检索结果-内蒙古大学图书馆

CBS-GAN: A Band Selection Based Generative Adversarial Net for Hyperspectral Sample Generation

IOP Conference Series: Earth and Environmental Science 2021年第1期734卷

作者： Yulin Qiao Mostofa Zaman Mohammad Yi Li Xiaobo Liu Zhihua Cai School of Automation China University of Geosciences (Wuhan) 430074 Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems 430074 Wuhan China Hubei Key Laboratory of Intelligent Geo-Information Processing China University of Geosciences Wuhan 430078 China School of Computer Science China University of Geosciences (Wuhan) 430078 Wuhan China

Sample generation is an effective method to improve the performance of hyperspectral image classification by generating virtual samples for training sample expansion in the training process of classification. However, there are some defects existing in the previous sample generation methods including the lack of spatial information, the redundant generation and the damage of the original spectral components. In this paper, we propose conditional band selection generative adversarial net, named CBS-GAN, to handle this problem. Firstly, the band selection net of CBS-GAN is utilized to avoid redundant bands and keep original spectral information, then the generation net of CBS-GAN generates the spatial-spectral data blocks by selected bands for sample generation. The experiments of classification are also used to demonstrate the availability of virtual samples generated by our method.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A new Fermatean fuzzy Spearman-like correlation coefficient and its application in evaluating insecurity problem via multi-criteria decision-making approach

引用

Heliyon 2024年第22期10卷 e40403页

作者： Ejegwa, Paul Augustine Kausar, Nasreen Aydin, Nezir Feng, Yuming Olanrewaju, Oludolapo Akanni Department of Mathematics Joseph Sarwuan Tarka University Makurdi Nigeria Department of Mathematics Faculty of Arts and Science Yildiz Technical University Esenler Istanbul 34220 Turkey College of Science and Engineering Hamad Bin Khalifa University Doha Qatar Department of Industrial Engineering Yildiz Technical University Besiktas Istanbul 34349 Turkey Key Laboratory of Intelligent Information Processing and Control Chongqing Three Gorges University Chongqing 404100 China Department of Industrial Engineering Durban University of Technology Durban 4001 South Africa

The problem of insecurity is a global crisis with adverse effects on lives and properties. Fermatean fuzzy correlation coefficient is a dependable method for handling imprecision, which is the main bottleneck of insecurity assessment. A number of Fermatean fuzzy correlation coefficient methods have been developed. Based on Spearman's correlation coefficient, an innovative Fermatean fuzzy correlation coefficient method is built to enhance trustworthy insecurity assessment. The existing Fermatean fuzzy correlation coefficient methods are evaluated, and their shortcomings are identified in order to validate the construction of a new Fermatean fuzzy correlation coefficient method. The drawbacks of the existing methods lead us into building a new Fermatean fuzzy correlation coefficient method by using the Spearman's correlation coefficient approach, which has the potential of overcoming the drawbacks of the existing Fermatean fuzzy correlation coefficient methods. In addition, some theoretical findings are provided to support the strength of the novel Fermatean fuzzy correlation coefficient method and it is shown that the new method satisfies the Fermatean fuzzy correlation coefficient requirements. Furthermore, the novel Fermatean fuzzy correlation coefficient method is applied to assess the insecurity situation in the North-Central Region of Nigeria to furnish intended tourists with relevant travel advice. To demonstrate the inherent significance of the novel Fermatean fuzzy correlation coefficient method, we compare its effectiveness to that of the extant Fermatean fuzzy correlation coefficient methods. The results of the comparison show the superiority of the novel Fermatean fuzzy correlation coefficient method over the existing ones in terms of reliability, consistency, precision and compliance with the Fermatean fuzzy correlation coefficient axioms. Ultimately, it is discovered that the new method can effectively address hesitations related to insecurity assessment

关键词： Correlation coefficient Fermatean fuzzy sets Insecurity assessment Multi-criteria decision-making North central region of Nigeria Security crises

来源：评论

学校读者我要写书评

暂无评论

Correction to: Parallel optimization of the ray-tracing algorithm based on the HPM model

引用

The Journal of Supercomputing 2021年第9期77卷 10333-10333页

作者： Jun-Feng, Wang Gang-Yi, Ding Yi-Ou, Wang Yu-Gang, Li Fu-Quan, Zhang School of Computer Science and Technology Beijing Institute of Technology Beijing People’s Republic of China Beijing Institute of Science and Technology Information Beijing People’s Republic of China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou People’s Republic of China

A correction to this paper has been published: https://***/10.1007/s11227-021-03680-0

