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Improved beluga whale optimization algorithm based cluster routing in wireless sensor networks

Mathematical Biosciences and Engineering 2024年第3期21卷 4587-4625页

作者： Yuan, Hao Chen, Qiang Li, Hongbing Zeng, Die Wu, Tianwen Wang, Yuning Zhang, Wei Chongqing Key Laboratory of Geological Environmental Monitoring and Disaster Early Warning in the Three Gorges Reservoir Area Chongqing Three Gorges University Chongqing404120 China Internet of Things and Intelligent Control Technology Chongqing Engineering Research Center Chongqing Three Gorges University Chongqing404120 China Chongqing Municipal Key Laboratory of Intelligent Information Processing and Control Chongqing Three Gorges University Chongqing404120 China

Cluster routing is a critical routing approach in wireless sensor networks (WSNs). However, the uneven distribution of selected cluster head nodes and impractical data transmission paths can result in uneven depletion of network energy. For this purpose, we introduce a new routing strategy for clustered wireless sensor networks that utilizes an improved beluga whale optimization algorithm, called tCBWO-DPR. In the selection process of cluster heads, we introduce a new excitation function to evaluate and select more suitable candidate cluster heads by establishing the correlation between the energy of node and the positional relationship of nodes. In addition, the beluga whale optimization (BWO) algorithm has been improved by incorporating the cosine factor and t-distribution to enhance its local and global search capabilities, as well as to improve its convergence speed and ability. For the data transmission path, we use Prim’s algorithm to construct a spanning tree and introduce DPR for determining the optimal route between cluster heads based on the correlation distances of cluster heads. This effectively shortens the data transmission path and enhances network stability. Simulation results show that the improved beluga whale optimization based algorithm can effectively improve the survival cycle and reduce the average energy consumption of the network. © 2024 the Author(s).

关键词： Heuristic algorithms

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Extended State Observer-based Hybrid Dynamic Event-Triggered Consensus control with External Disturbances 24

Extended State Observer-based Hybrid Dynamic Event-Triggered...

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2nd International Conference on Frontiers of Intelligent Manufacturing and Automation, CFIMA 2024

作者： Pei, Wenliang Hua, Changchun Cui, Hailong Zhao, Guanglei Ma, Zhuang The Institute of Electrical Engineering The Key Lab of Intelligent Rehabilitation and Neuroregulation in Hebei Province Key Laboratory of Intelligent Control and Neural Information Processing Ministry of Education Yanshan University Hebei China Tangshan University Hebei China

ISBN: (纸本)9798400710681

This paper solves the event-triggered robust consensus problem of disturbed multi-agent systems (MASs) in fully distributed fashion. First, a distributed extended state observer (DESO) is developed for appropriately estimating system states and external disturbances. Then, by utilising these estimates, a fully distributed event-triggering control protocol, that composes of an adaptive distributed controller to avoid using global information while maintaining desired consensus property, and a novel hybrid dynamic event-triggering mechanism (ETM) to save communication resources, is put forward for the MASs. It is notable that an auxiliary differential equation is incorporated in the triggering condition, with which, positive minimum interevent times (MIETs) are available to ease the hardware implementation, while being with adaptive coefficients, the proposed hybrid dynamic ETM can be independent of any global information. Finally, the obtained main results are testified via a numerical example. © 2024 Copyright held by the owner/author(s).

