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Trip route simulation for pre-Qin settlements based on a gradient descent and variable-neighborhood ant colony optimization algorithm in the Linfen Basin, China

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EARTH SCIENCE INFORMATICS 2021年第1期14卷 415-428页

作者： Liu, Fang Yu, Lijun Zhu, Jianfeng Nie, Yueping Sun, Yu Chinese Acad Sci Aerosp Informat Res Inst Beijing 100101 Peoples R China Beijing Jinghang Computat & Commun Res Inst Beijing 100074 Peoples R China Hainan Univ Sch Informat & Commun Engn Haikou 570228 Hainan Peoples R China

A travel or transport path reflects the settlement pattern and the spread of civilization. Travel simulations of the pre-Qin period of the Central Plains of China can deepen our understanding of the origin and development of Chinese civilization. Here, based on the idea of swarm intelligence, an ant colony optimization algorithm based on gradient descent and variable-neighborhood search (GD-VNSACO) methods is proposed to simulate the travel routes of ancestors. We simulate the process of humans gradually exploring the surrounding space and obtaining experience and inspiration in four cultural periods from 7 to 2.7 ka B.P. (including the Yangshao Period, Miaodigou II Period, Longshan Period and Xia Shang and Zhou Period). The GD-VNSACO algorithm is suitable for studying settlement travel because of its improved search ability and convergence speed based on local and overall optimization. We conclude that in the four periods, the high-density routes of transport were concentrated along the Fen River, forming a main line from north to south. Over time, high-density areas of transport and communication among settlements, as well as the transport scope, expanded. However, there was an abnormality in the Miaodigou II Period, which was mainly caused by the climate becoming dryer and colder.

关键词： Route simulation GD-VNSACO ACO Linfen Basin Variable-neighborhood research gradient descent algorithm

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Hybrid gradient descent spider monkey optimization (HGDSMO) algorithm for efficient resource scheduling for big data processing in heterogenous environment

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JOURNAL OF BIG DATA 2020年第1期7卷 1-25页

作者： Seethalakshmi, V. Govindasamy, V. Akila, V. Pondicherry Engn Coll Dept Comp Sci & Engn Pondicherry India Pondicherry Engn Coll Dept Informat Technol Pondicherry India

Big Data constructed based on the advancement of distributed computing and virtualization is considered as the current emerging trends in Data Analytics. It is used for supporting potential utilization of computing resources focusing on, on-demand services and resource scalability. In particular, resource scheduling is considered as the process of resource distribution through an effective decision making process with the objective of facilitating required tasks over time. The incorporation of heterogeneous computing resources by the Big Data consumers also permits the option of reducing energy usage and enhanced resource efficiency. Further, optimal scheduling of resources is considered as an NP hard problem due to the dynamic characteristics of the resources and fluctuating users' demand. In this paper, a Hybrid gradient descent Spider Monkey Optimization (HGDSMO) algorithm is proposed to efficient resource scheduling by handling the issues and challenges in the Hadoop heterogenous environment. The proposed HGDSMO algorithm uses the gradient descentand foraging and social behavior of the spider monkey optimization algorithm involved in the objective of effective resource allocation. It is designed as the efficient task scheduling approach that balances the load of the cloud by allocating them to appropriate VMs depending on their requirements. It is also proposed as a dynamic resource management scheme for efficiently allocating the cloud resources for effective execution of clients' tasks. The simulation results of the proposed HGDSMO algorithm confirmed to be potent in throughput, load balancing and makespan compared to the baseline hybrid meta-heuristic resource allocation algorithms used for investigation.

关键词： Heterogeneous Environment Optimal Resource Allocation gradient descent algorithm Spider Monkey Optimization (SMO) Load balancing

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A novel filtering-based recursive identification method for a fractional-order Hammerstein state space system with piecewise nonlinearity

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART I-JOURNAL OF SYSTEMS AND CONTROL ENGINEERING 2025年

作者： Lang, Hongjun Bi, Yiqun Li, Meihang Ji, Yan Qingdao Univ Sci & Technol Coll Automat & Elect Engn Songlin Rd 99 Qingdao 266061 Peoples R China

This paper investigates parameters and states estimation for a class of fractional-order state space systems with colored noises. To provide accurate parameter estimation, we suggest a novel gradient descent algorithm based on the extended Kalman filtering. The new approach features lower estimation error variances and a faster convergence rate than the conventional gradient descent algorithm. A data filtering is introduced to filter the input and output data, thereby reducing the impact of colored noises on the accuracy of the parameter estimates.

