ENHANCED CONSISTENCY IN GEOLOGICAL RISK ASSESSMENT THROUGH CONTINUOUS MACHINE LEARNING

• Main Authors: Casacão, João Pedro, Flach, Bruno da Costa, Silva, Francisco José Cordeiro, de Mello Brandao, Rafael Rossi, Cersósimo, Dario Sergio, Mendes, Carlos Raoni de Alencar, Fernandes, Susana de Lurdes Alve, Fontoura de Gusmão Cerqueira, Renato, André Libório, Carolina, Ribeiro de Almeida, Joana de Noronha
• Format: Patent
• Language: English
• Published: 26.03.2020
• Subjects: CALCULATING; COMPUTING; COUNTING; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES; PHYSICS; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR

Geological risk assessment includes receiving a first set of geological factors associated with a first site. Data pertaining to at least one second site with a second set of geological factors similar to first set of geological factors of the first site is retrieved. A user input indicating a comparison of the first set of geological factors to the second set of geological factors received, and a level of knowledge of the first site is determined based upon the comparison. A suggested probability of success for the first site is determined based upon the level of knowledge. A probability of success is determined for each of the geological factors of the second set of geological factors. A probability of success for the first site is determined. The probability of success of the first site is assessed based upon the level of knowledge of the first site, the suggested probability of success for the first site, and the probability of success for each of the second set of geological factors.