关键词：

来源：评论

学校读者我要写书评

暂无评论

Two-dimensional picture arrays and Parikh q—matrices

引用

Journal of Physics: Conference Series 2018年第1期1132卷

作者： Somnath Bera Kalpana Mahalingam Linqiang Pan K. G. Subramanian Key Laboratory of Image Information Processing and Intelligent Control of Education Ministry of China School of Automation Huazhong University of Science and Technology Wuhan 430074 Hubei China Department of Mathematics Indian Institute of Technology Madras Chennai 600036 India School of Electric and Information Engineering Zhengzhou University of Light Industry Zhengzhou 450002 Henan China Department of Mathematics Madras Christian college Tambaram Chennai 600017 India

Based on the idea of 'q—count' of certain subwords of a word and generalizing the notion of Parikh matrix of a word, the notion of Parikh q—matrix of a word over an ordered alphabet was introduced. On the other hand, with a two-dimensional picture array of symbols arranged in rows and columns, two kinds of upper triangular matrices, known as row and column Parikh matrices have also been introduced and investigated. Here combining these two kinds of matrices of a picture array, we introduce row/column Parikh q—matrix of an array, leading to the concept of q—ambiguity of a picture array. Results relating to q—ambiguity of picture arrays are derived in the context of these Parikh q—matrices of arrays.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Vehicle detection based on point cloud intensity and distance clustering

引用

Journal of Physics: Conference Series 2021年第4期1748卷

作者： Zhao Wang Xing Wang Bin Fang Kun Yu Jie Ma School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan 430074 China National key laboratory of multispectral information processing technology Huazhong University of Science and Technology Wuhan 430074 China Science and technology on complex system control and intelligent agent cooperation laboratory Beijing 100074 China

In the intelligent transportation system, vehicle detection is one of the essential technologies in obstacle avoidance and navigation, however the existing vehicle detection methods cannot meet the actual needs. This paper presents a vehicle detection method combines the intensity and distance information of point cloud, which improves the segmentation performance of nearby objects. Specifically, the data of point cloud collected by lidar is preprocessed first. Then the processed point cloud is clustered by combining its coordinate and intensity information. Finally, the clustered suspected targets are fed to the random forest classifier. Our method can efficiently detect and classify targets in large-scale disordered 3D point cloud with high accuracy. In the real-scanned Livox Mid-40 Lidar dataset, our proposed method improves the detection accuracy by 31% compared with the traditional Euclidean clustering.

关键词：

来源：评论

学校读者我要写书评

暂无评论

TSW-FD: A Novel Temporal and Spatial Domain Weight Analysis of Feature Difference for Micro-Expression Spotting

引用

Journal of Physics: Conference Series 2021年第1期1828卷

作者： Zhihao Zhang Fan Mo Ke Zhao Tong Chen Xiaolan Fu State Key Laboratory of Brain and Cognitive Science Institute of Psychology Chinese Academy of Sciences Beijing 100101 China Department of Psychology University of Chinese Academy of Sciences Beijing 100049 China Chongqing Key Laboratory of Non-linear Circuit and Intelligent Information Processing Southwest University Chongqing 400715 China Chongqing Key Laboratory of Artificial Intelligence and Service Robot Control Technology Chongqing 400715 China

The micro-expression spotting has recently attracted increasing attention from psychology and computer vision community, since embraced in the second facial Micro-Expression Grand Challenge (MEGC 2019). Different from the original feature difference (FD) analysis, in this paper, we proposed a novel temporal and spatial domain weight analysis of feature difference (TSW-FD) to achieve micro-expression spotting. The experimental results showed that TSW-FD improved 17.86% and 24.21% in F1-Score comparing to the FD in CASME II and SMIC-E-HS.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Design of chinese natural language in fuzzy boundary determination algorithm based on big data

引用

Journal of information Hiding and Multimedia Signal processing 2017年第2期8卷 423-434页

作者： Zhang, Fu Quan Mao, Zi Jing Ding, Gang Yi Xu, Lin School of Software Beijing Institute of Technology Beijing100081 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou350121 China Via Room A9#301 Juyuan JiyuanFuzhou350008 China Department of Electrical Engineering University of Texas at San Antonio One UTSA Circle San AntonioTX78249 United States Via Arrow Oaks 126 San AntonioTX78249 United States Beijing Institute of Technology Via Room 611 Software Building 5 South Zhongguancun Street Haidian Beijing100081 China Innovative Information Industry Research Institute Fujian Normail University Fuzhou350300 China Via Fuqing Brunch of Fujian Normal University Campus County 1# Longjiang Road FuqingFuzhou350300 China

In this study, we proposed a new method to determine the fuzzy boundary of natural language based on big data. According to the principle of natural language recognition, the acoustic characteristics of the analysis, natural language acoustic model and statistical model is established, Viterbi decoding algorithm has been applied for natural language decoding, and take this as the basis, we implemented deep learning methods for natural language feature extraction, and used the support vector machine method for classification, according to the characteristics of natural language significant division, in accordance with the constraints, combined with large data analysis method, to determine the natural language fuzzy boundary. Experimental results indicate that using the proposed method, compared with existing methods the recall and accuracy rate have been improved. © 2017 ISSN.