关键词： Piecewise linearity fractional-order system parameter estimation state filtering gradient descent algorithm

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Optimal Control of Nonlinear Competitive Epidemic Spreading Processes With Memory in Heterogeneous Networks

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IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING 2025年第1期12卷 96-109页

作者： You, Jin Li, Yan Cao, Xiangyang Zhao, Daduan Chen, Yangquan Zhang, Chenghui Shandong Univ Sch Control Sci & Engn Jinan 250061 Peoples R China Luoyang Inst Sci & Technol Sch Elect Engn & Automat Luoyang 471000 Peoples R China Univ Calif Merced Mechatron Embedded Syst & Automat Lab Merced CA 95343 USA

Modeling and control of epidemic-like spreading processes, such as contagions, rumors or products in complex networks, holds profound significance for understanding transmission mechanisms, formulating effective prevention and optimizing resource allocation. This paper investigates the optimal control problems for competing processes modeled by fractional-order bi-virus systems with memory in complex networks for the first time. The proposed model performs exceptionally well in capturing the dynamics of virus transmission and immune. First, the key indicators: bi-basic reproduction numbers (BBRNs) are introduced for the metapopulation model with nonlinear infectious functions in heterogenous networks. Then they are utilized to classify the equilibria, including extinction, absolute dominance and coexistence ones. Second, sufficient conditions for the stability of the equilibria are derived. Leveraging this result, an optimal therapeutic protocol is presented to eradicate viruses and minimize the cost function simultaneously. The corresponding optimal control solutions are generated via gradient descent algorithm, which can converge relatively quickly by iteratively adjusting control variables. Particularly, the role of fractional-order $\alpha$ in system modeling and optimization is deeply probed into. Finally, numerical examples are also included at the end of this paper to further shed light on the effectiveness of our results.

关键词： Optimal control Epidemics Process control Predictive models Mathematical models Infectious diseases Prevention and mitigation COVID-19 Heuristic algorithms Heterogeneous networks Complex network competing process gradient descent algorithm fractional-order system optimal control

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Chirality-Free Full Decoupling of Jones Matrix Phase-Channels with a Planar Minimalist Metasurface

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NANO LETTERS 2025年第4期25卷 1322-1328页

作者： Mu, Xinyang Qin, Haoye Zhao, Wannian Han, Sanyang Liu, Ziqi Shi, Yuzhi Huang, Wei Li, Bo Song, Qinghua Tsinghua Univ Tsinghua Shenzhen Int Grad Sch Shenzhen 518055 Peoples R China Chinese Acad Sci Suzhou Inst Nanotech & Nanob SINANO Key Lab Multifunct Nanomat & Smart Syst Suzhou 215123 Peoples R China Tongji Univ Inst Precis Opt Engn Sch Phys Sci & Engn Shanghai 200092 Peoples R China Suzhou Lab Suzhou 215000 Peoples R China

The complete manipulation of Jones matrix phase-channels using metasurfaces brings forth unparalleled possibilities across diverse wavefront modulation applications. Traditionally, achieving independent control over all four phase-channels usually involves the introduction of chirality with multilayer or three-dimensional metasurfaces. Here, we present a general chirality-free method that relies on polarization base transformation with a planar minimalist metasurface, effectively decoupling the four Jones matrix phase-channels, thereby unleashing the fundamental boundaries imposed by conventional linear or circular polarization bases. To achieve independent wavefront modulation across these four channels, we employ an inverse design methodology leveraging a gradient descent algorithm. Remarkably, our strategy enables four channel wavefront modulations with only three control degrees of freedom within the minimalist meta-structures. As a proof-of-concept, we experimentally project four far-field holographic images, each corresponding to one of the four phase-channels, holding promises for various applications such as augmented/virtual reality display, information encryption, optical communication and data storage.

