Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Bücher
Zeitschriften
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
ATZ-Fachkongress

Chassis.tech plus 2024


4 Kongresse in einer Veranstaltung

Treffen Sie in München die Fachleute von Chassis, Lenkung, Bremsen sowie Reifen/Räder.
Erweiterte Suche
Anmelden
nach oben
Cluster Computing
Erschienen in: Cluster Computing 4/2016

01.12.2016

A method analysis for hail cloudy prediction based on CNN

verfasst von: Li Guodong, Xu Wenxia, Yang Bing, Buhailiqiemu Awudong, Chang Xiaojuan

Erschienen in: Cluster Computing | Ausgabe 4/2016

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

A hailstorm forecast method is proposed in the paper. Edge Detect Cellular Neural Network (EDCNN) method is used to extract the edge of cloud radar images. We have detected the texture of the cloud images. Then the texture image has been processed with wavelet transform. The hail data information from the image has been found. We will get approximate detail coefficients, level detail coefficients, vertical detail coefficients, diagonal detail coefficients, and reconstructed coefficients. Construct hail cloud life feature vector matrix to explain the problem. Found the corresponding rules through the five coefficients. At last, through the simulation experiment achieve the purpose of hail forecast. A feature vector of hail cloud life has been constructed, the rules of hail had been found from the feature vector. And Compared with the contour variance of the hail cloud inner and outer, we will find this paper puts forward the method is more effective. The conclusion is rationality according the simulation experiment verifies.
Vorheriger Artikel Clustering and ontology-based information integration framework for surface subsidence risk mitigation in underground tunnels
Nächster Artikel A topological enabled three-dimensional model based on constructive solid geometry and boundary representation