关键词： State estimation

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Residual Tensor Train: A Quantum-Inspired Approach for Learning Multiple Multilinear Correlations

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2023年第5期4卷 1101-1113页

作者： Chen, Yiwei Pan, Yu Dong, Daoyi Zhejiang University Institute of Cyber-Systems and Control College of Control Science and Engineering Hangzhou310027 China Zhejiang University State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control College of Control Science and Engineering Hangzhou310027 China University of New South Wales School of Engineering and Information Technology CanberraACT2600 Australia

States of quantum many-body systems are defined in a high-dimensional Hilbert space, where rich and complex interactions among subsystems can be modeled. In machine learning, complex multiple multilinear correlations may also exist within input features. In this article, we present a quantum-inspired multilinear model, named residual tensor train (ResTT), to capture the multiple multilinear correlations of features, from low to high orders, within a single model. ResTT is able to build a robust decision boundary in a high-dimensional space for solving fitting and classification tasks. In particular, we prove that the fully connected layer and the Volterra series can be taken as special cases of ResTT. Furthermore, we derive the rule for weight initialization that stabilizes the training of ResTT based on a mean-field analysis. We prove that such a rule is much more relaxed than that of tensor train (TT), which means that ResTT can easily address the vanishing and exploding gradient problem that exists in the existing TT models. Numerical experiments demonstrate that ResTT outperforms the state-of-the-art tensor network and benchmark deep learning models on MNIST and Fashion-MNIST datasets. Moreover, ResTT achieves better performance than other statistical methods on two practical examples with limited data, which are known to have complex feature interactions. © 2020 IEEE.

关键词： Neural networks

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Multi-source information fusion:Progress and future

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Chinese Journal of Aeronautics 2024年第7期37卷 24-58页

作者： Xinde LI Fir DUNKIN Jean DEZERT School of Automation Southeast UniversityNanjing 210008China Nanjing Center for Applied Mathematics Nanjing 211135China Key Laboratory of Measurement and Control of CSE Ministry of EducationNanjing 210096China Southeast University Shenzhen Research Institute Shenzhen 518063China Information Modeling and Processing Department ONERAPalaiseau 92320France

Multi-Source information Fusion(MSIF),as a comprehensive interdisciplinary field based on modern information technology,has gained significant research value and extensive application prospects in various domains,attracting high attention and interest from scholars,engineering experts,and practitioners *** achieving fruitful results in both theoretical and applied aspects over the past five decades,there remains a lack of comprehensive and systematic review articles that provide an overview of recent development in *** light of this,this paper aims to assist researchers and individuals interested in gaining a quick understanding of the relevant theoretical techniques and development trends in MSIF,which conducts a statistical analysis of academic reports and related application achievements in the field of MSIF over the past two decades,and provides a brief overview of the relevant theories,methodologies,and application domains,as well as key issues and challenges currently ***,an analysis and outlook on the future development directions of MSIF are presented.

关键词： Multi-sensor system information fusion Artificial intelligence Pattern recognition Human-machine integration

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Periodicity in dynamical games driven by the Hedge algorithm and myopic best response 63

Periodicity in dynamical games driven by the Hedge algorithm...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Guo, Xinxiang Mu, Yifen Yang, Xiaoguang University of Chinese Academy of Sciences The Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and Systems Science Chinese Academy of Sciences School of Mathematical Sciences Beijing100190 China Institute of Systems Science Academy of Mathematics and Systems Science Chinese Academy of Sciences The Key Laboratory of Systems and Control Beijing100190 China Institute of Systems Science Academy of Mathematics and Systems Science Chinese Academy of Sciences The Key Laboratory of Management Decision and Information System Beijing100190 China

ISBN: (纸本)9798350316339

In this paper, we consider the n × n two-payer zero-sum repeated game in which one player (player X) employs the popular Hedge (also called multiplicative weights update) learning algorithm while the other player (player Y) adopts the myopic best response. The theoretical analysis on the dynamics of such game system is still rare, which is however of promising interests. We investigate the dynamics of such Hedge-myopic system by defining a metric Q(xt), which measures the distance between the stage strategy xt and Nash Equilibrium (NE) strategy of player X. We analyze the trend of Q(xt) and prove that it is bounded and can only take finite values on the evolutionary path when payoffs are all rational numbers and the game has an interior NE. Based on this, we prove that the stage strategy sequence of both players are periodic after finite stages and the time-averaged strategy of player Y within one period is an exact NE strategy. © 2024 IEEE.

