CONSERVATION MODELING ENGINE FRAMEWORK

摘要

Methods, including service methods, articles of manufacture, systems, articles and programmable devices provide a conservation modeling engine framework. Programmable conservation modeling engines in communication with different customizable resource conservation modules, each resource conservation module customized to a distinct resource, select one of the modules customized to a resource identified for conservation, and user-defined criteria as a function of the identified resource and the selected module. Input data is selected and collected as a function of the resource identified and the selected module and used to weight the input data. Different optimized conservation plans are created as a function of the weighted input data and the selected module, each of the optimized conservation plans displayed having a different implementation cost, a different time for implementation and a different total amount of the identified resource saved.

主权项

1. A computer implemented method for conservation modeling, the method comprising executing on a processor the steps of:
creating a plurality of different conservation plans for a region for a future time period as a function of a determined rate of change of availability of a resource identified for conservation, wherein the plurality of conservation plans includes a first plan that has a least implementation cost relative to implementation costs of a second plan and a third plan of the plurality of conservation plans, the second plan that has a fastest time for implementation relative to times for implementation of the first plan and the third plan, and the third plan that conserves a most amount of the resource identified for conservation relative to amounts of the resource identified for conservation that are conserved by the first plan and the second plan; optimizing the first, second and third plans via at least one of a greedy algorithm, a penalty method algorithm and a cooperative optimization; predicting via a Monte Carlo methodology future values of an input variable at an execution time of the first, second and third plans; and modifying the optimized first, second and third plans to meet a threshold as a function of the predicted future value of the input variable.