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Research on evolutionary multi-objective optimization algorithms

Ruan Jian Xue Bao/Journal of Software 2009年第2期20卷 271-289页

作者： Gong, Mao-Guo Jiao, Li-Cheng Yang, Dong-Dong Ma, Wen-Ping Institute of Intelligent Information Processing Xidian University Xi'an 710071 China Key Laboratory of Intelligent Perception and Image Understanding Xidian University Xi'an 710071 China

Evolutionary multi-objective optimization (EMO), whose main task is to deal with multi-objective optimization problems by evolutionary computation, has become a hot topic in evolutionary computation community. After summarizing the EMO algorithms before 2003 briefly, the recent advances in EMO are discussed in details. The current research directions are concluded. On the one hand, more new evolutionary paradigms have been introduced into EMO community, such as particle swarm optimization, artificial immune systems, and estimation distribution algorithms. On the other hand, in order to deal with many-objective optimization problems, many new dominance schemes different from traditional Pareto-dominance come forth. Furthermore, the essential characteristics of multi-objective optimization problems are deeply investigated. This paper also gives experimental comparison of several representative algorithms. Finally, several viewpoints for the future research of EMO are proposed. © by Institute of Software, the Chinese Academy of Sciences. All rights reserved.

关键词： Multiobjective optimization

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An Expansion-based Document Ranking Framework Incorporated with Core Concern Capturing 5

An Expansion-based Document Ranking Framework Incorporated w...

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5th International Conference on intelligent Autonomous Systems, ICoIAS 2022

作者： Qi, Yinqiao Xin, Jinghao Li, Ning Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Department of Automation Shanghai China

ISBN: (数字)9781665498388

ISBN: (纸本)9781665498388

Entity-based ranking is a popular research area in document ranking as knowledge graphs can introduce additional evidence for ranking systems. In most entity-based ranking framework, the original query is transformed into a set of entities and candidate documents are ranked according to their relevance to the entity set. However, mistakes can easily occur during the transformation process, which introduce noise to the ranking system. This paper represents an expansion-based ranking framework, which expand the original query with high-quality candidate entities to mitigate the impact of transformation mistakes and enrich the semantics of the query in the meanwhile. Compared with existing query expansion methods, our expansion method is lightweight as it reduces much computational burden and requests little extra information. However, the core concerns of the users might be covered up after query expansion. To alleviate this dilemma, a core concern capturing method is pro-posed, wherein the attention weight of each inter-entity relation is measured to capture the core entity pairs in the expanded query. Experiments on the S2-CS dataset demonstrate the effectiveness of our lightweight query expansion method and the superiority of our core concern capturing method. Compared with a classical retrieval model, our method provides 11% improvements in terms of NDCG@15. © 2022 IEEE.

关键词： Semantics

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Integrated Power and Hydrogen Trading in Multimicrogrid Coupled with Offsite Hydrogen Refueling Stations 6

Integrated Power and Hydrogen Trading in Multimicrogrid Coup...

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6th IEEE Conference on Energy Internet and Energy System Integration, EI2 2022

作者： Li, Longyan Ning, Chao Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China

ISBN: (纸本)9798350347159

This paper proposes a novel two-level electricity and hydrogen market framework for multi-microgrids (MMGs) coupled with offsite hydrogen refueling stations (HRSs), aiming to strengthen the synergy between electricity and hydrogen. The local hydrogen market among the MMG and HRSs is modeled by multi-leader multi-follower Stackelberg game theory, in which microgrids play the role of leaders to adjust hydrogen prices while HRSs participate as followers to determine their hydrogen purchase scheme. Moreover, to deal with economic and technical issues of the MMG in a holistic manner, Nash bargaining theory is used to model the electricity transaction among microgrids. A distributed algorithm is developed to solve such games, thus reducing the cost of information communication and the risk of privacy exposure. The case study demonstrates that this market mechanism guarantees benefits for all parties and boosts the independence of MMGs by reducing transactions with the main grid. © 2022 IEEE.

关键词： Game theory

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A fast VLSI architecture for two-dimensional discrete wavelet transform based on lifting scheme

A fast VLSI architecture for two-dimensional discrete wavele...

