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    Theory of machine learning based on nonrelativistic quantum mechanics 

    Nieto-Chaupis, Huber (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 for Price Prediction for Agricultural Products 

    Bayona-Oré, Sussy; Cerna, Rino; Tirado Hinojoza, Eduardo (World Scientific and Engineering Academy and Society, 2021-06-07)
    Family farms play a role in economic development. Limited in terms of land, water and capital resources, family farming is essentially characterized by its use of family labour. Family farms must choose which agricultural ...
    Acceso abierto
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    Machine Learning to Assess Urbanistic Development in the South Pole of Lima City 

    Nieto-Chaupis, Huber; Alfaro-Acuña, Anthony (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 

    Nieto-Chaupis, Huber (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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    Machine Learning Analysis for Cervical Cancer Prediction, a Systematic Review of the Literature 

    Gutierrez-Espinoza, Sandy; Cabanillas-Carbonell, Michael (Institute of Electrical and Electronics Engineers, 2021-12-30)
    At present, cervical cancer is still the most complex issue due to the fact that people who suffer from it have a high risk of death. Therefore, it is very important to have an early diagnosis. The present study is a review ...
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    Testing Machine Learning at Classical Electrodynamics 

    Nieto-Chaupis, Huber (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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    Sentiment Analysis of Tweets using Unsupervised Learning Techniques and the K-Means Algorithm 

    Iparraguirre-Villanueva, Orlando; Guevara-Ponce, Victor; Sierra-Liñan, Fernando; Beltozar-Clemente, Saul; Cabanillas-Carbonell, Michael (SAI The Science and Information Organization, 2022)
    Abstract: Today, web content such as images, text, speeches, and videos are user-generated, and social networks have become increasingly popular as a means for people to share their ideas and opinions. One of the most ...
    Acceso abierto
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    Quantization of Energies with Machine Learning Without Quantum Mechanics 

    Nieto-Chaupis, Huber (IEEE, 2025-02-26)
    The field of Machine Learning through the technique of artificial neural network is used to determine in a straightforward manner the quantized energies of a particle in an infinite well. To accomplish this, unphysical ...
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    Machine Learning Algorithms for Producing Equations in Physics 

    Nieto-Chaupis, Huber (IEEE, 2025-02-26)
    Based at the prospective scenario that computers might to replace humans, emerge the idea that them can carry out jobs as a scientist does. Thus, one might to expect that for example machine learning can be a serious ...
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    Machine Learning as Mediator of Classical Electrodynamics and Quantum Mechanics 

    Nieto-Chaupis, Huber (IEEE, 2025-03-13)
    Machine Learning has been used as part of a closed-form operation that allows to link classical physics to quantum mechanics of a free electron radiating photons inside superintese laser field. To accomplish this an ...
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    AuthorNieto-Chaupis, Huber (20)Cabanillas-Carbonell, Michael (6)Iparraguirre-Villanueva, Orlando (3)Bayona-Oré, Sussy (2)Cerna, Rino (2)Gamboa-Cruzado, Javier (2)Garcia-Rios, Victor (2)Marres-Salhuana, Marieta (2)Sierra-Liñan, Fernando (2)Alfaro-Acuña, Anthony (1)... View MoreSubject
    Machine learning (32)
    Quantum mechanics (7)Perceptron (4)Classification (3)COVID-19 (3)Mathematical models (3)Pandemics (3)Physics (3)Agriculture (2)Family farm (2)... View MoreDate2022 (13)2023 (9)2021 (5)2025 (4)2020 (1)

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