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International Conference on Control engineering and Information System, ICCEIS 2014

作者： Liu, W. Jiangxi Key Laboratory of Data and Knowledge Engineering Institute of Information Resources Management Jiangxi University of Finance and Economics Nanchang China

ISBN: (纸本)9781138026858

This paper proposes an effective fusion of Analytic Hierarchy Process (AHP) and Grey Relational Analysis (GRA) approach for the risk evaluation in Mobile Commerce (MC) development. The hybrid method employs the complementary strength of these two appealing techniques, in which, the criteria weight obtained by applying AHP approach, and the GRA approach used to get the overall performance measure of MC risk. At last, experimental results are shown in this paper to verify the effectiveness of the hybrid model. © 2015 Taylor & Francis Group, London.

关键词： Analytic hierarchy process

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Layer-Wise Learning Rate Optimization for Task-Dependent Fine-Tuning of Pre-Trained Models: An Evolutionary Approach

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ACM Transactions on Evolutionary Learning and Optimization 2024年第4期4卷 1-23页

作者： Bu, Chenyang Liu, Yuxin Huang, Manzong Shao, Jianxuan Ji, Shengwei Luo, Wenjian Wu, Xindong Key Laboratory of Knowledge Engineering with Big Data Ministry of Education and School of Computer Science and Information Engineering Hefei University of Technology Hefei China School of Artificial Intelligence and Big Data Hefei University Hefei China Guangdong Provincial Key Laboratory of Novel Security Intelligence Technologies School of Computer Science and Technology Harbin Institute of Technology Shenzhen China

The superior performance of large-scale pre-Trained models, such as Bidirectional Encoder Representations from Transformers (BERT) and Generative Pre-Trained Transformer (GPT), has received increasing attention in both academic and industrial research and has become one of the current research hotspots. A pre-Trained model refers to a model trained on large-scale unlabeled data, whose purpose is to learn general language representation or features for fine-Tuning or transfer learning in subsequent tasks. After pre-Training is complete, a small amount of labeled data can be used to fine-Tune the model for a specific task or domain. This two-stage method of "pre-Training+fine-Tuning"has achieved advanced results in natural language processing (NLP) tasks. Despite widespread adoption, existing fixed fine-Tuning schemes that adapt well to one NLP task may perform inconsistently on other NLP tasks given that different tasks have different latent semantic structures. In this article, we explore the effectiveness of automatic fine-Tuning pattern search for layer-wise learning rates from an evolutionary optimization perspective. Our goal is to use evolutionary algorithms to search for better task-dependent fine-Tuning patterns for specific NLP tasks than typical fixed fine-Tuning patterns. Experimental results on two real-world language benchmarks and three advanced pre-Training language models show the effectiveness and generality of the proposed framework. © 2024 held by the owner/author(s).

关键词： Semantics

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Identifying Scientific and Technical“Unicorns”

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Journal of data and Information Science 2021年第2期6卷 96-115页

作者： Lucy L.Xu Miao Qi Fred Y.Ye Jiangsu Key Laboratory of Data Engineering and Knowledge Service School of Information ManagementNanjing UniversityNanjing 210023China University Library Nantong UniversityNantong 226019China

Purpose:Using the metaphor of"unicorn,"we identify the scientific papers and technical patents characterized by the informetric feature of very high citations in the first ten years after publishing,which may provide a new pattern to understand very high impact works in science and ***/methodology/approach:When we set CT as the total citations of papers or patents in the first ten years after publication,with CT≥5,000 for scientific"unicorn"and CT≥500 for technical"unicorn,"we have an absolute standard for identifying scientific and technical"unicorn"***:We identify 165 scientific"unicorns"in 14,301,875 WoS papers and 224 technical"unicorns"in 13,728,950 DII patents during 2001–*** 50%of"unicorns"belong to biomedicine,in which selected cases are individually *** rare"unicorns"increase following linear model,the fitting data show 95%confidence with the RMSE of scientific"unicorn"is 0.2127 while the RMSE of technical"unicorn"is *** limitations:A"unicorn"is a pure quantitative consideration without concerning its quality,and"potential unicorns"as CT≤5,000 for papers and CT≤500 for patents are left in future *** implications:Scientific and technical"unicorns"provide a new pattern to understand high-impact works in science and ***"unicorn"pattern supplies a concise approach to identify very high-impact scientific papers and technical ***/value:The"unicorn"pattern supplies a concise approach to identify very high impact scientific papers and technical patents.

