检索结果-内蒙古大学图书馆

IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA)

作者： Tingfeng Liu Hui Gao Jianjun Wu College of Information Science and Engineering Henan University of Technology Zhengzhou China Key Laboratory of Grain Information Processing and Control College of Information Science and Engineering Henan University of Technology Ministry of Education Zhengzhou China

ISBN: (数字)9781728170053

ISBN: (纸本)9781728170060

Outliers may be objectively existing data generated by mechanisms different from most data, and have related laws and certain research value. Outliers have been widely used in recent years, including financial fraud, cyber fraud, and abnormal weather warnings. Traditional outlier detection algorithms such as statistical-based outlier detection, cluster-based outlier detection, deviation-based outlier detection, distance-based outlier detection, density-based outlier detection, etc., but there are many shortcomings in the traditional outlier detection algorithms. Outlier detection algorithms based on information entropy, outlier detection algorithms based on spectral clustering, etc. have gradually appeared. Because in practice, traditional outlier detection algorithms cannot perform good detection applications on high-dimensional data, spatial data, and time series data, so they are performed for high-dimensional outlier detection, space outlier detection, and time series outlier detection. Dedicated research. How to improve the effectiveness, scalability and space-time efficiency of the algorithm will be the future research direction.

关键词： Anomaly detection Clustering algorithms Time series analysis Spatial databases Prediction algorithms Classification algorithms

来源：评论

学校读者我要写书评

暂无评论

Spatiotemporal Evolution Analysis of NO 2 Column Density before and after COVID-19 Pandemic in henan Province Based on SI-APSTE Model

Research Square

引用

Research Square 2021年

作者： Liu, Yang Zhao, Jinhuan Song, Kunlin Cheng, Cheng Li, Shenshen Cai, Kun Henan Engineering Laboratory of Spatial Information Processing Henan Key Laboratory of Big Data Analysis and Processing School of Computer and Information Engineering Henan University Kaifeng475004 China State Key Laboratory of Remote Sensing Science Aerospace Information Research Institute Chinese Academy of Sciences Beijing100101 China School of Information and Electronics Beijing Institute of Technology Beijing100081 China

Air pollution is the result of comprehensive evolution of a dynamic and complex system composed of emission sources, topography, meteorology and other environmental factors. The establishment of spatiotemporal evolution model is of great significance for the study of air pollution mechanism, trend prediction, identification of pollution sources and pollution control. In this paper, the air pollution system is described based on cellular automata and restricted agents, and a Swarm Intelligence based Air Pollution SpatioTemporal Evolution (SI-APSTE) model is constructed. Then the spatiotemporal evolution analysis method of air pollution is studied. Taking henan Province before and after COVID-19 pandemic as an example, the NO2 products of TROPOMI and OMI were analysed based on SI-APSTE model. The tropospheric NO2 Vertical Column Densities (VCDs) distribution characteristics of spatiotemporal variation of henan province before COVID-19 pandemic were studied. Then the tropospheric NO2 VCDs of TROPOMI was used to study the pandemic period, month-on-month and year-on-year in 18 urban areas of henan Province. The results show that SI-APSTE model can effectively analyse the spatiotemporal evolution of air pollution by using environmental big data and swarm intelligence, and also can establish a theoretical basis for pollution source identification and trend prediction. © 2021, CC BY.

关键词： Air pollution

来源：评论

学校读者我要写书评

暂无评论

A layered parallel algorithm for data clustering via fuzzy c-means technique

Research Square

引用

Research Square 2021年

作者： Mu, Yashuang Wei, Wei Guo, Hongyue Sun, Lijun Key Laboratory of Grain Information Processing and Control Henan University of Technology Ministry of Education Zhengzhou450001 China School of Artificial Intelligence and Big Data Henan University of Technology Zhengzhou450001 China College of Information Science and Engineering Henan University of Technology Zhengzhou450001 China School of Maritime Economics and Management Dalian Maritime University Dalian116026 China Collaborative Innovation Center for Transport Studies Dalian Maritime University Dalian116026 China

In this study, a layered parallel algorithm via fuzzy c-means (FCM) technique, called LP-FCM, is proposed in the framework of Map-Reduce for data clustering problems. The LP-FCM mainly contains three layers. The first layer follows a parallel data partitioning method which is developed to randomly divide the original dataset into several subdatasets. The second layer uses a parallel cluster centers searching method based on Map-Reduce, where the classic FCM algorithm is applied to search the cluster centers for each subdataset in Map phases, and all the centers are gathered to the Reduce phase for the confirmation of the final cluster centers through FCM technique again. The third layer implements a parallel data clustering method based on the final cluster centers. After comparing with some famous classic random initialization sequential clustering algorithms which include K-means, K-medoids, FCM and MinMaxK-means on 20 benchmark datasets, the feasibility in terms of clustering accuracy is evaluated. Furthermore, the clustering time and the parallel performance are also tested on some generated large-scale datasets for the parallelism. © 2021, CC BY.