关键词： Big data

来源：评论

学校读者我要写书评

暂无评论

Design and implementation of a clock recovery circuit for fast Ethernet applications

引用

Chinese Journal of Systems Engineering and Electronics 2004年第4期000卷

A circuit architechure to realize clock recovery for fast Ethernet applications is presented, whick includies system architecture, modified Mueller Muller algorithm for 100BASE-TX, phase detector for 100BASE-TX and multiple output charge pump PLL. The clock recovery circuit is verified by TSMC 0.35um 1P5M CMOS process. The results show that this clock recovery circuit exactly extracts the timing information. It has advantages over others for simple and easy implementation.

关键词： clock recovery phase locked loop adaptive equalizer

来源：评论

学校读者我要写书评

暂无评论

Self adaptation of chimera states

arXiv

引用

arXiv 2018年

作者： Yao, Nan Huang, Zi-Gang Ren, Hai-Peng Grebogi, Celso Lai, Ying-Cheng Department of Applied Physics Xi’an University of Technology Xi’an710048 China School of Life Science and Technology Xi’an Jiao Tong University Xi’an710049 China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an710048 China Institute for Complex Systems and Mathematical Biology King’s College University of Aberdeen AberdeenAB24 3UE United Kingdom School of Electrical Computer and Energy Engineering Arizona State University TempeAZ85287 United States Department of Physics Arizona State University TempeAZ85287 United States

Chimera states in spatiotemporal dynamical systems have been investigated in physical, chemical, and biological systems, and have been shown to be robust against random perturbations. How do chimera states achieve their robustness? We uncover a self-adaptation behavior by which, upon a spatially localized perturbation, the coherent component of the chimera state spontaneously drifts to an optimal location as far away from the perturbation as possible, exposing only its incoherent component to the perturbation to minimize the disturbance. A systematic numerical analysis of the evolution of the spatiotemporal pattern of the chimera state towards the optimal stable state reveals an exponential relaxation process independent of the spatial location of the perturbation, implying that its effects can be modeled as restoring and damping forces in a mechanical system and enabling the articulation of a phenomenological model. Not only is the model able to reproduce the numerical results, it can also predict the trajectory of drifting. Our finding is striking as it reveals that, inherently, chimera states possess a kind of "intelligence" in achieving robustness through self adaptation. The behavior can be exploited for controlled generation of chimera states with their coherent component placed in any desired spatial region of the system. Copyright © 2018, The Authors. All rights reserved.

关键词： Dynamical systems

来源：评论

学校读者我要写书评

暂无评论

Artificial intelligence-based methods for renewable power system operation

Nature Reviews Electrical Engineering

引用

Nature Reviews Electrical Engineering 2024年第3期1卷 163-179页

作者： Yuanzheng Li Fei Hu Juntao Duan Yong Zhao Zhigang Zeng Yizhou Ding Shangyang He Guanghui Wen Hua Geng Zhengguang Wu Hoay Beng Gooi Chenghui Zhang Shengwei Mei Key Laboratory of lmage Information Processing and Intelligent Control of Ministry of Education of China School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China National Key Laboratory of Multispectral Information Intelligent Processing Technology Huazhong University of Science and Technology Wuhan China China-EU Institute for Clean and Renewable Energy Huazhong University of Science and Technology Wuhan China Department of Systems Science School of Mathematics Southeast University Nanjing China Department of Automation Tsinghua University Beijing China State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China School of Electrical and Electronics Engineering Nanyang Technological University Singapore Singapore School of Control Science and Engineering Shandong University Jinan China Department of Electrical Engineering Tsinghua University Beijing China

Carbon neutrality goals are driving the increased use of renewable energy (RE). Large-scale use of RE requires accurate energy generation forecasts; optimized power dispatch, which minimizes costs while satisfying operational constraints; effective system control to ensure a stable power supply; and electricity markets that support bidding and trading decisions associated with RE. However, the uncertainties in RE generation make renewable power systems challenging to operate. For example, the intermittent nature of wind power can make it difficult to balance the supply and demand of electricity in real time; therefore, traditional power sources could be needed to meet the demand, which can increase electricity prices. This Review outlines the potential of artificial intelligence-based methods for supporting renewable power system operation. We discuss the ability of machine learning, deep learning and reinforcement learning methods to facilitate power system forecasts, dispatch, control and markets to support the use of RE. We also emphasize the applicability of these techniques to different operational problems. Finally, we discuss potential trends in renewable power system development and approaches to address the associated operational challenges such as the increasingly distributed nature of RE installations, diversification of energy storage systems and growing market complexity.

关键词：

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：