A sparse probabilistic approach with chaotic artificial bee colony optimization for sea clutter soft computing-Reference-Cited by-同舟云学术

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A sparse probabilistic approach with chaotic artificial bee colony optimization for sea clutter soft computing

Published:2016-12 Issue: Volume:49 Page:108-119
ISSN:1568-4946
Container-title:Applied Soft Computing
language:en
Short-container-title:Applied Soft Computing

Author:

Sun Yuanmeng,Liu Xinggao,Zhang Zeyin,Wang Zhicheng,Yu Yusheng,Zhang Tianjian,Zhu Yu,Song Zhengji

Funder

Major Program of National Natural Science Foundation of China

Zhejiang Province Natural Science Foundation

Shanghai Aerospace Science and Technology Innovation Fund

Aerospace Science and Technology Innovation Fund of China Aerospace Science and Technology Corporation

Publisher

Elsevier BV

Subject

Software

Reference53 articles.

1. Hybrid PSO-SVM method for short-term load forecasting during periods with significant temperature variations in city of Burbank;Selakov;Appl. Soft Comput.,2014

2. Accurately predicting building energy performance using evolutionary multivariate adaptive regression splines;Cheng;Appl. Soft Comput.,2014

3. Non-Mercer hybrid kernel for linear programming support vector regression in nonlinear systems identification;Lu;Appl. Soft Comput.,2009

4. Statistical analysis of real aperture radar field backscattered from sea surfaces under Moderate winds by Monte Carlo simulations;Pinel;IEEE Trans. Geosci. Remote Sens.,2014

5. Weibull distribution and K-distribution of sea clutter observed by X-band radar and analyzed by AIC;Sayama;IEICE Trans. Commun. E83B,2000

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1. A novel radar operating mode identification approach based on variational relevance vector machine with chaotic gravitational search optimization;Transactions of the Institute of Measurement and Control;2022-12-01

2. Artificial bee colony directive for continuous optimization;Applied Soft Computing;2020-02

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