关键词： Unicorn Scientific paper Technical patent Citation analysis Patent analysis

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Investigating Laws of Intelligence Based on AI IQ Research

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Annals of data Science 2020年第3期7卷 399-416页

作者： Liu, Feng Shi, Yong Research Center on Fictitious Economy and Data Science The Chinese Academy of Sciences Beijing100190 China The Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing100190 China The College of Information Science and Technology University of Nebraska at Omaha OmahaNE68118 United States

Based on the authors’ previous work on the research on the evaluation of artificial intelligence (AI) intelligence quotient and the Standard Intelligent Model, this paper proposes three laws of intelligence for interpreting the concepts of intelligence, wisdom, consciousness, life and non-life. The first law is called "M Law of Intelligence" where any Agent can be regarded as a system that has the abilities to input, output, storage (master) and creative (innovate) knowledge. The second law is called "Ω Law of Intelligence" in which any Agent is affected by new "forces" FΩ and Fα derived in this paper, which evolve to Ωpoint whose knowledge processing ability is infinite, or converge to αpoint whose knowledge processing ability is zero. The third law is called "Α Law of Intelligence", that is, when an Agent changes surrounding αpoint, the entire Universe relative to the Agent will also change between infinity and zero. The Three Laws need to be validated by a biochemical experiment method, an AI system intelligence evaluation experiment method or the computer program simulation experiment method. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Software engineering

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Numerical simulation of force suppression for flow circular cylinder at low reynolds number

International Journal of Control and Automation

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International Journal of Control and Automation 2015年第12期8卷 207-216页

作者： Cui, Zhendong Gu, Shenming Gong, Xiwu School of Mathematics Physics and Information Science Zhejiang Ocean University Zhoushan China Key Laboratory of Oceanographic Big Data Mining and Application of Zhejiang Province Zhoushan Zhejiang China Key Laboratory of Offshore Engineering Technology of Zhejiang Province Zhoushan Zhejiang China

Numerical simulation was conducted for fluid flow past a circular cylinder with triangular control rod in the upstream at low Reynolds numbers. The study focuses on the influences of leg length of rod L, rod-to-cylinder spacing ratio S, vertex angle of triangular a of rod on the vortex shedding and forces. The results show the equilateral triangle rod in the upstream takes effective suppression of not only the lift but also the drag in the range of 0.2R≤L≤0.5R and 3R≤S≤6R(R is the radius of circular cylinder), and the vortex shedding between the two cylinders maybe lead to sharp increasing of the force on the circular cylinder. © 2015 SERSC.

关键词： Circular cylinders

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Research on mining Global Maximal Frequent Itemsets for Health Big data 3rd

Research on Mining Global Maximal Frequent Itemsets for Heal...

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2017 IEEE 第3届信息技术与机电一体化工程国际学术会议(ITOEC 2017)

作者： Bo He Jianhui Pei School of Computer Science and Engineering ChongQing University of Technology Key Laboratory of Statistical information technology and data mining State Statistics BureauChengDu University of Information Technology Guizhou Key Laboratory of Power Big Data Guizhou Institute of Technology

Traditional mining algorithms did not suit mining of global maximal frequent ***,a new mining algorithm of global maximal frequent itemsets for health big data,namely,NMAGMFI algorithm

ISBN: (纸本)9781509053643;9781509053636

Traditional mining algorithms did not suit mining of global maximal frequent ***,a new mining algorithm of global maximal frequent itemsets for health big data,namely,NMAGMFI algorithm

关键词： Itemsets data mining Frequency modulation Big data Algorithm design and analysis Information technology

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Trade credit or credit insurance? A green supply chain finance design scheme with multi-objective programming

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Journal of Intelligent and Fuzzy Systems 2023年第2期45卷 2707-2721页

作者： Zhang, Linzi Shi, Yong School of Economics and Management University of Chinese Academy of Sciences Beijing China University of Birmingham Edgbaston Birmingham United Kingdom Research Center on Fictitious Economy Data Science Chinese Academy of Science Beijing China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing China

Classical supply chain finance (SCF) primarily focuses on the financial service among all upstream and downstream supply chain participants. Due to the continuously deteriorating of the ecological environment, an environmental-friendly SCF system is urgently needed. In this paper, we propose a novel SCF design scheme with environmental concerns, i.e., green supply chain finance (GSCF), consider the financing channels both from banks and from consumers, and design a bi-objective optimization model that depicts the trade-off between the benefit and the emission. Further, an improved normalized normal constraint (INNC) Pareto method is developed to address the optimal financing strategy of the bi-objective model. We then conduct a numerical case of a Taiwanese steel firm to verify the effectiveness and efficiency of our method. Results show that our model provides a portfolio of optimal solutions on Pareto frontier which can be applied as an effective decision support system when designing a GSCF. Furthermore, the sensitivity analysis also presents the impact of environmental investment cost, technological ratio of companies and the interest rate of trade credit on the optimal configuration of the GSCF. © 2023 - IOS Press. All rights reserved.