关键词： K-means clustering

来源：评论

学校读者我要写书评

暂无评论

Classification and Quantitative Modeling Analysis of Groundwater Hardness based on Ultraviolet Absorption Spectrum

引用

Journal of Physics: Conference Series 2021年第1期1746卷

作者： Guofang Wu Feiyu Lian Maixia Fu Yuan Zhang School of Information Science and Engineering Henan University of Technology Key Laboratory of Grain Information Processing and Control Ministry of Education Henan University of Technology Zhengzhou 45001 Key Laboratory of Grain Photoelectric Detection and Control Henan Province Henan University of Technology Zhengzhou 45001

In accordance with the national standard of groundwater quality, samples with various ion concentrations are prepared based on water hardness standard substances, and a water hardness classification and quantitative analysis model based on ultraviolet absorption spectrum are established. Firstly, thepartial least squares discriminant analysis (PLSDA) model is established by using a group of samples with different ion concentration that form the training set, and the binary tree is introduced for multiple classification of water hardness. Secondly, partial least squares support vector machine (PLS-SVM) is used to establish the quantitative model of each class of samples. Atlast, Monte carlo cross-examination is performed on the model using a test set composed of samples with different ion concentrations. Experimental results show that, for the identification of underwater hardness, the average error rate is 1.13%, which is less than other common classification methods, and MSE is 0.247, and R2 is 0.987, which both are improved than other common methods for the prediction of ion concentration of underwater.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Screening of the critical control points of microbial contamination in the production line of Liangpi by microbial profiling analysis and the spoilage potential assessment of dominant microorganisms

引用

LWT 2025年 227卷

作者： Shijia Fan Xiaojie Wang Meiran Tang Yi Li Zhen Li Zequn Zhang Biao Suo College of Food Science and Technology Henan Agricultural University Zhengzhou China Key Laboratory of Staple Grain Processing Ministry of Agriculture and Rural Affairs Zhengzhou China National R&D Center for Frozen Rice & Wheat Products Processing Technology Henan Province Engineering Research Center of Quick-Frozen Flour-Rice and Prepared Food Henan Agricultural University Zhengzhou China

To reveal the critical control points for microbial safety in the production line of Liangpi (steamed cold noodles, SCN), we collected 360 samples from the production line in a factory. The microbial loads were always the highest in the semifinished products, finished products and inner wall of the pipelines. The microbial load on the equipment surface in summer was significantly greater than that in winter ( P < 0.05), and more than 10 3 log CFU/cm 2 of Staphylococcus aureus , Bacillus cereus and lactic acid bacteria (LAB) adhered to the inner walls of the raw slurry and finished slurry pipelines as well as the surface of the conveyor belt. Lactococcus , Acinetobacter , Leuconostoc , Saccharomycetaceae (f), and Aspergillaceae (f) were the dominant microorganisms in the SCN production line. The microbial profiling revealed that the surface of the processing equipment, finished slurry and raw and auxiliary materials were the critical control points. The effective use of whey fermentation powder in controlling the finished slurry significantly reduced the initial total plate count (TPC) of SCN. B. cereus L17 and B. cereus L18, which can decompose starch, had the strongest ability to cause spoilage of SCN. The results provide theoretical guidance for the safety control of SCN.

关键词： Liangpi Production line High-throughput sequencing (HTS) Critical control points Spoilage potential

来源：评论

学校读者我要写书评

暂无评论

A Comparison of Dndc and Daycent to Evaluate Greenhouse Gas Emissions from China's Main Cropping Systems

SSRN

引用

SSRN 2023年

作者： Wang, Junyi Kuhnert, Matthias Abdalla, Mohamed Smith, Pete Ding, Weixin Yan, Xiaoyuan Zou, Jianwen Guo, Shiwei Fan, Jianling Jiang, Yanbin Hu, Ronggui Li, Fusheng Guo, Yanbin Chen, Zengming Zhao, Xu Xie, Yingxin Institute of Biological & Environmental Science University of Aberdeen 23 St Machar Drive AberdeenAB24 3UU United Kingdom State Key Laboratory of Soil and Sustainable Agriculture Institute of Soil Science Chinese Academy of Sciences Nanjing210008 China Jiangsu Key Laboratory of Low Carbon Agriculture and GHGs Mitigation College of Resources and Environmental Sciences Nanjing Agricultural University Nanjing China Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control School of Environmental Science and Engineering Nanjing University of Information Science & Technology China Ministry of Agriculture College of Resources and Environment Huazhong Agricultural University Wuhan430070 China College of Agriculture Guangxi University Nanning530004 China Beijing Key Laboratory of Biodiversity and Organic Farming College of Resources and Environmental Sciences China Agricultural University Beijing100193 China National Engineering Research Center for Wheat State Key Laboratory of Wheat and Maize Crop Science Collaborative Innovation Center of Henan Grain Crops Henan Agricultural University Zhengzhou450046 PR China