关键词： Consensus algorithm

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Dual-view Label and Feature Supervision Network for Semi-supervised Medical Image Segmentation 24

Dual-view Label and Feature Supervision Network for Semi-sup...

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7th International Conference on Signal processing and Machine Learning, SPML 2024

作者： Zhou, Zhen Li, Zuoyong Wang, Zhengyuan Teng, Shenghua Wang, Tao College of Electronic and Information Engineering Shandong University of Science and Technology Qingdao China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control School of Computer and Big Data Minjiang University Fuzhou China

ISBN: (纸本)9798400717192

Semi-supervised learning has garnered significant attention, particularly in medical image segmentation, owing to its capacity to leverage a large number of unlabeled data and a limited amount of labeled data to improve performance. However, most existing semi-supervised segmentation methods exhibit shortcomings in supervising unlabeled data, both in the label space due to potential noise in pseudo-labels, and the feature space due to indistinct class boundaries. To address the issues above, we propose Dual-view Label and Feature Supervision Network, termed DLFS-Net, to enhance label and feature supervision for unlabeled data. Our approach is based on a dual-view learning strategy that incorporates two modules: the Confidence Fusion Supervision Module (CFS) and the Dual-view Prototype Learning Module (DPL). Specifically, the CFS module generates weight matrices to integrate complementary information from two model outputs, producing more accurate pseudo-labels in the label space. The DPL module reduces intra-class variations in the feature space from two different views through prototype learning to generate clear class boundaries. Experiments on the LA and Pancreas-CT datasets demonstrate that our framework show solid gains (e.g.,1.76% Dice and 2.37% Jaccard improvement on Pancreas-CT dataset with 20% labeled data) compared with the state-of-the-art methods. © 2024 ACM.

关键词： Self-supervised learning

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Quasi Markov Simplex Optimization of Nonlinear Functional Parameters in Multivariable Collaborative Cascade control 41

Quasi Markov Simplex Optimization of Nonlinear Functional Pa...

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第41届中国控制会议

作者： Tangwen Yin Department of Automation Shanghai Jiao Tong UniversityKey Laboratory of System Control and Information ProcessingMinistry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Exposition to risk for the benefit of automatic control creates *** and robustness are two options to reduce the inherent fragility risk of safety-critical ***,time and resource parameters that characterize the agile responsiveness and robust adaptivity are difficult to be optimized due to multilevel coupling structures with different time *** propose the quasi Markov simplex optimization(QMSO) of nonlinear functional parameters in multivariable collaborative cascade control(MCCC) to improve agility and robustness for systems with hierarchical multivariable coordination and multiple *** verify if the singularly perturbed feedback and control with quasi Markovian jumps through optimal nonlinear functional parameters can achieve the multivariable collaborative cascade control equivalent to that of singular perturbation modeling and design without decomposing slow and fast *** in aviation show that the nonlinear functional parameters in MCCC can be estimated through QMSO to improve agility and robustness for the consistence of flight *** find that the simplex optimization equivalently establishes the nonlinear singularly perturbed feedback and control with quasi Markovian jumps,without having to realize singular perturbation modeling and design,and there is no need to decompose slow and fast *** conclusion,the quasi Markov simplex estimation of nonlinear functional parameters optimizes the hierarchical multivariable coordination under multiple timescales,so that the synthesized collaborative cascade control is capable to improve agility and robustness.

关键词： Agility Hierarchical Multivariable Coordination Multiple Timescales Nonlinear Aircraft control Robustness

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A video archive management method based on blockchain technology 11

A video archive management method based on blockchain techno...

