Search
Now showing items 1-10 of 15
Theory of machine learning based on nonrelativistic quantum mechanics
(World Scientific, 2021)
The goal of this paper is the presentation of the elementary procedures that normally are done in nonrelativistic Quantum Mechanics in terms of the principles of Machine Learning. In essence, this paper discusses Mitchell's ...
Acceso restringido
Machine Learning to Assess Urbanistic Development in the South Pole of Lima City
(Springer, 2022-01-01)
We employ Machine Learning through the Mitchell’s criteria to carry out an assessment on the potential spatial configurations at the south pole of Lima city, at Perú. Based at both qualitative and quantitative facts, an ...
Acceso restringido
Data Analysis of Particle Physics Experiments Based on Machine Learning and the Mitchell’s Criteria
(Springer, 2020)
Commonly the searching and identification of new particles, requires to reach highest efficiencies and purities as well. It demands to apply a chain of cuts that reject the background substantially. In most cases the ...
Acceso restringido
Testing Machine Learning at Classical Electrodynamics
(Institute of Electrical and Electronics Engineers, 2021-10-22)
Like physics or another laws-based basic science, machine learning might also be a firm methodology to solve physics problems by the which a kind of optimization and minimization of energy are needed. Expressed at the ...
Acceso restringido
Machine Learning of a Pair of Charged Electrically Particles Inside a Closed Volume: Electrical Oscillations as Memory and Learning of System
(Springer Link, 2022)
In this paper the problem of two charged particles inside a frustum is faced through the principles of Machine Learning compacted by the criteria of Tom Mitchell. In essence, the relevant equations from the classical ...
Acceso restringido
The Criteria of Mitchell to Interpret Classical Radiation as Compton Scattering
(IEEE, 2022)
The principles of Machine Learning through the criteria of Mitchell are used to validate a concrete quantum-mechanics interpretation from a classical radiation scheme inside the framework of linear and nonlinear Compton ...
Acceso restringido
The Machine Learning Principles Based at the Quantum Mechanics Postulates
(Springer Link, 2022)
Quantum mechanics is governed by well-defined postulates by the which one can go through either theory or experimental studies in order to perform measurements of microscopic dynamics of elementary particles, atoms and ...
Acceso restringido
Quantum Mechanics of Theorem of Bayes Modeled by Machine Learning Principles
(IEEE, 2022)
A theory consisting in quantum mechanics and theorem of Bayes, is presented. In essence, the Bayes probability has been built from two subspaces. While in one some quantum measurements are done, in the another it is seen ...
Acceso restringido
Machine Learning and Bayes Probability For Detecting Camouflaged Mini Pandemic at the Waves of Covid-19
(IEEE, 2022)
This paper present a methodology based at Machine Learning and a theory backed by the Bayes probability to identify rare strains that might not be in coherence with the corona virus. By using the criteria of Tom Mitchell ...
Acceso restringido
The Approach of Machine Learning to Optimize the Bank-Customer Interaction at Pandemic Epochs
(IEEE, 2022)
Along the pandemic created by the Corona virus 2019 (Covid-19 in shorthand), the global economy was observed to experience various turbulent months that were reflected by the increasing of unemployment and the apparition ...
Acceso restringido