نتایج جستجو برای: dutch elm disease

تعداد نتایج: 1516060  

2014
Jérôme Pouzoulet Alexandria L. Pivovaroff Louis S. Santiago Philippe E. Rolshausen

This review illuminates key findings in our understanding of grapevine xylem resistance to fungal vascular wilt diseases. Grapevine (Vitis spp.) vascular diseases such as esca, botryosphaeria dieback, and eutypa dieback, are caused by a set of taxonomically unrelated ascomycete fungi. Fungal colonization of the vascular system leads to a decline of the plant host because of a loss of the xylem ...

Utilizing surrogate models based on artificial intelligence methods for detecting structural damages has attracted the attention of many researchers in recent decades. In this study, a new kernel based on Littlewood-Paley Wavelet (LPW) is proposed for Extreme Learning Machine (ELM) algorithm to improve the accuracy of detecting multiple damages in structural systems.  ELM is used as metamo...

2013
Yoshinori Mitamura Sayaka Mitamura-Aizawa Takashi Katome Takeshi Naito Akira Hagiwara Ken Kumagai Shuichi Yamamoto

With recent development of spectral-domain optical coherence tomography (SD-OCT), the pathological changes of retina can be observed in much greater detail. SD-OCT clearly delineates three highly reflective lines in the outer retina, which are external limiting membrane (ELM), photoreceptor inner and outer segment (IS/OS) junction, and cone outer segment tips (COST) in order from inside. These ...

Journal: :Journal of International Commerce, Economics and Policy 2015

2005
Guang-Bin Huang Nan-Ying Liang Hai-Jun Rong Paramasivan Saratchandran Narasimhan Sundararajan

The primitive Extreme Learning Machine (ELM) [1, 2, 3] with additive neurons and RBF kernels was implemented in batch mode. In this paper, its sequential modification based on recursive least-squares (RLS) algorithm, which referred as Online Sequential Extreme Learning Machine (OS-ELM), is introduced. Based on OS-ELM, Online Sequential Fuzzy Extreme Learning Machine (Fuzzy-ELM) is also introduc...

Journal: :Int. J. Machine Learning & Cybernetics 2011
Guang-Bin Huang Dianhui Wang Yuan Lan

Computational intelligence techniques have been used in wide applications. Out of numerous computational intelligence techniques, neural networks and support vector machines (SVMs) have been playing the dominant roles. However, it is known that both neural networks and SVMs face some challenging issues such as: (1) slow learning speed, (2) trivial human intervene, and/or (3) poor computational ...

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