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Optoelectronic Imaging and Multimedia Technology XI 2024

作者： Wu, Rongteng College of Computer and Big Data Minjiang University Fuzhou350108 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou350108 China

ISBN: (纸本)9781510682061

Video archives play a crucial role in various industries, from media and entertainment to security and surveillance. Managing these archives efficiently and securely is a growing challenge due to the increasing volume of video data being generated. In this paper, a video archive management method is presented to solve security and sensibility of the video files on blockchain. By encrypting video files and generating cryptographic hashes, the presented method can protect the integrity of the data and prevent unauthorized modifications. The method based on blockchain technology offers a compelling solution to the challenges faced in managing video archives. By combining the inherent security and transparency of blockchain with innovative data management algorithms, organizations can ensure the integrity, security, and accessibility of their video archives. © 2024 SPIE.

关键词： Data integrity

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An Enhanced Pythagorean Fuzzy Distance Method with Application in the Selection of Renewable Energy Source via MCDA

An Enhanced Pythagorean Fuzzy Distance Method with Applicati...

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2024 International Conference on New Trends in Computational Intelligence, NTCI 2024

作者： Terna, Anum Manasseh Ejegwa, Paul Augustine Feng, Yuming Joseph Sarwuan Tarka University Department of Mathematics Makurdi Nigeria Chongqing Three Gorges University Key Laboratory of Intelligent Information Processing and Control Chongqing Wanzhou404100 China

ISBN: (纸本)9798331517021

Many complex decision-making processes have been prosecuted with the aid of Pythagorean fuzzy distance methods. This is because the theory of Pythagorean fuzzy sets has the ability to handle the vagueness and imprecision in decision-making. Various Pythagorean fuzzy distance methods have been constructed and applied to multiple criteria decision-making. Recently, Thakur et al. developed a Pythagorean fuzzy distance method based on Euler's number by considering an incomplete number of the parameters of Pythagorean fuzzy sets. This exclusion could render the result of the distance method unreliable in real-life applications. In this work, we augment the Thakur et al:'s Pythagorean fuzzy distance method by the inclusion of the complete parameters of Pythagorean fuzzy sets for an effective interpretation. The properties of the enhanced Pythagorean fuzzy distance method are described and the method satisfies the conditions of distance function. In addition, the new method is used to discuss the selection of renewable energy source based on multiple criteria decision-making approach. Furthermore, the enhanced method is compared with other existing Pythagorean fuzzy distance methods via multiple criteria decision-making approach to show the superiority of the augmented method. © 2024 IEEE.

关键词： multi-criteria decision analysis multiple criteria decision-making Pythagorean fuzzy distance method Pythagorean fuzzy set renewable energy source

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Silicon Content control for Blast Furnace: Model-free DDQN-ICM Method

Silicon Content Control for Blast Furnace: Model-free DDQN-I...

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2023 China Automation Congress, CAC 2023

作者： Zhang, Baocong Ding, Xuda Liu, Wei Chen, Cailian Guan, Xinping Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Department of Automation Shanghai200240 China

ISBN: (纸本)9798350303759

Silicon content control is critical to ensure the quality of molten iron and the stable operation of the blast furnace. The complex reactions and large uncertainty of the blast furnace make it hard to control. Several predictive control-based methods were already studied in Silicon content control. However, the requirements of prediction model design and short predictive horizon limit the generalization and long-term optimization of the methods. To tackle these issues, we propose a deep double Q-learning (DDQN) and intrinsic curiosity module (ICM) based Silicon content control method. First, the deep Q-learning framework employed in our approach eliminates the need for a prediction model and supports long-range simulations, thereby enhancing algorithm generalization and long-term optimization capabilities. Second, DDQN and ICM help to avoid the over-optimistic of action taking and improve exploration efficiency to tackle the large uncertainty of the blast furnace. Third, to ensure operational safety, we have designed a regulation strategy that incorporates ϵ-greedy exploration and ICM, mitigating the risks posed by exploration actions. Finally, we validate the effectiveness of our method using on-site data, demonstrating that DDQN-ICM achieves superior performance in terms of tracking accuracy and disturbance rejection. © 2023 IEEE.

关键词： Blast furnaces

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