Zobrazeno 1 - 10
of 189
pro vyhledávání: '"LVQ neural network"'
Autor:
WenJun Zhang, GuangHua Liu
Publikováno v:
Network Biology, Vol 13, Iss 4, Pp 98-121 (2023)
Based on previously constructed data tables of acupoint functions and meridians, we performed a pattern classification of acupoints based on functional similarity in this study. Unsupervised pattern classification methods include k-means clustering,
Externí odkaz:
https://doaj.org/article/a689e25de11c48a1bff4ccee1a738eab
Publikováno v:
Agriculture, Vol 14, Iss 4, p 584 (2024)
Tractor condition recognition has important research value in helping to understand the operating status of tractors and the trend of tillage depth changes in the field. Therefore, this article presents a method for recognizing tractor conditions, pr
Externí odkaz:
https://doaj.org/article/311bc31453e4437a8e3eeb0afbe8a76d
Publikováno v:
IEEE Access, Vol 8, Pp 104555-104564 (2020)
Accurate prediction of traffic flow in urban networks is of great significance for smart city management. A short-term traffic flow prediction algorithm of Quantum Genetic Algorithm - Learning Vector Quantization (QGA-LVQ) neural network is proposed
Externí odkaz:
https://doaj.org/article/1134d15c76234ea8a1a85be256ebf6bc
Akademický článek
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Autor:
Jian-Hui Wu, Wei Wei, Lu Zhang, Jie Wang, Robertas Damasevicius, Jing Li, Hai-Dong Wang, Guo-Li Wang, Xin Zhang, Ju-Xiang Yuan, Marcin Wozniak
Publikováno v:
IEEE Access, Vol 7, Pp 23109-23119 (2019)
The steel industry is one of the pillar industries in China. The physical and mental health of steel workers is related to the development of China's steel industry. Steel workers have long been working in shifts, high temperatures, noise, highly str
Externí odkaz:
https://doaj.org/article/8bd08daabaa140dd979e26b920c9b3de
Akademický článek
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Publikováno v:
Zhongguo Jianchuan Yanjiu, Vol 13, Iss 1, Pp 133-139 (2018)
[Objectives] This paper proposes a heterogeneous integrated learner to solve the problem of fuzzy uncertainty classification in order to judge the target intention of air attack in a short time. [Methods] First, a limit learning machine, decision tre
Externí odkaz:
https://doaj.org/article/4ec252a46488451b835dfe9bf6c5cba9
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
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Autor:
Tongke Fan
Publikováno v:
Recent Advances in Computer Science and Communications. 14:1903-1911
Background: Roberts, Sobel, Prewitt and other operators are commonly used in image edge detection, but because of the complex background of agricultural pests and diseases, the efficiency of using these operators to detect is not ideal. Objective: To
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a2859cfac65fab98fccdfb84a67207f1
https://doi.org/10.2174/2666255813666191218112436
https://doi.org/10.2174/2666255813666191218112436
Publikováno v:
IEEE Access, Vol 8, Pp 104555-104564 (2020)
Accurate prediction of traffic flow in urban networks is of great significance for smart city management. A short-term traffic flow prediction algorithm of Quantum Genetic Algorithm - Learning Vector Quantization (QGA-LVQ) neural network is proposed
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1559576af6d4d67c68c8c1789b76be7a
https://doi.org/10.1109/access.2020.2999608
https://doi.org/10.1109/access.2020.2999608