China contributes the largest share of cropland’s greenhouse gas (GHG) emissions globally. Processed-based biogeochemical models are useful tools to simulate GHG emissions from cropping systems. However, model comparisons are necessary to provide information for the application of models under different climate, soil, and crop conditions. In this study, two widely-used models (DayCent and DNDC) were evaluated and compared under four main cropping systems in China. The field observations from nine experiments were used for model calibration and validation. The DayCent and DNDC models simulated daily and seasonal CH4 emissions from early rice-late rice and rice-wheat cropping systems reasonably well (r2≥0.49 for daily simulation and nRMSE≤52.9% for seasonal simulation). Both models were able to satisfactorily predict seasonal N2O emissions from maize-wheat fields (0.6≤d≤0.8), but overestimated most daily N2O fluxes at fertilisation and irrigation events. Significantly positive relationships were found between simulated and observed cumulative N2O fluxes in spring maize growing season (0.61≤ r2≤0.85). The DNDC showed smaller differences in simulated and observed cumulative GHG emissions for spring maize and double rice, while DayCent showed better performance on estimating N2O and CH4 for maize-wheat and rice-wheat. This study shows that both models have strengths and weaknesses under a variety of cropping systems and growing regions, which are important to consider when choosing a model for a crop/region-specific simulation. © 2023, The Authors. All rights reserved.

关键词： Crops

来源：评论

学校读者我要写书评

暂无评论

Nonreciprocal tripartite entanglement and asymmetric Einstein-Podolsky-Rosen steering via directional quantum squeezing

arXiv

引用

arXiv 2024年

作者： Jiao, Ya-Feng Wang, Jie Wang, Dong-Yang Tang, Lei Wang, Yan Zuo, Yun-Lan Bao, Wan-Su Kuang, Le-Man Jing, Hui School of Electronics and Information Zhengzhou University of Light Industry Zhengzhou450001 China Academy for Quantum Science and Technology Zhengzhou University of Light Industry Zhengzhou450001 China Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control of Ministry of Education Department of Physics Synergetic Innovation Center for Quantum Effects and Applications Hunan Normal University Changsha410081 China School of Physics Zhengzhou University Zhengzhou450001 China College of Physics and Electronic Engineering Institute of Solid State Physics Sichuan Normal University Chengdu610101 China School of Physics and Chemistry Hunan First Normal University Changsha410205 China Henan Key Laboratory of Quantum Information and Cryptography IEU Zhengzhou450001 China

The generation and manipulation of multipartite entanglement and EPR steering in macroscopic systems not only play a fundamental role in exploring the nature of quantum mechanics, but are also at the core of current developments of various nascent quantum technologies. Here we report a theoretical method using directional injection of quantum squeezing to produce nonreciprocal multipartite entanglement and EPR steering in a three-mode optomechanical system with closed-loop coupling. We show that by directionally applying a two-photon parametric driving field with a phase-matched squeezed vacuum reservoir to an optomechanical resonator, a squeezed optical mode can be introduced for one of its input directions, thereby yielding an asymmetric enhancement of optomechanical interaction and the time-reversal symmetry breaking of the system. Based on this feature, it is found that bipartite and tripartite entanglement and the associated EPR steering of the subsystems can only be generated when the coherent driving field input from the squeezing injection direction, namely, achieving nonreciprocity in such quantum correlations. More excitingly, it is also found that by properly adjusting the squeezing parameter, the overall asymmetry of EPR steering can be stepwise driven from no-way regime, one-way regime to two-way regime. These findings, holding promise for preparing rich types of entangled quantum resources with nonreciprocal correlations, may have potential applications in the area of quantum information processing such as quantum secure direct communication and one-way quantum computing. Copyright © 2024, The Authors. All rights reserved.

关键词： Quantum computers

来源：评论

学校读者我要写书评

暂无评论

Adaptive fixed-time output synchronization of MWRDNNs with delayed output couplings

引用

Journal of the Franklin Institute 2025年第10期362卷

作者： Qian Qiu Jingjing Li Jiayuan Yan Hongtai Yao Housheng Su School of Artificial Intelligence Henan University Zhengzhou 450046 China Hanjiang National Laboratory Wuhan 430060 China National Key Laboratory of Multispectral Information Intelligent Processing Technology School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan 430074 China

