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Sampling using adaptive regenerative processes

BERNOULLI 2025年第1期31卷 509-536页

作者： Mckimm, Hector Wang, Andi Pollock, Murray Robert, Christian Roberts, Gareth Imperial Coll London Dept Math London England Univ Warwick Dept Stat Coventry England Newcastle Univ Sch Math Newcastle Upon Tyne England Paris Dauphine Univ CEREMADE Paris France

Enriching Brownian motion with regenerations from a fixed regeneration distribution mu at a particular regeneration rate kappa results in a Markov process that has a target distribution pi as its invariant distribution. For the purpose of Monte Carlo inference, implementing such a scheme requires firstly selection of regeneration distribution mu, and secondly computation of a specific constant C. Both of these tasks can be very difficult in practice for good performance. We introduce a method for adapting the regeneration distribution, by adding point masses to it. This allows the process to be simulated with as few regenerations as possible and obviates the need to find said constant C. Moreover, the choice of fixed mu is replaced with the choice of the initial regeneration distribution, which is considerably less difficult. We establish convergence of this resulting self-reinforcing process and explore its effectiveness at sampling from a number of target distributions. The examples show that adapting the regeneration distribution guards against poor choices of fixed regeneration distribution and can reduce the error of Monte Carlo estimates of expectations of interest, especially when pi is skewed.

关键词： adaptive algorithm Markov process MCMC normalizing constant regeneration distribution Restore sampler sampling simulation

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Modified fractional least mean square-based control scheme for dynamic voltage restorer to improve power quality

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ELECTRICAL ENGINEERING 2024年第4期106卷 5069-5087页

作者： Deshpande, Chinmay V. Chilipi, Rajasekharareddy Arya, Sabha Raj SVNIT DoEE Ichchhanath Surat 395007 Gujarat India

The paper introduces a modified fractional least mean square (M-FLMS) filter-based control scheme designed for optimal control of dynamic voltage restorers. This scheme accurately estimates fundamental components from the supply voltage and performs exceptionally well, even under grid voltage anomalies. In this study, the original fractional least mean square (FLMS) control structure undergoes modifications incorporating an adjustable gain parameter, significantly enhancing its performance during voltage distortions. The resultant M-FLMS control scheme achieves swift convergence, reduced steady-state errors, and improved computational efficiency. Comparative analysis between the least mean square and FLMS control algorithms validates the superiority of the proposed M-FLMS approach, demonstrating faster settling times and decreased peak overshoot. Additionally, the grasshopper optimization algorithm is employed to efficiently tune load voltage and DC-link voltage proportional-integral controller gains, further augmenting the control scheme's effectiveness. The paper evaluates the suggested control scheme's effectiveness in both steady-state and dynamic behaviors through MATLAB-based simulations, offering a comprehensive assessment of its capabilities.

关键词： adaptive algorithm Fractional least mean square Grasshopper optimization algorithm Modified-fractional least mean square Power quality improvement Riemann-Liouville derivative Voltage unbalance

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The sensitivity of the adaptive algorithm with a posteriori error control to marking criteria

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St. Petersburg Polytechnical University Journal: Physics and Mathematics 2015年第4期1卷 436-443页

作者： Maria A. Churilova Peter the Great St. Petersburg Polytechnic University 29 Politekhnicheskaya St. St. Petersburg 195251 Russian Federation

The aim of this work is to compare different marking strategies, their influence on the work of adaptive algorithms with a posteriori error control for plane elasticity problems. The error control was performed using a functional error majorant. The implemented adaptive algorithms were based on the functional error majorant with no symmetry limitation on the free tensor, computed using the zero-order Raviart–Thomas approximations on triangular meshes. The four most commonly used element-marking criteria were used in adaptation. Numerical results for several plane-strain problems have been presented, including the case of different materials and geometry. A comprehensive analysis of the obtained results was given.

