Results 271 to 280 of about 2,309 (295)

Local coupled extreme learning machine

Neural Computing and Applications, 2014
Due to the significant efficiency and simple implementation, extreme learning machine (ELM) algorithms enjoy much attention in regression and classification applications recently. Many efforts have been paid to enhance the performance of ELM from both methodology (ELM training strategies) and structure (incremental or pruned ELMs) perspectives. In this
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Machine learning for source localization in urban environments

MILCOM 2016 - 2016 IEEE Military Communications Conference, 2016
This paper investigates source localization in urban environments using machine learning methods. Both classification and regression schemes are examined using the random forest algorithm. In both approaches, the localization performance depends mostly on arrival time information of received signals.
Darcy A. Bibb, Zhengqing Yun, Magdy F. Iskander   +2 more
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Comments on “Local coupled extreme learning machine”

Neural Computing and Applications, 2016
Local coupled extreme learning machine (LCELM) (Qu in Neural Comput Appl 27(1):27---33, 2016) is a recently developed variant of ELM and uses the paradigm of local coupled feed-forward neural network (LCFNN) (Sun in Neural Netw 23(1):108---113, 2010) to train an ELM model.
Wan-Guo Yu, Xu Zhou, Yu-Lin He, Rana Aamir Raza Ashfaq   +3 more
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Learning Mealy machines with local timers

Komplexe Echtzeitsysteme wie autonome Fahrzeuge, fortschrittliche Roboter und intelligente Energiesysteme sind im Begriff, das tägliche Leben grundlegend zu verändern. Um diese Systeme sicher einsetzen zu können, muss ihre korrekte Funktionsweise unbedingt gewährleistet werden. Das erfordert oft präzise Verhaltensmodelle.
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Local Class Boundaries for Support Vector Machine

2010
The support vector machine (SVM) has proved effective in classification. However, SVM easily becomes intractable in its memory and time requirements to deal with the large data, and also can not nicely deal with noisy, sparse, and imbalanced data.
Guihua Wen, Caihui Zhou, Jia Wei, Lijun Jiang   +3 more
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Improving Machining Localization in Abrasive-Assisted Electrochemical Jet Machining of SiCp/Al Composites using Large Standoff Distance

Arabian Journal for Science and Engineering, 2021
Zhuang Liu, Changshui Gao, Guo Chao
exaly  

Learning Mealy Machines with Local Timers

2023
Paul Kogel, Verena Klös, Sabine Glesner
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Localized Fatigue in Accounting- Machine Operators

Journal of Occupational and Environmental Medicine, 1980
K, Maeda, W, Hünting, E, Grandjean
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A new localization theory of adaptive machining of near-net-shape blades

Chinese Journal of Aeronautics, 2021
Neng Wan, Zezhong C Chen
exaly  

On Consistency and Stability of Support Vector Machines and Localized Support Vector Machines

In recent years, the demand for machine learning and artificial intelligence has grown rapidly. This has manifested itself in a drastic increase in the number of existing applications as well as in the pervasiveness of these applications. In these, different machine learning methods have shown enormous empirical success in accurately capturing ...
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