关键词： Metasurface Meta-Hologram Polarization Multiplexing Chirality Free gradient descent algorithm Jones Matrix

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Dynamic gain-based neural network backstepping control with its applications to a quad-rotor hover

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TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL 2025年第4期47卷 677-687页

作者： Yang, Jiaxing Yang, Xuebo Zheng, Xiaolong Harbin Inst Technol Sch Astronaut Res Inst Intelligent Control & Syst Harbin 150001 Peoples R China

In this paper, a novel neural network (NN) backstepping control method is proposed for a class of uncertain nonlinear systems with unknown control direction functions. To solve the control problems caused by unknown control direction functions, a method called "virtual control coefficient" is presented using equivalence transformations. However, to improve the flexibility of the control method, a function named "dynamic gain" is introduced to design the feedback gains of the NN backstepping controllers. Moreover, instead of using sigma-modification, gradient descent algorithm is applied to train the weights of NNs such that the unknown nonlinearities of the system can be well approximated by NNs. With the help of Lyapunov stability criterion, it can be proved that the system tracking error is semi-global uniformly ultimately bounded. Finally, the effectiveness of the proposed control method is verified by the experimental results on a quad-rotor hover platform.

关键词： Neural network backstepping dynamic gain gradient descent algorithm unknown control direction functions quad-rotor hover

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Dual Jones Matrices Empowered Six Phase Channels Modulation with Single-Layer Monoatomic Metasurfaces

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LASER & PHOTONICS REVIEWS 2025年第7期19卷

作者： Liu, Ziqi Mu, Xinyang Song, Helun Yu, Yefeng Zhang, Ruirui Zou, Yonggang Geng, Zihan Wang, Mingdi Chen, Linghu Sun, Yunfei Tong, Xiaogang Song, Qinghua Huang, Wei Changchun Univ Sci & Technol Natl Key Lab High Power Semicond Lasers Changchun 130022 Jilin Peoples R China Chinese Acad Sci Suzhou Inst Nanotech & Nanobion Key Lab Multifunct Nanomat & Smart Syst Suzhou 215123 Jiangsu Peoples R China Chinese Acad Sci Suzhou Inst Nanotech & Nanobion Key Lab Semicond Display Mat & Chips Suzhou 215123 Jiangsu Peoples R China Tsinghua Univ Tsinghua Shenzhen Int Grad Sch Shenzhen 518055 Guangdong Peoples R China Nanjing Univ Sci & Technol Sch Microelect Nanjing 210094 Jiangsu Peoples R China Soochow Univ Sch Mech & Elect Engn Suzhou 215021 Jiangsu Peoples R China Suzhou Yihua Biomed Technol Co Ltd Suzhou 215000 Jiangsu Peoples R China Suzhou Univ Sci & Technol Sch Elect & Informat Engn Suzhou 215009 Jiangsu Peoples R China Taiyuan Inst Technol Dept Elect Engn Taiyuan 030008 Shanxi Peoples R China

A comprehensive manipulation of the Jones matrix phase channels is crucial for enhancing the information capacity and security of the metasurface. However, a single-layer planar metasurface, without the incorporation of chirality, can only achieve a maximum of three independent phase channels for single Jones matrix under either linear or circular polarization bases. Here, an effective strategy is proposed that utilizes dual Jones matrices in different polarization bases with a single-layer monoatomic metasurface, thus extending the number of independent phase channels to six. To encode six holographic images into these six phase channels, a three-step gradient descent algorithm is introduced. As a proof of principle, a metasurface consisting of arrays of monoatomic dielectric structure is designed and fabricated in each unit cell, which exhibits six independent holographic images in the far field. The demonstrated metasurface platform is expected to open up new possibilities for the development of optical devices for applications in high-capacity information storage, high-security encrypted communication, and high-solution optical displays.

