Buscar

Mostrando ítems 1-10 de 10738

Mechanistic approach to predict real machining time for milling free-form geometries applying high feed rate

COELHO, Reginaldo Teixeira; SOUZA, Adriano Fagali de; ROGER, Alessandro Rodrigues; RIGATTI, Aldo Marcel Yoshida; RIBEIRO, Alexandre Alves de Lima (SPRINGER LONDON LTD, 2010)

An accurate estimate of machining time is very important for predicting delivery time, manufacturing costs, and also to help production process planning. Most commercial CAM software systems estimate the machining time in ...

Mechanistic approach to predict real machining time for milling free-form geometries applying high feed rate

Universidade de São Paulo (USP); SOCIESC; Universidade Estadual Paulista (Unesp) (Springer London Ltd, 2010-02-01)

Mechanistic approach to predict real machining time for milling free-form geometries applying high feed rate

Universidade de São Paulo (USP); SOCIESC; Universidade Estadual Paulista (Unesp) (Springer London Ltd, 2010-02-01)

Mechanistic approach to predict real machining time for milling free-form geometries applying high feed rate

Coelho, Reginaldo Teixeira; de Souza, Adriano Fagali; Roger, Alessandro Rodrigues; Yoshida Rigatti, Aldo Marcel; de Lima Ribeiro, Alexandre Alves (Springer London Ltd, 2014)

Zeno-machines And The Metaphysics Of Time

Andraus; Augusto (Univ do Vale do Rio dos SinosSao Leopoldo, 2016)

Data-driven identification of rotating machines using ARMA deterministic parameter evolution in the angle/time domain

Universidade Estadual Paulista (Unesp); Univ Lyon (2020-09-01)

The functional-series angle-/time-varying autoregressive moving-average (AT-FS-ARMA) model was used to model and analyze vibration-based signals from internal combustion engines. This approach is derived from the formulation ...

Forecasting of Multiple Points in Time Series with Support Vector MachinesPredicción de Múltiples Puntos de Series de Tiempo Utilizando Support Vector Machines

BAUTISTA THOMPSON, E.; FIGUEROA NAZUNO, J.; GUZMÁN RAMIREZ, E. (Computación y Sistemas, 2009)

1
2
3
4
. . .
1074

Buscar

Mechanistic approach to predict real machining time for milling free-form geometries applying high feed rate

Mechanistic approach to predict real machining time for milling free-form geometries applying high feed rate

Mechanistic approach to predict real machining time for milling free-form geometries applying high feed rate

Mechanistic approach to predict real machining time for milling free-form geometries applying high feed rate

Zeno-machines And The Metaphysics Of Time

Data-driven identification of rotating machines using ARMA deterministic parameter evolution in the angle/time domain

Forecasting of Multiple Points in Time Series with Support Vector MachinesPredicción de Múltiples Puntos de Series de Tiempo Utilizando Support Vector Machines

kappa-Entropy Based Restricted Boltzmann Machines

κ-Entropy Based Restricted Boltzmann Machines

Extreme learning machine for mass spectrometry data analysis

Buscar

Filtros

Mechanistic approach to predict real machining time for milling free-form geometries applying high feed rate

Mechanistic approach to predict real machining time for milling free-form geometries applying high feed rate

Mechanistic approach to predict real machining time for milling free-form geometries applying high feed rate

Mechanistic approach to predict real machining time for milling free-form geometries applying high feed rate

Zeno-machines And The Metaphysics Of Time

Data-driven identification of rotating machines using ARMA deterministic parameter evolution in the angle/time domain

Forecasting of Multiple Points in Time Series with Support Vector MachinesPredicción de Múltiples Puntos de Series de Tiempo Utilizando Support Vector Machines

kappa-Entropy Based Restricted Boltzmann Machines

κ-Entropy Based Restricted Boltzmann Machines

Extreme learning machine for mass spectrometry data analysis