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5th International Conference on Natural Computation, ICNC 2009

作者： Zhang, Hong-Juan Ning, Hong-Yun Tianjin Key Lab of Intelligent Computing and Novel Software Technology Tianjin University of Technology Tianjin 300191 China Key Laboratory of Computer Vision and System Ministry of Education Tianjin University of Technology Tianjin300191 China

ISBN: (纸本)9780769537368

To improve the convergence time of Ant Colony Algorithm, avoid falling in local best and enhance the quality of solution, a novel dynamic parameters ant colony algorithm with particle swarm characteristics is proposed. Learning the multi-information instruction characteristic of Particle Swarm Optimization Algorithm, the global pheromone update rule with particle swarm characteristic is introduced to improve the directive function of pheromone and the speed of convergence. At the same time, solution multiplicity is guaranteed as far as possible. Using the function of current condition to update particle speed and position, parameters of Ant Colony Algorithm is used to reflect the current condition. Hyperbola Tangent function is imported to dynamic adjust parameters so that the relation between local search and global search could be balanced. Comparing with basic Ant Colony Algorithm, the simulation result on TSP shows that new algorithm has higher convergence speed and better solution. © 2009 IEEE.

关键词： Particle swarm optimization (PSO)

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Automatic Web service composition based on Horn clauses and Petri nets

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Expert systems with Applications 2011年第10期38卷 13024-13031页

作者： Tang, Xianfei Jiang, Changjun Zhou, Mengchu Department of Computer Science and Technology Tongji University Shanghai 201804 China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 201804 China Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ 07102 United States

This paper introduces an automatic Web service composition method based on logical inference of Horn clauses and Petri nets. The Web service composition problem is transformed into the logical inference problem of Horn clauses by exploring the dependency relations among services. An algorithm is presented, to determine whether the composite service exists in time that is linear in the size of the knowledge base. It can also return the rule set necessary for the composition. Petri nets are chosen to model the rule set and its structural analysis techniques are used to obtain the composite service. © 2010 Elsevier Ltd. All rights reserved.

关键词： Automatic reasoning Knowledge base Petri nets service composition Web service

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ScIAMC:Single-Cell Imputation via adaptive matrix completion 10

ScIAMC:Single-Cell Imputation via adaptive matrix completion

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10th IEEE International Conference on Cyber Security and Cloud computing and 9th IEEE International Conference on Edge computing and Scalable Cloud, CSCloud-EdgeCom 2023

作者： Zhang, Shuai Chen, Xiang Peng, Li Hunan University of Science and Technology School of Computer Science and Engineering Xiangtan Hunan411201 China Hunan Key Laboratory for Service computing and Novel Software Technology China

ISBN: (纸本)9798350312461

Single-cell sequencing techniques are often impacted by technical noise, leading to the generation of very sparse expression matrices. This technical noise is referred to as dropouts and poses as a major challenge for downstream analysis. In this study, we introduce scIAMC (single-cell imputation via adaptive parameter matrix completion), which is based on matrix completion theory to recover missing values in expression matrices. To expedite the algorithm's running time and avoid any parameter tuning on data, we formulated an optimization problem. Our approach led to an enhanced cell population identification and minimal errors, while also restoring biological landscapes that were damaged by these dropouts. © 2023 IEEE.

关键词： Cell proliferation

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Towards Using Local Process Mining to Analyse Learning Behavior Pattern 17th

Towards Using Local Process Mining to Analyse Learning Behav...

