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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 ...
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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 ...
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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 ...
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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 ...
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The Quantum Mechanics Propagator as the Machine Learning Performance in Space-Time Displacements
(Institute of Electrical and Electronics Engineers, 2021-12)
The role of evolution operator is to provide the time displacement of wave function through the Hamiltonian of the system. The usage of coordinates representation gives the well-known propagator that is the Green’s function. ...
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Combined Monte Carlo and Machine Learning Algorithms to Predict Horizontal Expansion of Lima City
(IEEE, 2022)
In this paper, the method of Monte Carlo is projected onto the Mitchell criteria inside the framework of Machine Learning. Because the probabilistic character that exhibits the theory of Mitchell, the Monte Carlo technology ...
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Model of Early Intervention Using Machine Learning: Predicting Monkeypox Pandemic
(IEEE, 2022)
This paper presents a model of intervention at the first phases of global pandemic using the criteria of Mitchell that simplifies to some extent the philosophy of Machine Learning. These criteria are projected onto the ...
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Quantum Displacements Dictated by Machine Learning Principles: Towards Optimization of Quantum Paths
(Springer Link, 2023)
In Physics the energy of any system represents a sensitive variable because of it depends the functionality and evolution of system at time. Thus the deep knowledge of the interactions of system might be a remarkable ...
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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 ...
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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 ...
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