Výsledky vyhledávání - "André Paim Lemos"

Evolving clustering algorithm based on mixture of typicalities for stream data mining

Autor: Jose Guilherme S. Maia, Frederico Gadelha Guimarães, André Paim Lemos, Carlos Alberto Severiano Junior, Juan Camilo Fonseca Galindo, Miri Weiss Cohen, Cristiano Leite de Castro

Publikováno v: Future Generation Computer Systems. 106:672-684

Many applications have been producing streaming data nowadays, which motivates techniques to extract knowledge from such sources. In this sense, the development of data stream clustering algorithms has gained an increasing interest. However, the appl

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::6d6c259b3dd84e523cd1a0d0b760052d
https://doi.org/10.1016/j.future.2020.01.017

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Evolving Fuzzy System with Multivariable Gaussian Participatory Learning and Recursive Maximum Correntropy - eFCE

Autor: Alisson Marques Silva, André Paim Lemos, Fernanda P. S. Rodrigues

Publikováno v: FUZZ-IEEE

This paper suggests a new evolving fuzzy approach called eFCE (evolving Fuzzy with Multivariable Gaussian Participatory Learning and Recursive Maximum Correntropy). The approach uses a single pass learning procedure based on a recursive clustering al

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::7daf41d2238044910cfe8566335a5313
https://doi.org/10.1109/fuzz45933.2021.9494451

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An anatomy for neural search engines

Autor: Davi De Castro Reis, Thiago Akio Nakamura, André Paim Lemos, Pedro H. Calais

Publikováno v: Information Sciences. 480:339-353

In this work, we explore the application of modern deep learning techniques to build a neural model centric search engine. We conduct an in-depth discussion under several quantitative and qualitative criteria, comparing the trade-offs of adopting the

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::b5c30361375aa16e67cd882d357ab9e2
https://doi.org/10.1016/j.ins.2018.12.041

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A multi-agent system for solving the Dynamic Capacitated Vehicle Routing Problem with stochastic customers using trajectory data mining

Autor: Juan Camilo Fonseca-Galindo, Gabriela de Castro Surita, José Maia Neto, Cristiano Leite de Castro, André Paim Lemos

Publikováno v: Expert Systems with Applications. 195:116602

The worldwide growth of e-commerce has created new challenges for logistics companies, one of which is being able to deliver products quickly and at low cost, which reflects directly in the way of sorting packages, needing to eliminate steps such as

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9ba7e4d7d8e09f87f2cb64b9af7e91c5
https://doi.org/10.1016/j.eswa.2022.116602

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Adaptive fault detection and diagnosis using parsimonious Gaussian mixture models trained with distributed computing techniques

Autor: Ubirajara Fumega, Reinaldo M. Palhares, Carlos Henrique De Morais Bomfim, Thiago Akio Nakamura, André Paim Lemos, Walmir Matos Caminhas, Mário César Mello de Massa Campos, Benjamin Rodrigues de Menezes

Publikováno v: Journal of the Franklin Institute. 354:2543-2572

After a great advance by the industry on processes automation, an important challenge still remains: the automation under abnormal situations. The first step towards solving this challenge is the Fault Detection and Diagnosis (FDD). This work propose

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::1ada430750a34c3c24d36f129ea849e6
https://doi.org/10.1016/j.jfranklin.2016.11.024

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MILKDE: A new approach for multiple instance learning based on positive instance selection and kernel density estimation

Autor: Gustavo Matheus de Almeida, Antônio de Pádua Braga, Alexandre W. C. Faria, Alisson Marques Silva, Honovan Paz Rocha, Frederico Coelho, André Paim Lemos

Publikováno v: Engineering Applications of Artificial Intelligence. 59:196-204

Multiple Instance Learning (MIL) is a recent paradigm of learning, which is based on the assignment of a single label to a set of instances called bag. A bag is positive if it contains at least one positive instance, and negative otherwise. This work

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::7a4aa8464b80f1961aa137b60e67369e
https://doi.org/10.1016/j.engappai.2016.12.015

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Dataset structure as prior information for parameter-free regularization of extreme learning machines

Autor: Antônio de Pádua Braga, André Paim Lemos, Leonardo Jose Silvestre, João P. Braga

Publikováno v: Neurocomputing. 169:288-294

This paper proposes a novel regularization approach for Extreme Learning Machines. Regularization is performed using a priori spatial information expressed by an affinity matrix. We show that the use of this type of a priori information is similar to

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::f660562bd8f907af5fc5883b4a0b3065
https://doi.org/10.1016/j.neucom.2014.11.080

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Cryptocurrencies Transactions Advisor Using a Genetic Mamdani-type Fuzzy Rules Based System

Autor: Rafael Aeraf Leao Cadence, André Paim Lemos, Taiguara Melo Tupinambas

Publikováno v: FUZZ-IEEE

Cryptocurrencies prices forecasting is a complex theme due to the chaotic market behavior and the influence of external events. Therefore, inference models should offer, in addition to a satisfying accuracy, reasonable interpretability, so that inves

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::66705637da1c2b927c23e5ad325ed68a
https://doi.org/10.1109/fuzz-ieee.2018.8491619

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