number Publication date
WO2000063789A2 (en) 2000-10-26
AU4291600A (en) 2000-11-02

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