Zobrazeno 1 - 10
of 88
pro vyhledávání: '"Ming Feng Yeh"'
Publikováno v:
Axioms, Vol 11, Iss 8, p 364 (2022)
The grey Riccati model (GRM) is a generalization of the grey Verhulst model (GVM). Both the GRM and GVM generally perform well in simulating and forecasting the raw sequences with a bell-shaped or single peak feature. Although there are several metho
Externí odkaz:
https://doaj.org/article/c478d54aa94b4e13b365d5c893d1eadd
Autor:
Ming-Feng Yeh, Ming-Hung Chang
Publikováno v:
Axioms, Vol 10, Iss 4, p 278 (2021)
The only parameters of the original GM(1,1) that are generally estimated by the ordinary least squares method are the development coefficient a and the grey input b. However, the weight of the background value, denoted as λ, cannot be obtained simul
Externí odkaz:
https://doaj.org/article/83313f93b4dc411cab943178ff5cc905
Autor:
Ming-Feng Yeh1 njyeh@mail.lhu.edu.tw, Hung-Ching Lu2
Publikováno v:
Journal of Grey System. 2019, Vol. 31 Issue 2, p110-120. 11p.
Autor:
Ming-Feng Yeh, Ti-Hung Chen
Publikováno v:
Intelligent Automation & Soft Computing. 26:407-420
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5416ceb0134133e15f780163ff3b7b96
https://doi.org/10.32604/iasc.2020.013917
https://doi.org/10.32604/iasc.2020.013917
Autor:
Ming-Feng Yeh1 mjyeh@mail.lhu.edu.tw, Shih-Chang Wang2
Publikováno v:
Journal of Grey System. 2017, Vol. 29 Issue 3, p36-44. 9p.
Autor:
Ming-Feng Yeh1 mfyeh@mail.lhu.edu.tw, Hung-Ching Lu2
Publikováno v:
Journal of Grey System. 2017, Vol. 29 Issue 2, p29-38. 10p.
Autor:
Ti-Hung Chen, Ming-Feng Yeh
Publikováno v:
Universal Journal of Control and Automation. 5:12-17
This paper will propose the state feedback control based networked control system (NCS) design with the differential evolution algorithm. For designing a networked control system, one has to overcome the problems about the random latency and the data
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::839786741f4d0ed762ebc095ac76ed73
https://doi.org/10.13189/ujca.2017.050102
https://doi.org/10.13189/ujca.2017.050102
Publikováno v:
ICMLC
This study attempts to improve the forecasting accuracy of rolling grey model by applying Gaussian bare-bones differential evolution (GBDE) to optimize the weight of background value and number of data points used to construct a rolling-GM(1,1). Expe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b27a17f44615fc2f41dba56a674bf6e0
https://doi.org/10.1109/icmlc48188.2019.8949310
https://doi.org/10.1109/icmlc48188.2019.8949310
Publikováno v:
Journal of Grey System. 2015, Vol. 27 Issue 2, p38-46. 9p.
Publikováno v:
ICMLC
Inspired by neural-network-based GM(1,1) (NN-GM(1,1)), this study attempts to drive a more simple and efficient learning rule to enhance the fitting/forecasting ability and convergence speed of the grey neural network. Simulation results on two real
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fa78b9722ca1524dd3b245b49c384e45
https://doi.org/10.1109/icmlc.2018.8527024
https://doi.org/10.1109/icmlc.2018.8527024