This work develops an adaptive output feedback control technique to make multi-weight reaction–diffusion neural networks (MWRDNNs) with delayed output couplings be fixed-time output synchronized. Unlike earlier related works, the proposed control algorithm introduces an adaptive law to timely update the control gain of the node, avoiding dependence on global information of the network. Additionally, the algorithm incorporates integral terms with multiple coupling delays, mitigating the impact of multiple coupling delays in the network. By adopting the Lyapunov functional method, fixed-time stability theory, and key inequality techniques, the fixed-time output synchronization (OS) criterion is derived, and the settling time is obtained, which avoids the defect of relying on the initial value of the system. Concurrently, a corollary states that the fixed-time OS can be reached for MWRDNNs without output coupling delays through a node-based adaptive adjustment scheme. Lastly, the effectiveness of the developed control methods is validated by the correlation results obtained from two numerical simulation examples.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Exploiting boundary-isolated multiple edge-spanning tree for node shielding-based network robustness enhancement

引用

Expert Systems with Applications 2025年 287卷

作者： Wei, Wei Jiang, Mingkun Zhang, Qinghui Li, Peng Ma, Tao Li, Weidong Ministry of Education Zhengzhou450001 China Henan Key Laboratory of Grain Storage Information Intelligent Perception and Decision Making Henan University of Technology Zhengzhou450001 China Institute for Complexity Science Henan University of Technology Zhengzhou450001 China Beijing Institute of Technology No. 5 Zhongguancun South Street Haidian District Beijing100086 China Technology Ltd Zhengzhou450001 China

As a critical network protection strategy, shielding vulnerable nodes can help build robust networks, where robustness can be generally measured using network connectivity, or complex metrics adapted to specific scenarios. However, the general connectivity-oriented node shielding is NP-hard and few methods can be applied in large-scale networks. The existing limited one can only achieve a far from optimal solution, where the core problem is that it shields the vulnerable part of the graph to infinite connectivity. We analyzed the spanning tree strategy and found a special kind of structure that is a superset of node cut sets, and any combination of nodes in the structure cannot form node cut sets smaller than the threshold. By using the structure as a boundary and shielding separate components, the algorithm can further prevent a large percentage of nodes from shielding without affecting robustness, and thus significantly reduce the cost of shielding. Experimental results in small and large scale graphs reveals that it is more than 105 times efficient than the optimal method while only introducing about 2 % extra cost. The shield ratio in large graphs can be more than 99.9 % and the cost saving ratio can be more than 60 % compared to the existing one, where the ratio is much lower in other heuristics. © 2025 Elsevier Ltd

关键词： Trees (mathematics)

来源：评论

学校读者我要写书评

暂无评论

RFBLS: A robust rough fuzzy broad learning system with local neighborhood structure

引用

Neurocomputing 2025年 647卷

作者： Yonghe Chu Yanlong Guo Peng Li Weiping Ding Witold Pedrycz Heling Cao School of Artificial Intelligence and Computer Science Nantong University Nantong 226019 China College of Information Science and Engineering Henan University of Technology Zhengzhou 450001 China Key Laboratory of Grain Information Processing and Control(Henan University of Technology) Ministry of Education Zhengzhou 450001 China Centre for Complexity Science Henan University of Technology Zhengzhou 450001 China Department of Electrical and Computer Engineering University of Alberta Edmonton AB T6G 2R3 Canada Institute of Systems Engineering Macau University of Science and Technology Macau SAR Taipa 999078 China Research Center of Performance and Productivity Analysis Istinye University Istanbul Turkiye

As an extension of random vector functional link neural network (RVFLNN), the broad learning system (BLS) has gradually been applied in various fields due to its advantages of simple network structure, rapid training, and fast model updating. Despite its remarkable achievements, there are still some difficulties and challenges that restrict its further application in practical tasks. In BLS, all samples equally contribute to constructing the optimal classification boundary. However, when training samples contain noise or outliers, it will result in the obtained classification boundary not being the true optimal classification boundary. In other words, BLS is sensitive to noise points or outliers. To address it, we propose a robust rough fuzzy broad learning system with local neighborhood structure (RFBLS). In RFBLS, fuzzy sets are utilized by associating a membership degree with each sample. This incorporation ensures diverse contributions of different samples during the minimization of the objective function. Samples with noise or outliers are assigned smaller weights, effectively eliminating the influence of noise and outlier samples in the learning process. We employ the rough set theory to explore the influence-decision degree of each conditional attribute on the decision attribute, aiming to eliminate the impact of redundant or interfering features. Subsequently, we comprehensively consider the distance between samples and class centers, as well as the local neighborhood structure relationship between samples. Initially, we calculate the initial membership degree of each sample based on the distance to class centers. Then, utilizing fuzzy K-nearest neighbors, we calculate and rank the membership degrees of K nearest neighbors for each sample. These rankings are then weighted with the initial membership degree, achieving the fusion of relationships and membership degree calculations between samples. Finally, extensive comparative experiments are conducted on var

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：