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2004 7th International Conference on Solid-State and Integrated Circuits Technology Proceedings, ICSICT 2004

作者： Xiong, Chengyi Tian, Jinwen Liu, Jian Institute of Pattern Recognition and Artificial Intelligence Key Laboratory of Eduaction Ministry for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China College of Electronic Information Engineering South-Center University for Nationalities Wuhan 430074 China

This paper proposes a novel fast architecture for two-dimensional discrete wavelet transform by using lifting scheme. The parallel and embedded decimation techniques are employed to optimize the architecture, which is mainly composed of two horizontal filter modules and one vertical filter module, working in parallel and pipeline fashion with 100% hardware utilization. The architecture is designed to generate two outputs at one working clock cycle, with every two subbands coefficients alternately. The total time of computing J levels of decomposition for N×N image is approximately 2N2(I-4 J)/3 clock cycles. In comparison with the other devices reported in previous literature, the design has many advantages including lower hardware complexity and area and power efficient. The design is also fast, regular and simple, as well as well suited for VLSI implementation. © 2004 IEEE.

关键词： VLSI circuits

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A Parallel Read-Write Circuit Design for Driving Memristor Crossbar Array

A Parallel Read-Write Circuit Design for Driving Memristor C...

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2023 International Conference on Neuromorphic Computing, ICNC 2023

作者： Jiang, Ningye Jiang, Mingxuan Zeng, Zhigang Huazhong University of Science and Technology School of Artificial Intelligence and Automation Wuhan430074 China Huazhong University of Science and Technology School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan430074 China

ISBN: (纸本)9798350316889

Memristor crossbar array is considered as a promising circuit module for accelerating neural networks. Because the memristor is tunable and multi-state, it is important to design applicable Read-Write (RW) circuit for driving memristor crossbar array. In this paper, a novel RW circuit based on analog circuits is proposed for tuning memristors in high-dimensional array parallelly, which is scalable and low-overhead. The standalone RW circuit schematic is presented for reading/writing single memristor and verified in circuit simulation. Then, we extend and apply this circuit into a two-dimensional memristor crossbar array. The performance of memristor crossbar array controlled by designed RW circuits is verified via the simulations under various machine learning datasets. The comparison with related works is presented, which demonstrates the advantages of the proposed RW circuit regarding overhead and anti-error. © 2023 IEEE.

关键词： Memristors

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Automatic segmentation of brain structures using geometric moment invariants and artificial neural networks

Automatic segmentation of brain structures using geometric m...

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21st International Conference on Information processing in Medical Imaging, IPMI 2009

作者： Jabarouti Moghaddam, Mostafa Soltanian-Zadeh, Hamid Control and Intelligent Processing Center of Excellence Department of Electrical and Computer Engineering University of Tehran Tehran Iran Image Analysis Laboratory Department of Radiology Henry Ford Hospital Detroit MI United States

ISBN: (纸本)3642024971

We propose an automatic method for the segmentation of the brain structures in three dimensional (3D) Magnetic Resonance images (MRI). The proposed method consists of two stages. In the first stage, we represent the shape of the structure using Geometric Moment Invariants (GMIs) in 8 scales. For each scale, an Artificial Neural Network (ANN) is designed to approximate the signed distance function of a desired structure. The GMIs along with the voxel intensities and coordinates are used as the input features of the ANN and the signed distance function as its output. In the second stage, we combine the outputs of the ANNs of the first stage and design another ANN to classify the image voxels into two classes, inside or outside of the structure. We introduce a fast method for moment calculations. The proposed method is applied to the segmentation of caudate, putamen, and thalamus in MRI where it has outperformed other methods in the literature. © 2009 Springer Berlin Heidelberg.

关键词： Neural networks

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Finite-Time Fuzzy Sliding Mode control for Nonlinear Descriptor Systems

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IEEE/CAA Journal of Automatica Sinica 2021年第6期8卷 1141-1152页

作者： Zhixiong Zhong Xingyi Wang Hak-Keung Lam Key Laboratory of Information Processing and Intelligent Control Minjiang UniversityFuzhou 350121China College of Mechanical and Electronic Engineering Fujian Agriculture and Forestry UniversityFuzhou 350108China Department of Engineering King’s College LondonLondonWC2R 2LSUnited Kingdom

This article addresses the finite-time boundedness(FTB)problem for nonlinear descriptor ***,the nonlinear descriptor system is represented by the Takagi-Sugeno(T-S)model,where fuzzy representation is assumed to be appearing not only in both the state and input matrices but also in the derivative *** using a descriptor redundancy approach,the fuzzy representation in the derivative matrix is reformulated into a linear ***,we introduce a fuzzy sliding mode control(FSMC)law,which ensures the finite-time boundedness(FTB)of closed-loop fuzzy control systems over the reaching phase and sliding motion ***,by further employing the descriptor redundancy representation,the sufficient condition for designing FSMC law,which ensures the FTB of the closed-loop control systems over the entire finite-time interval,is derived in terms of linear matrix inequalities(LMIs).Finally,a simulation study with control of a photovoltaic(PV)nonlinear system is given to show the effectiveness of the proposed method.