关键词： A posteriori error estimate Linear elasticity adaptive algorithm Raviart–Thomas approximation

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ABNGrad: adaptive step size gradient descent for optimizing neural networks

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APPLIED INTELLIGENCE 2024年第3期54卷 2361-2378页

作者： Jiang, Wenhan Liang, Yuqing Jiang, Zhixia Xu, Dongpo Zhou, Linhua Changchun Univ Sci & Technol Sch Math & Stat Changchun 130022 Peoples R China Northeast Normal Univ Sch Math & Stat Changchun 130024 Peoples R China

Stochastic adaptive gradient decent algorithms, such as AdaGrad and Adam, are extensively used to train deep neural networks. However, randomly sampling gradient information introduces instability to the learning rates, leading to adaptive methods with poor generalization. To address this issue, the ABNGrad algorithm, which leverages the absolute value operation and the normalization technique, is proposed. More specifically, the absolute value function is first incorporated into the iteration of the second-order moment estimate to ensure that it monotonically increases. Then, the normalization technique is employed to prevent a rapid decrease in the learning rate. In particular, the techniques used in this paper can also be integrated into other existing adaptive algorithms, such as Adam, AdamW, AdaBound, and RAdam, yielding good performance. Additionally, it is shown that ABNGrad can attain the optimal regret bound for solving online convex optimization problems. Finally, many experimental results illustrate the effectiveness of ABNGrad. For a comprehensive exploration of the advantages of the proposed approach and the specifics of its detailed implementation, the readers are referred to the following https://***/Wenhan-Jiang/***

关键词： Neural networks adaptive algorithm ABNGrad Online learning

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An adaptive integral sliding mode control strategy for medical linear accelerator vacuum system

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APPLIED RADIATION AND ISOTOPES 2024年 210卷 111370页

作者： Sun, Binzhe Wang, Jin Zhou, Shaoheng Zhang, Yong Jiang, Jieqiong Shandong Univ Sch Energy & Power Engn Jinan 250061 Peoples R China Neutron Times Innovat Sci & Technol Qingdao 266041 Peoples R China Shandong Key Lab Neutron Sci & Technol Qingdao 266199 Peoples R China

Medical linear accelerators (MLAs) are critical components for radiation therapy, providing a state-of-the-art treatment platform for cancer therapy. The vacuum system is one of the most important MLA subsystems and its stable operation is necessary to generate high-quality beams. For vacuum system pressure control, traditional proportional-integral-derivative (PID) strategies have disadvantages such as inaccurate and imprecise control response due to its simple calculation. This paper presents an innovative adaptive integral sliding mode control (AISMC) strategy aimed at enhancing the response time, precision of control, and capability to reduce disturbances within the MLA vacuum system. In addition, a nonlinear MLA vacuum system mathematical model is established based on mechanism method. Stability of the developed vacuum control system is validated using Lyapunov stability theory. Simulation results illustrate that the proposed AISMC strategy has better response speed and accuracy than traditional PID-based systems, achieving better pressure tracking performance than traditional sliding mode control strategy with PID control. Most important for the proposed controller, system chattering is effectively mitigated.

关键词： Integral sliding mode control adaptive algorithm Medical linear accelerators Vacuum system Pressure control

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Robust Image Restoration with an adaptive Huber Function Based Fidelity

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INTERNATIONAL JOURNAL OF COMPUTER VISION 2024年第12期132卷 6127-6141页

作者： Song, Lingfei Huang, Hua Beijing Normal Univ Sch Artificial Intelligence Beijing 100875 Peoples R China

Numerous image restoration algorithms have been proposed in the last several decades. These algorithms usually optimize an objective function consisting of an & ell;2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\ell _2}$$\end{document} norm based fidelity and a regularization term, whose optimality could be justified from the view of maximum a posteriori estimation with an assumption that the noise is Gaussian. However, it is known that the & ell;2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\ell _2}$$\end{document} norm based fidelity is very sensitive to gross errors that may appear in the observation. Since real-world image restoration tasks are usually hindered by abnormal pixels, impulsive noise, and other heavy-tailed noise, the utility of these traditional algorithms is limited. Although some robust algorithms have been proposed by replacing the & ell;2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\ell _2}$$\end{document} norm based fidelity with a robust one, they are designed for specific restoration tasks (e.g., multi-frame super-resolution) with a fixed image prior (e.g., the total-variation) and have not provided a principled way to justify the choice of a robust fidelity term. Currently designing a robust algorithm for general image restoration tasks is still an open problem. This paper studies the problem of robust image restoration in both theoretical and algorithmic manners. In the theoretical part, we p

关键词： Robust image restoration Huber function Minimax estimation adaptive algorithm

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Optimization design method for multi-stress accelerated degradation test based on Tweedie exponential dispersion process

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APPLIED MATHEMATICAL MODELLING 2024年 135卷 684-707页