关键词： dual Jones matrices gradient descent algorithm holography metasurface six phase channels modulation

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Distributed optimization algorithm for multi-agent networks with lazy gradient information

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ASIAN JOURNAL OF CONTROL 2025年第1期27卷 532-539页

作者： Mo, Lipo Yang, Yang Huang, Xiankai Beijing Technol & Business Univ Sch Math & Stat Beijing 100048 Peoples R China Beijing Technol & Business Univ Sch Comp & Artificial Intelligence Beijing Peoples R China

Based on the so-called lazy gradient information, this note proposes two communication-reduced distributed optimization algorithms over undirected multi-agent networks. The lazy gradients refer to some gradients that do not change much in the past iterations and thus may not be distributed among agents which correspondingly reduces the communication load in the networks. For both the deterministic and the stochastic frameworks, the asymptotic properties of the distributed optimization algorithms are established. Compared with the existing literature using the lazy gradient information, the proposed algorithms in the paper are fully distributed and more suitable for the situation of decentralized multi-agent networks. The effectiveness of the proposed algorithms is also testified through numerical simulations.

关键词： communication reduction distributed optimization gradient descent algorithm lazy gradient

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A fast LMS-based digital background calibration technique for 16-bit SAR ADC with modified shuffling scheme

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MICROELECTRONICS JOURNAL 2025年 156卷

作者： Wang, Jiacong Du, Biyun Su, Zhangjie Hu, Ke Yu, Jia Cao, Chao Liu, Shubin Guo, Haijun Shandong Univ Sch Integrated Circuits Jinan 250101 Peoples R China Shandong Univ Sch Software Jinan 250101 Peoples R China Xidian Univ Sch Microelect Xian 710071 Peoples R China Univ Jinan Sch Informat Sci & Engn Jinan 250022 Peoples R China

- This paper introduces a modified shuffling scheme to achieve less overhead in ADC, lower power consumption for digital calibration and higher update frequency. Different-size unit capacitors are used in the shuffling, which reduces the number of switches and capacitors by almost half while remaining complexity of the digital circuit unchanged. Additionally, a novel LMS-based digital background calibration technique suitable for split-based ADC is proposed. Fast convergence and linear calibration are achieved with the improved gradient descent algorithm, which uses Momentum and Nesterov accelerated gradient (NAG). The convergence speed is found to be over 10 times faster than typical LMS algorithm and maintain calibration accuracy in MATLAB simulation of a 16-bit, 1 MS/s SAR ADC.

关键词： Split-capacitor SAR ADC Modified shuffling Fast convergency LMS-Based calibration gradient descent algorithm

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Research on three-dimensional attack area based on improved backtracking and ALPS-GP algorithms of air-to-air missile

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Journal of Systems Engineering and Electronics 2025年第1期36卷 292-310页

作者： ZHANG Haodi WANG Yuhui HE Jiale College of Automation Engineering Nanjing University of Aeronautics&AstronauticsNanjing 210016China National Key Laboratory of Air-based Information Perception and Fusion AVICLuoyang 471000China

In the field of calculating the attack area of air-to-air missiles in modern air combat scenarios,the limitations of existing research,including real-time calculation,accuracy efficiency trade-off,and the absence of the three-dimensional attack area model,restrict their practical *** address these issues,an improved backtracking algorithm is proposed to improve calculation efficiency.A significant reduction in solution time and maintenance of accuracy in the three-dimensional attack area are achieved by using the proposed ***,the age-layered population structure genetic programming(ALPS-GP)algorithm is introduced to determine an analytical polynomial model of the three-dimensional attack area,considering real-time *** accuracy of the polynomial model is enhanced through the coefficient correction using an improved gradient descent *** study reveals a remarkable combination of high accuracy and efficient real-time computation,with a mean error of 91.89 m using the analytical polynomial model of the three-dimensional attack area solved in just 10^(-4)s,thus meeting the requirements of real-time combat scenarios.

关键词： air combat three-dimensional attack area improved backtracking algorithm age-layered population structure genetic programming(ALPS-GP) gradient descent algorithm

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