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Jetzt informieren
Literatur
1.
Chuang, Z., Jiannan, C., Chaohui, Z.: Novel color edge detector derived from CNN mode. Comp. Eng. Appl. 44(2), 17–19 (2008)
2.
Chua, L.O., Roska, T.: Cellular neural networks and visual computing. Cambridge University Press, Cambridge (2000)
3.
Bu-Qing, C.A.O., Jian-Xun, L.I.U., Bin, W.: Currency characteristic extraction and identification research based on PCA and BP neural network. J. Conv. Inform. Technol. 7(2), 38–44 (2012)
4.
Zhou, Y., Zhu, Y.: Identification of a hail cloud clustering method similar to the evolution of research. J. Anhui Agri. Sci. 35(30), 9637–9642 (2007)MathSciNet
5.
Li Guodong, Xu, Wenxia, Wang Xu: Efficient hail cloudy identification scheme base on CNN. J. Conv. Inform. Technol. 7(22), 669–676 (2012)
6.
Guodong Li, Wenxia Xu. (2011) Process Weather Image By Some CNN, Int. Conf. Green Energy Environ. Sustain. Dev., 1721–1726
7.
Guodong, Li, Wang., Xu: Hail identification analysis from Radar image by CNN. Appl. Mech. Mat. 155, 841–845 (2012)
8.
CHUALO.: Chaos CNN: aversionof complexity, Int. J. Bifurc. 7, 2219–2425 (1997)
9.
M. Lei, L. Min (2004) Robustness design of templates of CNN for detecting inner corners of objects in gray-scale images, in Int. Conf. on Communications, Circuit and Systems, Vol. II: 1090–1093. IEEE Press
10.
Bálya, D., Roska, B., Roska, T., Werblin, F.S.: A CNN framework for modeling parallel processing in a mammalian retina. Int. J. Circuit Theory Appl. (CTA) 30, 363–393 (2002)CrossRefMATH
11.
Dan, Yang: MATLAB image processing[M]. Tsinghua University Press, Beijing (2013)
12.
Dongjian, H.: Digital image processing [M]. Xi’an: Xi’an Electronic and Science University press (2004)
13.
Defeng, Zhang: MATLAB digital image processing [M]. Mechanical Industry Press, Beijing (2009)
14.
Zhaoqing, Zhang: Hail cloud based on catastrophe theory prediction research [D]. Tianjin University, Tianjin (2009)
15.
Rekeczky C.: CNN architectures for constrained diffusion based locally adaptive image processing. Int. J. Circuit Theory Appl. (2002)
16.
Zhao, J., Wang, H., Yu, D.: A new approach for edge detection of noisy image based on CNN. Int. J. Circ. Theory Appl. (2003)
17.
Aizenberg, N.N.,Aizenberg, I.N.:CNN-like networks based on multi-valued and universal binary neurons: Learning and application to image processing. In: Proceedings of the 3rd IEEE International Workshop on Cellular Neural Networks and their Applications, Rome (1994)
18.
Zhao J.,Yu D.: A new approach for ME multilevel image restoration based on CNN. Int. J. Circ. Theory Appl. (1999)
19.
Guiming, H. Wenyan, J., Min, Z.: A research of segmentation of video moving objects based on cellular neural network. Comp. Modern. (2007)
20.
Destri. G., Marenzoni, P.: Cellular neural networks as a gen-eral massively parallel computational paradigm. Int. J. Circ. Theory Appl. (1996)
21.
Guozhen, B., Jiehao, Y.: Self tuning of PID parameters based on Improved Fuzzy Neural Network[J]. Appl. Res. Comp. (2016)
22.
Fang, X.: Dynamics study on two-dimensional neural networks. Appl. Res. Comp. (2011)
23.
Feng, Q., Sheng, L., Zhang, W.: A new method of image restoration based on cellular neural network. J. Image Graph. (2009)
24.
Sun, X., Pan, G.: Study on the moving target tracking algorithm based on cellular neural network. Comp. Dev. Appl. (2008)
25.
Zhang, C., Zhang, X.: A sufficient condition for the stability of cellular neural networks. J. Beijing Union Univ. Nat. Sci. (2006)
26.
Zhang, X., Zhu, Y., Wang.: Performance analysis and application of super chaotic synchronization system of cellular neural network. Comp Appl Software 2009
27.
Dogaru, R., et al.: Pyramidal cells: A novel class of adaptive coupling cells and their application for cellular neural networks. Fundamental Theory and Applications, IEEE Transactions on Circuits and Systems-I (1998)
28.
Jing, G., Dianxun, S.: The faster higher-order cellular automaton for hyper-parallel undistorted data compression. J. Comp. Sci. Technol. (2000)
29.
Jing, G., Dianxun, S.: A new parallel-by-cell approach to undistorted data compression based on cellular automaton and genetic algorithm. J. Comp. Sci. Technol. (1999)
30.
Shuai, D.X.,Gu, J.: The faster high-order cellular automaton for hyper-parallel undistorted data compression. J. Comp. Sci. Technol. (2000)
31.
Xuan, J., Luo, X., Zhang, G., Lu, J., Xu, Z.: Uncertainty analysis for the keyword system of web events. IEEE Trans. Syst. Man Cyber. Syst. 46(6), 829–842 (2016)CrossRef
Metadaten
Titel
A method analysis for hail cloudy prediction based on CNN
verfasst von
Li Guodong
Xu Wenxia
Yang Bing
Buhailiqiemu Awudong
Chang Xiaojuan
Publikationsdatum
01.12.2016
Verlag
Springer US
Erschienen in
Cluster Computing / Ausgabe 4/2016
Print ISSN: 1386-7857
Elektronische ISSN: 1573-7543
DOI
https://doi.org/10.1007/s10586-016-0632-3

Weitere Artikel der Ausgabe 4/2016

Cluster Computing 4/2016 Zur Ausgabe

OriginalPaper

An optimal path finding strategy in networks based on random walk

OriginalPaper

On the role of application and resource characterizations in heterogeneous distributed computing systems

OriginalPaper

High-performance XML modeling of parallel queries based on MapReduce framework

OriginalPaper

Object-based dynamic influence measurement model (DIMM) using social data (on facebook)

OriginalPaper

Availability analysis and case study of mobile-OTP key generation using skip sampling of voice

OriginalPaper

Unified formal derivation and automatic verification of three binary-tree traversal non-recursive algorithms

Premium Partner

    Bildnachweise