Bibhorr deemed research on this issue to be very important because there hasn’t been any serious fundamental and technical work done to use AI in flight dynamics performance upgradation. Fuzzy logics have several drawbacks, such as forecasts that aren’t always correct, ambiguity in some circumstances, sluggish run time, etc. This led Bibhorr to create and launch this algorithm by inventing new models and methods.
The invented algorithm is based on Baudhayan’s AI-augmented triangulation logic, where the concept permits numerous logical values of a variable spanning between 0 and 2π. Bibhorr (2019) provided a formula for triangulation determination, known as Bibhorr formula, that was used to determine the final conclusion for an AI algorithm’s learning scenario. The triangulation modelling, on which the behavior learning algorithm is based, uses angular magnitude as an indicator of learning effort. Based on the angular variation, the behavior learning algorithm makes necessary adjustments. In order to calculate the variation in the data in angular form, the algorithm first receives the data array for time interval t1 and then receives data for time interval t2. For two distinct time intervals, t1 and t2, the algorithm computes the angular variation b as a function of variation between the data lines.
