Mirce science: Prediction
“Each in-service event generated by the motion
of a machine through in-service reality has its own probability function, but probability itself propagates
in accordance to the mechanisms of causing action(s). Jezdimir Knezevic
Mirce science is a theory for for predicting the irreversible motion of a machine through in-service reality, by subjecting mechanisms of causing actions to Mirce equations. However, the quantitative evaluation of these equations is not possible due to inability of mathematics to deal with the large number of multi-dimensional integral equations and their interactions. These type of problems are not specifically related to the Mirce equations. They are common to all scientific disciplines of this nature, as it is a known mathematical fact that the integral equations do not have analytical solutions. However, as it is not acceptable to simplify observed machine in-service reality in order to cope with mathematical limitations, a suitable computational solution was required.
Classical mechanics developed by Newton needed a new method for computing solutions, as existing methods of geometry and algebra could not be applied. Hence, for the quantitative predictions of the motion defined by Newton's equations, calculus was created. It is the mathematical method for computing the continuous change, focusing on rates of change (derivatives) and the accumulation of quantities (integrals).
Quantum mechanics equations describe the probabilistic behaviour of subatomic particles using wave functions, energy operators and fundamental constants like Planck’s constant, the Schrodinger equation that describes time-dependent system evolution, while the Heisenberg principle limits measurement precision. However, the existing calculus methods could not be used for the evaluation of these equations. Hence, new methods have been created to enable predictions to be made. Hence, the new computational methods have been developed, among which the Monte Carlo method plays a leading roll.
Mirce equations, are used to model the motion of a machine through in-service reality, where the number of dimensions is determined by the number of causing mechanisms that generates occurrences of negative events and the number of positive actions, determined and executed by humans, to perform and return a machine to positive in-service state.
Decades of searching for the method that is able to facilitate quantitative evaluation of Mirce equations finally succeeded by making use of Monte Carlo method. It was invented to solve similar computational problems in context of nuclear technology, as the only possible method for solving six-dimensional integral equation, in order to design shielding for nuclear reactors.
Hence, the Monte Carlo method is used in Mirce science, as it is the only possible approach that yields solutions to complex multi dimensional convolution integrals used to model of the motion of machines through in-service reality and quantitatively predict expected in-service performance and corresponding demand for the resources required.
It is necessary to stress that the accuracy of the predictions obtained by the Mirce equations is directly proportional to the accuracy of "translating" causing mechanisms of the motion of machines through in-service reality into their mathematical representations. Otherwise, the commonly applied saying computing jargon, "Garbage in, garbage out"!is fully applicable in Mirce science too.
Source: Knezevic, J., The Origin of MIRCE Science, pp. 232, MIRCE Science, Exeter, UK, 2017, ISBN 978-1-904848-06-6