关键词： Multiobjective optimization

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A novel self-adaptive density-based clustering algorithm for radar signal sorting

A novel self-adaptive density-based clustering algorithm for...

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IET International Radar Conference 2015

作者： Liu, Ying Cui, Hongyuan School of Computer and Control University of Chinese Academy of Sciences China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing100190 China

ISBN: (纸本)9781849199940

Radar signal sorting, which de-interleaves pulse sequences from different radar emitters, is one of the key techniques in Electronic Support Measures (ESM) system of modern warfare. As the electromagnetic environment in modern electronic wars is complex and dense, conventional multi-parameter de-interleaving techniques cannot achieve satisfactory accuracy. Although clustering algorithms have shown promising results in signal sorting, they all have their own weaknesses. In this paper, we propose a novel densitybased clustering algorithm targeting radar signal sorting problem. Our clustering algorithm determines the number of clusters and the density thresholds by the distribution of the data itself rather than depending on user experience as in K-Means or other existing density-based algorithms. Multiple density thresholds may be generated when necessary. We ran our algorithm on a set of simulation radar data. It outperforms DBSCAN-based signal sorting algorithm a lot in terms of accuracy, missing sorting rate and the error sorting in each set of parameters. In addition, it is observed that our algorithm is insensitive to the parameters, ratio factor, uniformity, and quantile. Thus, our proposed self-adaptive density-based clustering algorithm is promising in solving radar signal sorting problem in real electromagnetic environment.

关键词： Sorting

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Analyzing Multiple Phenotypes Based on Principal Component Analysis

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Acta Mathematicae Applicatae Sinica 2022年第4期38卷 843-860页

作者： De-liang BU San-guo ZHANG Na LI School of Mathematical Sciences University of Chinese Academy of SciencesBeijing 100049China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of SciencesBeijing 100049China LSC NCMISAcademy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China

Joint analysis of multiple phenotypes can have better interpretation of complex diseases and increase statistical power to detect more significant single nucleotide polymorphisms(SNPs)compare to traditional single phenotype analysis in genome-wide association *** component analysis(PCA),as a popular dimension reduction method,has been broadly used in the analysis of multiple *** PCA transforms the original phenotypes into principal components(PCs),it is natural to think that by analyzing these PCs,we can combine information across *** PCA-based methods can be divided into two categories,either selecting one particular PC manually or combining information from all *** this paper,we propose an adaptive principle component test(APCT)which selects and combines the PCs adaptively by using Cauchy combination *** proposed method can be seen as a generalization of traditional PCA based method since it contains two existing methods as special *** simulation shows that our method is robust and can generate powerful result in various *** real data analysis of stock mice data also demonstrate that our proposed APCT can identify significant SNPs that are missed by traditional methods.

关键词： multiple phenotypes principal component analysis cauchy combination method

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An incremental mining algorithm for global maximum frequent itemsets based on health big data 2

An incremental mining algorithm for global maximum frequent ...

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2017 IEEE 2nd Information Technology, Networking, Electronic and Automation Control Conference (ITNEC 2017)

作者： Bo He Jianhui Pei Hongyuan Zhang School of Computer Science and Engineering ChongQing University of Technology Key Laboratory of Statistical information technology and data mining State Statistics Bureau ChengDu University of Information Technology Guizhou Key Laboratory of Power Big Data Guizhou Institute of Technology

ISBN: (纸本)9781509064151;9781509064144

The global maximum frequent itemsets need to be updated because of incremental distributed database. On the base of the fast mining algorithm for global maximum frequent itemsets, an incremental mining algorithm for global maximum frequent itemsets based on health big data was proposed, namely,IMAGMFI algorithm. Firstly, the global frequent items were ***, the FP-tree was reconstructed by incremental distributed database. Third, the global maximum frequent itemsets of incremental distributed database were mined. Last,the global maximum frequent itemsets were gained by the strategy of top-down. The experimental results show that IMAGMFI algorithm is effective.

关键词： FP-tree Global Maximum Frequent Itemset Increasing mining Algorithm

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