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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 ...
Acceso restringido
Sentiment Analysis of Tweets using Unsupervised Learning Techniques and the K-Means Algorithm
(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
Price Prediction of Agricultural Products: Machine Learning
(Springer, 2022)
Family farming is essentially characterized by the use of family labor force, due to the lack of land, water, and capital resources. An important tool is which allows them to know which products will be the best priced ...
Acceso restringido
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 ...
Acceso restringido
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 ...
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 for Management in Software-defined Networks: A Systematic Literature Review
(DBpia, 2022)
Software-Defined Networking (SDN) has emerged as a new paradigm for managing data networks, and Machine Learning (ML) techniques have become relevant in the scientific community to solve management problems. Research on ...
Acceso restringido