关键词： Finite-time boundedness(FTB) fuzzy sliding mode control(FSMC) Takagi-Sugeno(T-S)fuzzy descriptor system

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Tuning Geometric Conformations of Curved DNA Structures by controlling Positions of Nicks 1

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17th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2022

作者： Xie, Chun Hu, Yingxin Chen, Kuiting Chen, Zhekun Pan, Linqiang Key Laboratory of Image Information Processing and Intelligent Control of Education Ministry of China School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China College of Information Science and Technology Shijiazhuang Tiedao University Shijiazhuang050043 China

ISBN: (数字)9789819915491

ISBN: (纸本)9789819915484

DNA origami is one of the powerful techniques that utilize DNA as building blocks to synthesize nanostructures. Traditionally, through introducing different numbers of insertions and deletions of base pairs in DNA helices, the in-plane bending angle of curved DNA structures could be roughly tuned. Here, we explored a strategy that used the position patterns of nicks in staple strands to tune the geometric conformation of curved DNA origami structures, including in-plane bending, out-of-plane bending, and twisting angles. When the structure adopted different patterns of nicks positions, great difference appeared in the geometric properties. Further, by combining subunits of different nicks position patterns, the bending and twisting of the combined structure was effectively tuned. The strategy increases the design accuracy of curved DNA origami structures and expands the toolbox for designing DNA structures. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Molecular dynamics

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A Class of Distributed Variable Structure Multiple Model Algorithm Based on Posterior Information of Information Matrix

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Journal of Shanghai Jiaotong university(Science) 2022年第5期27卷 671-679页

作者： HUANG Yinghao WU Yi YAO Lixiu CAI Yunze Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Jiao Tong UniversityShanghai200240China Department of Automation Key Laboratory of System Control and Information Processing of Ministry of EducationShanghai Jiao Tong UniversityShanghai200240China Alibaba(China)Co. Ltd.Hangzhou311121China

The tracking of maneuvering targets in radar networking scenarios is studied in this *** the interacting multiple model algorithm and the expected-mode augmentation algorithm,the fixed base model set leads to a mismatch between the model set and the target motion mode,which causes the reduction on tracking *** adaptive grid-expected-mode augmentation variable structure multiple model algorithm is *** adaptive grid algorithm based on the turning model is extended to the two-dimensional pattern space to realize the self-adaptation of the model ***,combining with the unscented information filtering,and by interacting the measurement information of neighboring radars and iterating information matrix with consistency strategy,a distributed target tracking algorithm based on the posterior information of the information matrix is *** the problem of filtering divergence while target is leaving radar surveillance area,a k-coverage algorithm based on particle swarm optimization is applied to plan the radar motion trajectory for achieving filtering convergence.

关键词： radar network system variable structure multiple model consistency filtering information matrix particle swarm optimization

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Prediction of chilling damage risk in maize growth period based on probabilistic neural network approach

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International Journal of Agricultural and Biological Engineering 2021年第2期14卷 120-125页

作者： Chunqiao Mi Changhua Zhao Qingyou Deng Xiaowu Deng School of Computer Science and Engineering Huaihua UniversityHuaihua 418000HunanChina Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture Huaihua 418000HunanChina Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application in Hunan Province Universities Huaihua 418000HunanChina Human Resource Department Huaihua UniversityHuaihua 418000HunanChina

Low temperature chilling damage is one of the most serious disasters in maize production,which is a typical non-linear complex issue with numerous influencing factors and strong *** to predict it is not only a hot theoretical research topic,but also an urgent practical problem to be ***,most of the current researches are focusing on post-disaster static descriptive assessment rather than pre-disaster dynamic predictive analysis,resulting in the problems such as no indicative result and low *** this study,the satisfaction rate of environmental accumulated temperature for maize production was used to measure the chilling damage risk,and a model for maize chilling damage risk prediction based on probabilistic neural network was *** model was composed of input layer,pattern layer,summation layer and output *** obtained results showed that the prediction accuracy for the most serious risk level was as high as 0.91,and the rates of the Type I Error and Type II Error made by the model were 0.1 and 0.09,*** indicated that the model employed was promising with good *** results of this research are of both theoretical significance for providing a new reference method of pre-disaster prediction to study maize chilling disaster risk and practical significance for reducing maize production risk and ensuring yield safety.

关键词： maize chilling damage risk prediction probabilistic neural network

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