# US 2018/0025102 A1 · Method for creating multivariate predictive models of oyster populations > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2018/0025102 A1 - Document ID: US20180025102A1 - Status: Published application - Kind: A1 - Application number: 15/479,080 - Filed: 2017-04-04 - Published: 2018-01-25 - Earliest claimed: 2016-07-22 - Assignees: The United States of America as represented by the Secretary of the Army - Applicants: United States of America as Represented by The Secretary of The Army - Inventors: Michael E Kjelland; Todd M Swannack; Candice D Piercy - Web page: https://patentgrep.com/patent/US20180025102A1 ## CPC - G06F 30/20: Design optimisation, verification or simulation (optimisation, verification or simulation of circuit designs G06F30/30) - G06F 16/212: {with details for data modelling support} - G06F 17/18: for evaluating statistical data {, e.g. average values, frequency distributions, probability functions, regression analysis (forecasting specially adapted for a specific administrative, business or logistic context G06Q10/04)} - G06F 17/40: Data acquisition and logging (for input to computer G06F3/00) - G06F 40/44: Statistical methods, e.g. probability models - G06N 7/04: Physical realisation - G06Q 10/00: Administration; Management - G06Q 10/04: Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" (market predictions or forecasting for commercial activities G06Q30/0202) - G06Q 50/02: Agriculture; Fishing; Forestry; Mining - A61B 2503/40: Animals - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS - 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 - A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D) ## Abstract A method for Multivariate Predictive Modeling simulates the impact of numerous environmental, life-cycle, and policy-based variables on oyster populations in real time by instantiating Oyster Group Demographic Objects and Reef Objects which function as independent processing components. The method creates novel interactive digital replicas of oyster population and reef entities which may be updated in real time to model environmental impacts on oyster population growth. ## Claims ### Claim 1 A method for creating a Multivariate Predictive Model of oyster population impacts comprised of the steps of: (a) instantiating a Project with project parameters which include geographical parameters and a time parameter; (b) instantiating a Reef Object with Reef Attributes and Reef processor functions for updating Reef Attribute values; (c) instantiating a Oyster Group Demographic (OGD) Object with OGD Attributes and OGD processor functions for updating OGD Attribute values; and (d) associating said OGD Objects with said Reef Objects to create a State Model that is a digital representation of one or more reefs having a demographically distributed oyster population. ### Claim 2 (depends on 1) The method of claim 1 which further includes the step of receiving input values to update said OGD Attribute values and said Reef Attribute values to create a Multivariate Predictive Model. ### Claim 3 (depends on 2) The method of claim 2 wherein said input values are field data. ### Claim 4 (depends on 2) The method of claim 2 wherein said input values are automatically calculated values. ### Claim 5 (depends on 1) The method of claim 1 which further includes the step of selecting said OGD Attributes from a group of OGD Attribute categories consisting of survivor values, reproduction, dispersal, larvae settling values, gender, gender transition, age, health, shell size, energy utilization capability, spawning growth, disease vulnerability, predator vulnerability. ### Claim 6 (depends on 2) The method of claim 2 wherein at least one attribute of said Multivariate Predictive Model may be compared to at least one attribute of another Multivariate Predictive Model in real time. ### Claim 7 (depends on 1) The method of claim 1 wherein steps (a) through (d) are iteratively performed. ### Claim 8 (depends on 7) The method of claim 7 which further includes performing (a) through (d) for successive time periods within said time parameter of said Project. ### Claim 9 (depends on 1) The method of claim 1 which further includes the step of instantiating a Multivariate Reef Density Model, wherein said Multivariate Reef Density Model includes high reef parameters, low reef parameters and functions to update said high reef parameters and said low reef parameters based on said user input which includes interval values and oyster age cohort parameter values. ### Claim 10 (depends on 1) The method of claim 1 which further includes the step of instantiating a Multivariate Reef Biomass Model, wherein said Multivariate Reef Biomass Model includes high reef parameters, low reef parameters and functions to associate said high and low reef parameters with time interval parameter values and oyster age cohort parameter values. ### Claim 11 (depends on 1) The method of claim 1 which further includes the step of instantiating a Growth Rate Matrix Object which models energy assimilation based on said OGD Attribute values selected from a group including total duration salinity, age and duration of exposure. ### Claim 12 (depends on 1) The method of claim 1 which further includes the step of instantiating a Growth Rate Matrix Object which models energy assimilation based on said OGD Attribute values selected from a group consisting of Dissolved Oxygen, age and duration of exposure. ### Claim 13 (depends on 1) The method of claim 1 which further includes the step of creating a Growth Rate Matrix Object which correlates energy assimilation to total suspended solids, age and duration of exposure. ### Claim 14 (depends on 1) The method of claim 1 which further includes the step of calculating baseline growth rate attribute for said OGD Object. ### Claim 15 (depends on 14) The method of claim 14 which further includes updating said baseline growth rate attribute to reflect an oyster size range. ### Claim 16 (depends on 1) The method of claim 1 which further includes the step of calculating baseline reproductive rate attribute for said OGD Object, wherein said baseline reproductive rate is a function of a salinity on overall reproduction. ### Claim 17 (depends on 1) The method of claim 1 which further includes the step of calculating baseline reproductive rate attribute for said OGD Object, wherein said baseline reproductive rate is a function of a total suspended solids on overall reproduction. ### Claim 18 (depends on 1) The method of claim 1 which further includes the step of calculating baseline reproductive rate attribute for said OGD Object, wherein said baseline reproductive rate is a function of a Dissolved Oxygen (DO) on overall reproduction. ### Claim 19 (depends on 1) The method of claim 1 which further includes the step of calculating baseline reproductive rate attribute for said OGD Object, wherein said baseline reproductive rate is a function of temperature on overall reproduction. ### Claim 20 (depends on 1) The method of claim 1 which further includes the step creating a Probability of Mortality Model by correlating salinity threshold and duration of exposure. ### Claim 21 (depends on 1) The method of claim 1 which further includes the step creating a Probability of Mortality Model by correlating total suspended solids and duration of exposure. ### Claim 22 (depends on 1) The method of claim 1 which further includes the step creating a Probability of Mortality Model by correlating temperature and duration of exposure. ### Claim 23 (depends on 1) The method of claim 1 which further includes the step of instantiating a Probability of Mortality Model by correlating Dissolved Oxygen and duration of exposure. ### Claim 24 (depends on 1) The method of claim 1 which further includes the step of instantiating a larvae Dispersal Matrix using input from a particle tracking model to approximate the percentage of oyster larvae moving from one reef to another.