Dezert-Smarandache Theory (DSmT

Scilogs, V: joining the dots

The DM becomes then more and more complicated, of complexity of rank 3 - 4. By the way, we may have dynamicity with respect to many factors / parameters, such as: time, decision makers, variation of neutrosophic components, type of aggregation operator, etc. All parameters influencing the decision making, combined together, take a single decision at time t1, afterwards at time t2, etc.

Dezert-Smarandache Theory (DSmT)

DSmT uses the included middle in the hybrid models, while the neutrosophic logic/set/probability in the indeterminate component (which is neither true nor false). One can adjust the fusion rules from independent sources to dependent sources. For example, one can have two sources m1 and m2 that are d% dependent. Then one can combine their masses taking into account their dependency. À Jean Dezert Les auteurs approximent la PCR5 avec des fonctions convexes (“An evidence clustering DSmT approximate reasoning method based on convex functions analysis”, par

Q Guo, Y He, X Guan, L Deng, L Pan, T Jian - Digital Signal

Processing, 2015).

Ils disent que c'est plus facile de faire cette approximation (qui est 99% accurate) que de calculer la PCR5. Je le pense pas, mais comme même la methode était differente des autres (jvd, de faire des approximations des fusions)... Donc, j'ai recommendé sa publication. On poura (une idee qui m'est venue) approximer la fusion de m1 et m2 en general... Qu'en penses-toi? Le deuxieme article (“Score-Level Fusion of Face and Voice

Using Particle Swarm Optimization and Belief Functions”, par Mezai, L. ; Hachouf, F., IEEE Transactions on Human-

Machine, 2015) combine, la DST avec la PCR5... Donc

DST + DSmT. Je me rappelle, quand on a presenté la PCR5 a

Philadelphie, j'ai dis a l’audience qu'on pourra utiliser nos règles de fusion, les PCRs, avec d'autres theories de la fusion. En verité, cela a été fait… To Jean Dezert In PCR5/6 formula what happens if the denominator m1(X)+m2(X) tends towards 0 but is not equal to 0? This seems to be a very imprecise formulation. If the denominator m1(X)+m2(X) tends towards 0, then also the conflicting mass m1(X)·m2(X) that is transferable tends to zero [because m1(X) and m2(X) each of them tend to zero (since they are positive)], therefore the redistribution masses x1 and y1 also tend to zero.