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17th CCF Conference on Computer Supported Cooperative Work and Social computing, ChineseCSCW 2022

作者： Ouyang, Sipeng Wen, Yiping Liu, Jianxun Qi, Lianyong Hunan Key Laboratory for Service Computing and Novel Software Technology Hunan University of Science and Technology Xiangtan411201 China Qufu Normal University Qufu273165 China

ISBN: (纸本)9789819923557

Learning behavior is the key factor to promote the occurrence of effective learning. Analyzing learning behavior pattern is helpful to understand the common learning behavior of different types of learners. This paper introduces the application of traditional process mining methods such as Sequence Miner, Heuristics Miner and Inductive Miner in the area of learning behavior analysis. The shortcomings of these methods are also analyzed. To overcome their shortcomings, a method of local process mining-based learning behavior pattern analysis is proposed in this paper. Comparative experiments based on real data sets are performed to verify its effectiveness. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Data mining

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Facial StO2-based Stress Recognition using Automatic Graph Generation and Dual-Stream GNN

Facial StO2-based Stress Recognition using Automatic Graph G...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Jia, Yingjuan Wang, Hanpu Liu, Xinyu Chen, Tong Southwest University College of Electronic and Information Engineering 400715 China Southwest University Chongqing Key Laboratory of Generic Technology and System of Service Robots China Southwest University Institute of Legal Psychology and Intelligent Computing 400715 China

ISBN: (纸本)9798350386226

The recognition of stress responses in health, resilience, and psychopathology holds significant scientific importance. The biological information carried by the facial tissue oxygen saturation (StO2) is a useful indicator for stress recognition. Although graph-based methods have achieved state-of-the-art (SOTA), there is room for improvement. This study proposes an automatic graph generation method for facial StO2, replacing manual methods and enhancing the information of graphs. To further enhance the capability of graphs' representation, a dimensionality reduction strategy for nodes is proposed. The strategy is implemented based on an novel objective function that can increase the inter-class distance and reduce the intra-class distance. After obtaining highly representative graphs, a dual-stream network integrating GAT and GCN is designed to extract stress-related features from the graphs, ultimately achieving the SOTA recognition accuracy. © 2024 IEEE.

关键词： Bioinformatics

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Solving economic dispatch problem in energy internet using a two-level stochastic gossip-based consensus algorithm

Solving economic dispatch problem in energy internet using a...

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2014 International Conference on Energy Research and Power Engineering, ERPE 2014

作者： Meng, Jie Zhang, Yan Zhang, Tao College of Information System and Management National University of Defense Technology Changsha China State Key Laboratory of High Performance Computing National University of Defense Technology Changsha China

ISBN: (纸本)9783038351603

In the future, energy Internet will gradually replace the traditional power network since it enables flexible energy sharing for consumers. Consensus algorithm achieved good performance in solving economic dispatch problem in microgrid system whereas the difficulty is finding a consensus variable. By means of choosing the incremental generator cost of each energy local area network (ELAN) as the consensus variable, the economic dispatch problem can be solved. Using the stochastic gossip-based algorithm as the basic framework, the economic dispatch problem can be solved in a distributed manner. In order to meeting the real-time load requirement in time under the fixed communication topology, the fluctuation of each ELAN will do the consensus update at the same time. The result of a representative case is presented to illustrate the performance of the proposed two-level stochastic gossip-based consensus algorithm. © (2014) Trans Tech Publications, Switzerland.

关键词： Scheduling

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A review on the system energy management of Energy Internet 5

A review on the system energy management of Energy Internet

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5th International Conference on Logistics and Supply Chain Management, LSCM 2015

作者： Zhang, Tao Zhang, Fu-Xing Wang, Rui Zhang, Yan Zhang, Xiao-Yu College of Information System and Management National University of Defense Technology Changsha China State Key Laboratory of High Performance Computing National University of Defense Technology Changsha China

ISBN: (纸本)9781510818071

Energy Internet(EI) as the future solution to the shortage of fossil energy and the worsening environment problem, is becoming the hotspot and the trend of the research. Firstly, the paper expounds the connotation and features of Energy Internet, and put forward the new requirements of the Energy Internet system energy management with four elements, namely the grid structure, consumptive pattern, measuring method and research perspective. Secondly, summarizes the related research at home and abroad of Energy Internet system energy management on the aspect of system structure design, robust modeling of energy management and optimization algorithm design. Finally, the future issue of Energy Internet system energy management research is prospected.

