FR3143802B3 - Détection d’anomalies dans les données billettiques de transport en commun - Google Patents

Détection d’anomalies dans les données billettiques de transport en commun Download PDF

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FR3143802B3
FR3143802B3 FR2213419A FR2213419A FR3143802B3 FR 3143802 B3 FR3143802 B3 FR 3143802B3 FR 2213419 A FR2213419 A FR 2213419A FR 2213419 A FR2213419 A FR 2213419A FR 3143802 B3 FR3143802 B3 FR 3143802B3
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ticketing data
data
preprocessing
tabular
test
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FR2213419A
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FR3143802A3 (fr
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Stéphane Duguet
Bilal Ladjelate
Rodolphe Lampe
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Hitachi Rail RCS France SAS
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Revenue Collection Systems France SAS
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Priority to FR2213419A priority Critical patent/FR3143802B3/fr
Priority to PCT/EP2023/086056 priority patent/WO2024126790A1/fr
Publication of FR3143802A3 publication Critical patent/FR3143802A3/fr
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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; 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
    • G06Q30/00—Commerce
    • G06Q30/018—Certifying business or products
    • G06Q30/0185—Product, service or business identity fraud
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; 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
    • G06N3/0464—Convolutional networks [CNN, ConvNet]
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; 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
    • G06N3/088—Non-supervised learning, e.g. competitive learning
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; 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
    • G06Q20/00—Payment architectures, schemes or protocols
    • G06Q20/38—Payment protocols; Details thereof
    • G06Q20/40—Authorisation, e.g. identification of payer or payee, verification of customer or shop credentials; Review and approval of payers, e.g. check credit lines or negative lists
    • G06Q20/401—Transaction verification
    • G06Q20/4016—Transaction verification involving fraud or risk level assessment in transaction processing
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; 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
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/40—Business processes related to the transportation industry
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; 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
    • G06N3/048—Activation functions
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00—Computing arrangements using knowledge-based models
    • G06N5/04—Inference or reasoning models
    • G06N5/045—Explanation of inference; Explainable artificial intelligence [XAI]; Interpretable artificial intelligence
    • G—PHYSICS
    • G07—CHECKING-DEVICES
    • G07B—TICKET-ISSUING APPARATUS; FARE-REGISTERING APPARATUS; FRANKING APPARATUS
    • G07B15/00—Arrangements or apparatus for collecting fares, tolls or entrance fees at one or more control points
    • G07B15/02—Arrangements or apparatus for collecting fares, tolls or entrance fees at one or more control points taking into account a variable factor such as distance or time, e.g. for passenger transport, parking systems or car rental systems
    • G—PHYSICS
    • G07—CHECKING-DEVICES
    • G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
    • G07C9/00—Individual registration on entry or exit
    • G07C9/10—Movable barriers with registering means

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  • Engineering & Computer Science (AREA)
  • Business, Economics & Management (AREA)
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  • Development Economics (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)
  • Complex Calculations (AREA)
  • Testing And Monitoring For Control Systems (AREA)
  • Debugging And Monitoring (AREA)

Abstract

Détection d’anomalies dans les données billettiques de transport en commun L’invention concerne un procédé (34) de détection d’anomalies de données billettiques comprenant au moins une phase d’apprentissage (P1) comprenant les étapes suivantes, appliquées à des données billettiques tabulaires d’entrainement : - prétraitement et sélection (36) de colonnes de données d’intérêt prédéterminées ; - apprentissage profond (38) d’un réseau de neurones avec les données billettiques d’entrainement optimisées par ledit prétraitement et obtention d’un modèle dudit réseau de neurones configuré pour détecter une anomalie ; et au moins une phase d’inférence (P2) comprenant les étapes suivantes, appliquées à des données billettiques tabulaires test ; - application (40) dudit prétraitement et de ladite sélection de colonnes de données d’intérêt prédéterminées auxdites données billettiques tabulaires test ; - obtention (42) d’un score correspondant à un niveau d’anomalie desdites données billettiques tabulaires test par application dudit modèle auxdites données billettiques test optimisées par ledit prétraitement. Figure pour l'abrégé : Figure 2
FR2213419A 2022-12-15 2022-12-15 Détection d’anomalies dans les données billettiques de transport en commun Active FR3143802B3 (fr)

Priority Applications (2)

Application Number Priority Date Filing Date Title
FR2213419A FR3143802B3 (fr) 2022-12-15 2022-12-15 Détection d’anomalies dans les données billettiques de transport en commun
PCT/EP2023/086056 WO2024126790A1 (fr) 2022-12-15 2023-12-15 Détection d'anomalies dans les données billettiques de transport en commun

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
FR2213419A FR3143802B3 (fr) 2022-12-15 2022-12-15 Détection d’anomalies dans les données billettiques de transport en commun
FR2213419 2022-12-15

Publications (2)

Publication Number Publication Date
FR3143802A3 FR3143802A3 (fr) 2024-06-21
FR3143802B3 true FR3143802B3 (fr) 2025-01-17

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FR2213419A Active FR3143802B3 (fr) 2022-12-15 2022-12-15 Détection d’anomalies dans les données billettiques de transport en commun

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FR (1) FR3143802B3 (fr)
WO (1) WO2024126790A1 (fr)

Family Cites Families (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5819226A (en) * 1992-09-08 1998-10-06 Hnc Software Inc. Fraud detection using predictive modeling
US6119103A (en) * 1997-05-27 2000-09-12 Visa International Service Association Financial risk prediction systems and methods therefor
WO2005077066A2 (fr) * 2004-02-09 2005-08-25 American Express Travel Related Services Company, Inc. Systeme et procede dans lesquels sont utilisees des donnees d'autorisation ameliorees afin de reduire la fraude dans des transactions de voyage
US7731086B2 (en) * 2005-06-10 2010-06-08 American Express Travel Related Services Company, Inc. System and method for mass transit merchant payment
US8763902B2 (en) * 2006-12-07 2014-07-01 Smart Systems Innovations, Llc Mass transit fare processing system
US8256666B2 (en) * 2007-01-30 2012-09-04 Phil Dixon Processing transactions of different payment devices of the same issuer account
WO2011006142A1 (fr) * 2009-07-09 2011-01-13 Cubic Corporation Application d'identification pour dispositif mobile fonctionnant par communication en champ proche

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Publication number Publication date
FR3143802A3 (fr) 2024-06-21
WO2024126790A1 (fr) 2024-06-20

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