Trusted decision support system and method
Methods and apparatus for providing a comprehensive decision support system to include predictions, recommendations with consequences and optimal follow-up actions in specific situations are described. Data is obtained from multiple disparate data sources, depending on the information deemed necessary for the situation being modeled. Some embodiments perform complex systems modeling including performing massive correlative analyses of the data obtained from the multiple disparate data sources with current situational data obtained regarding the situation for which the decision support process is being utilized. The decision support system provides a prediction or predictions and a recommendation or a choice of recommendations based on the correlative analysis and/or other analyses. In some embodiments the decision support system provides possible consequences that could result from a recommendation. In other embodiments the decision support system provides a list of tasks for acting upon a recommendation. Also described are methods and apparatus for developing application specific decision support models. The decision support model development process may include identifying multiple disparate data sources for retrieval of related information, selection of classification variables to be retrieved from the data sources, assignment of weights to each classification variable, selecting and/or defining rules, and selecting and/or defining analysis functions.
1 . A system comprising:
an electronic device configured to select a data set for an application area, to assign weighted scores to the data in the data set, to correlate the weighted data set with one or more previously correlated weighted data sets, and to determine, based upon the correlation, a recommended action as a response to an event related to the data set.
2 . The system of claim 1 , further comprising a statistical analysis engine configured to perform statistical analysis on the data set.
3 . The system of claim 1 , further comprising a statistical analyses engine configured to be programmed with one or more models, wherein each model comprises mathematical instructions for processing the data set.
4 . The system of claim 3 , wherein the mathematical instructions comprise weights to be assigned to the data set according to at least one of a source from which the data set was received and an age of the data set.
5 . The system of claim 3 , wherein the mathematical instructions comprise at least one of fuzzy logic instructions, Bayesian analyses instructions, neural network analyses instructions, probability calculation instructions, mean calculation instructions, confidence interval calculation instructions, Z-test instructions, T-test instructions, autoregressive modeling instructions, and residual analysis instructions for multiple regression.
6 . A system comprising:
a sensor network;
a database comprising data from the sensor network; and
a electronic device configured to select a data set from the database for an application area, to assign weighted scores to the data in the data set, to correlate the weighted data set with one or more previously correlated weighted data sets, and to determine, based upon the correlation, a recommended action as a response to an event related to the data set.
7 . The system of claim 6 , further comprising a statistical analysis engine configured to perform statistical analysis on the data set.
8 . The system of claim 6 , further comprising a statistical analyses engine configured to be programmed with one or more models, wherein each model comprises mathematical instructions for processing the data set.
9 . The system of claim 8 , wherein the mathematical instructions comprise weights to be assigned to the data set according to at least one of a source from which the data set was received and an age of the data set.
10 . The system of claim 8 , wherein the mathematical instructions comprise at least one of fuzzy logic instructions, Bayesian analyses instructions, neural network analyses instructions, probability calculation instructions, mean calculation instructions, confidence interval calculation instructions, Z-test instructions, T-test instructions, autoregressive modeling instructions, and residual analysis instructions for multiple regression.
11 . A system comprising:
an electronic device configured to select a data set for an application area, the electronic device further configured to analyze the data set according to fuzzy logic instructions so as to generate a recommended action and outcome information for the recommended action.
12 . The system of claim 11 , further comprising a statistical analysis engine configured to perform statistical analysis on the data set.
13 . The system of claim 11 , further comprising a statistical analyses engine configured to be programmed with one or more models, wherein each model comprises mathematical instructions for processing the data set.
14 . The system of claim 13 , wherein the mathematical instructions comprise weights to be assigned to the data set according to at least one of a source from which the data set was received and an age of the data set.
15 . The system of claim 13 , wherein the mathematical instructions comprise at least one of fuzzy logic instructions, Bayesian analyses instructions, neural network analyses instructions, probability calculation instructions, mean calculation instructions, confidence interval calculation instructions, Z-test instructions, T-test instructions, autoregressive modeling instructions, and residual analysis instructions for multiple regression.
16 . A system comprising:
an electronic device configured to select a data set for an application area, the electronic device further configured to analyze the data set according to statistical analysis instructions so as to generate a recommended action and outcome information for the recommended action.
17 . The system of claim 16 , further comprising a statistical analyses engine configured to be programmed with one or more models, wherein each model comprises mathematical instructions for processing the data set.
18 . The system of claim 17 , wherein the mathematical instructions comprise weights to be assigned to the data set according to at least one of a source from which the data set was received and an age of the data set.
19 . The system of claim 17 , wherein the mathematical instructions comprise at least one of fuzzy logic instructions, Bayesian analyses instructions, neural network analyses instructions, probability calculation instructions, mean calculation instructions, confidence interval calculation instructions, Z-test instructions, T-test instructions, autoregressive modeling instructions, and residual analysis instructions for multiple regression.