| 主权项 |
1. A system for accurate and detailed modeling of systems with large and complex datasets using a distributed simulation engine comprising:
a business data retrieval engine stored in a memory of and operating on a processor of a computing device; a business data analysis engine stored in a memory of and operating on a processor of a computing device; and an automated planning and value at risk estimation module stored in a memory of and operating on a processor of one of more computing devices; an action outcome simulation module stored in the memory of and operating on a processor of one or more computing devices; wherein, the business information retrieval engine:
(a) retrieves a plurality of business related data from a plurality of sources;(b) accept a plurality of analysis parameters and control commands directly from human interface devices or from one or more command and control storage devices; and(c) stores accumulated retrieved information for processing by data analysis engine or predetermined data timeout; wherein the business information analysis engine:
(d) retrieves a plurality of data types from the business information retrieval engine; and(e) performs a plurality of analytical functions and transformations on retrieved data based upon the specific goals and needs set forth in a current campaign by business process analysis authors; wherein the automated planning and value at risk estimation module:
(f) employs results of data analyses and transformations performed by the business information analysis engine, together with available supplemental data from a plurality of sources as well as any current campaign specific machine learning, commands and parameters from business process analysis authors to formulate current business planning and risk status reports; and(g) employs results of data analyses and transformations performed by the business information analysis engine, together with available supplemental data from a plurality of sources, any current campaign specific commands and parameters from business process analysis authors, as well as input gleaned from machine learned algorithms to deliver business decision pathway simulations and business value at risk support to a first end user; wherein, the action outcome simulation module:
(h) retrieves at least a portion of the results of data analyses and transformations performed by the business information analysis engine;(i) retrieves at least one piece of raw data from the business information retrieval engine;(j) employs a plurality of parameters entered from the automated planning and value at risk estimation module;(k) uses information obtained to execute predictive simulations of business venture or business decision progress pathway and outcome as originally initialized by simulation author using a simulation method that combines system dynamics method, discrete event method, or agent based method for at least one simulation instance;(l) employs groupings of action profile data and configuration parameters to create computer based models of real-world items to act in the simulation. |
