1. A means for creating optimized elements of a device, comprising: (a) selecting an equation or set equations that models the behavior of the elements of a device; (b) selecting a range for each input variable in said equation or set of equations; (c) selecting the number of trials; (d) selecting the logical distribution function of each of the said input variables; (e) selecting at least two fuzzy level boundaries for each of the said phenomenon; (f) generating values for all of said input variables of all of said trials, within said input variable's said range and within said logical distribution, using Monte Carlo simulations; (g) solving said equation or equations to produce outputs to produce a Meta Model; (h) increasing or decreasing the generated values of one of said input variables by fixed increments for each of said trials; (i) solving said equation or equations using the incremented or decremented values of one of said input values; (j) identifying the fuzzy level placement within said fuzzy level boundary for each of said outputs generated using said incremented or decremented input values for each of said trials; (k) calculating the probability of said fuzzy level placement for one of said outputs by dividing the number of said outputs at each of the said fuzzy levels by the number of said trials; (l) categorizing said fuzzy level placements for said output as indicating a positive or negative correlation; (m) categorizing the magnitude of said fuzzy level placement when there are more than two of the said fuzzy level boundaries; (n) repeating the process steps h through m for each of the remaining input variables; (o) mapping said correlations and said probabilities of the relationships between said input variables and phenomena in the form of a fuzzy cognitive map; and (p) adjusting the characteristics of said elements of said device, in accordance with said fuzzy cognitive map.
1. A means for creating optimized elements of a device, comprising: (a) selecting an equation or set equations that models the behavior of the elements of a device; (b) selecting a range for each input variable in said equation or set of equations; (c) selecting the number of trials; (d) selecting the logical distribution function of each of the said input variables; (e) selecting at least two fuzzy level boundaries for each of the said phenomenon; (f) generating values for all of said input variables of all of said trials, within said input variable's said range and within said logical distribution, using Monte Carlo simulations; (g) solving said equation or equations to produce outputs to produce a Meta Model; (h) increasing or decreasing the generated values of one of said input variables by fixed increments for each of said trials; (i) solving said equation or equations using the incremented or decremented values of one of said input values; (j) identifying the fuzzy level placement within said fuzzy level boundary for each of said outputs generated using said incremented or decremented input values for each of said trials; (k) calculating the probability of said fuzzy level placement for one of said outputs by dividing the number of said outputs at each of the said fuzzy levels by the number of said trials; (l) categorizing said fuzzy level placements for said output as indicating a positive or negative correlation; (m) categorizing the magnitude of said fuzzy level placement when there are more than two of the said fuzzy level boundaries; (n) repeating the process steps h through m for each of the remaining input variables; (o) mapping said correlations and said probabilities of the relationships between said input variables and phenomena in the form of a fuzzy cognitive map; and (p) adjusting the characteristics of said elements of said device, in accordance with said fuzzy cognitive map. 7. A means for creating optimized elements of a device as in claim 1 , wherein said device is magnetic.