关键词： Energy management

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ESR: Optimizing Gene Feature Selection for scRNA-seq Data 10

ESR: Optimizing Gene Feature Selection for scRNA-seq Data

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10th IEEE International Conference on Cyber Security and Cloud computing and 9th IEEE International Conference on Edge computing and Scalable Cloud, CSCloud-EdgeCom 2023

作者： Huang, Tao Chen, Xiang Peng, Li Hunan University of Science and Technology School of Computer Science and Engineering Xiangtan Hunan411201 China Hunan Key Laboratory for Service computing and Novel Software Technology China

ISBN: (纸本)9798350312461

The rapid development of single-cell RNA sequencing (scRNA-seq) technology has enabled researchers to explore gene expression differences at the level of individual cells, revealing more refined cell types and states. However, due to the low expression and high noise of scRNA-seq data, feature selection has become particularly important in the analysis of single-cell data. Here, we introduce the Entropy Stepwise Regression (ESR) method for feature selection. This method utilizes the correlation between genes and the entropy values of each feature to filter out genes that are conducive to downstream analysis. In mouse kidney samples, we compared the performance of three methods in terms of Adjusted Rand Index and achieved good results. This indicates that the method can improve the accuracy of downstream analysis. © 2023 IEEE.

关键词： Entropy

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KNOB particle swarm optimizer 1

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1st International Conference on Advances in Swarm Intelligence, ICSI 2010

作者： Zhang, Junqi Liu, Kun Tan, Ying Key Laboratory of Embedded System and Service Computing Department of Computer Science and Technology Tongji University Shanghai 200092 China Department of Machine Intelligence School of Electronics Engineering and Computer Science Peking University Beijing 100871 China

ISBN: (数字)9783642134951

ISBN: (纸本)3642134947

It is not trivial to tune the swarm behavior just by parameter setting because of the randomness, complexity and dynamic involved in particle swarm optimizer (PSO). Hundreds of variants in the literature of last decade, brought various mechanism or ideas, sometimes also from outside of the traditional metaheuristics field, to tune the swarm behavior. While, in the same time, additional parameters have to be afforded. This paper proposes a new mechanism, named KNOB, to directly tune the swarm behavior through parameter setting of PSO. KNOB is defined as the first principal component of the statistical probability sequence of exploration and exploitation allocation along the search process. The using of the KNOB to tune PSO by parameter setting is realized through a statistical mapping, between the parameter set and the KNOB, learned by a radial basis function neural network (RBFNN) simulation model. In this way, KNOB provides an easy way to tune PSO directly by its parameter setting. A simple application of KNOB to promote is presented to verify the mechanism of KNOB. © 2010 Springer-Verlag.

关键词： Particle swarm optimization (PSO)

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A Cloudedge-Combined Data Placement Strategy Based on User Access Regions 6

A Cloudedge-Combined Data Placement Strategy Based on User A...

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6th International Conference on Big Data and Information Analytics, BigDIA 2020

作者： Cao, Eryang Wang, Pengwei Yan, Chungang Jiang, Changjun Department of Computer Science and Technology Tongji University Shanghai200092 China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai200092 China School of Computer Science and Technology Donghua University Shanghai201620 China

To improve the availability of data in the cloud and avoid vendor lock-in risk, multi-cloud storage is attracting more and more attentions. However, accessing data from the cloud usually has some disadvantages such as higher latency and more bandwidth-consuming. Edge computing, which has become popular in recent years, could effectively solve the above problems while it usually reduces availability. Storage only in the cloud or edge environment is limited by many factors. To this end, we build mathematical model which is abstracted from real access mode of users in consideration of multi-cloud and edge. This paper presents a method combined NSGAII with multi-group method which has better ability of global search to help users determine cloud and edge services to store and access data object. A large number of experiments using real service provider information demonstrate that the proposed algorithm outperforms existing methods and effectiveness of it. © 2020 IEEE.

关键词： Multiobjective optimization

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