作者： Tian, Runcao Zhang, Fan Du, Hongguang Wang, Peng Civil Aviat Univ China Sch Safety Sci & Engn Tianjin 300300 Peoples R China Civil Aviat Univ China Inst Sci & Technol Innovat Tianjin 300300 Peoples R China Civil Aviat Univ China Key Lab Civil Aircraft Airworthiness Certificat Tianjin 300300 Peoples R China

In the operational environment of electronic products, simultaneous multiple stresses contribute to product degradation, with their interactions often being intricate. To effectively analyze and optimize multi-stress accelerated degradation tests, we introduce a Multi-Stress Generalized Coupling accelerated degradation model based on the Tweedie exponential dispersion process, coupled with a multi-decision optimization approach for test design. The model integrates stress interactions elucidated through fuzzy correlation analysis, reflecting the accelerated degradation behavior consistent with the Tweedie exponential dispersion process. Addressing the complexities of multi-parameter estimation, we propose a parameter estimation method underpinned by the Sine Cosine algorithm for multi-objective optimization within the proposed framework. Considering budgetary constraints, D-optimization and V-optimization strategies are deployed to finetune test scheme allocations, optimizing resource utilization. Validation through a three-stress accelerated degradation test on LED chips confirms the model's efficacy in reliability assessment. Our findings indicate the superior descriptive power of the Tweedie exponential dispersion model for complex degradation phenomena and the proposed model's closer approximation to stress conditions in real-world settings, with a methodological error maintained below 2 %. Furthermore, the test optimization method enhances the D-optimization and V-optimization objective values by 21.20 % and reduces them by 4.08 %, respectively, marking a substantial improvement over traditional schemes and endorsing the holistic advancement of multi-stress accelerated degradation testing methodologies.

关键词： Accelerated degradation test Multi-stress coupling Tweedie exponential dispersion process adaptive algorithm Multi-decision optimization Parameter estimation

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adaptive-Wavelet-Threshold-Function-Based M2M Gaussian Noise Removal Method

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IEEE INTERNET OF THINGS JOURNAL 2024年第20期11卷 33177-33192页

作者： Li, Shuang Liu, Shuai Wang, Jingjing Yan, Shefeng Liu, Jiahao Du, Zehua Qingdao Univ Sci & Technol Sch Informat Sci & Technol Qingdao 266061 Peoples R China Univ Chinese Acad Sci Inst Acoust Beijing 100190 Peoples R China Ocean Univ China Fac Informat Sci & Engn Qingdao 266100 Shandong Peoples R China Ocean Univ China Fac Informat Sci & Engn Qingdao Peoples R China

With little or no human intervention, almost every object in Internet of Things (IoT) has ability to communicate, sense, and process information to make everything connected. Noise in complex environment has a great impact on machine-to-machine (M2M) interaction in IoT. adaptive wavelet threshold function (AWTF)-based M2M Gaussian Noise Removal Method is proposed in this article. First, a bilateral enhanced wavelet threshold function is derived based on the adjustable zeroing window. Further, threshold is used to construct a bilateral enhanced wavelet threshold function, which can eliminate the oscillations in the existing wavelet threshold function. This ensures that there is no break in wavelet coefficients during the reconstruction process and that stable wavelet decomposition and reconstruction can be achieved. The signal-to-noise ratio (SNR) of a signal is estimated based on the variance of the noise-containing signal, and the zeroing window parameters are adjusted adaptively according to the SNR value to eliminate the noisy wavelet coefficients and improve the denoising performance. In addition, when the wavelet coefficients are reconstructed, the proposed algorithm can select a suitable threshold function according to a particular threshold value, which improves the robustness of the algorithm. "Doppler" and "Bumps" standard test signals are used as interactive signals to simulate the proposed algorithms. For "Doppler" signals, the SNR, root mean square error (RMSE), and noise suppression ratio (NSR) of AWTF increased by 8.48%, 42.59%, and 1.69%, respectively, compared with the GDES+ABC algorithm. For "Bumps" signal, the SNR, RMSE, and NSR of AWTF are improved by 11.67%, 24.46%, and 2.99%, respectively, compared with GDES+ABC algorithm. In addition, we also use different modulated signals to carry out real field experiments in Qingdao cruise ship home port, which proves the effectiveness of the proposed algorithm.

关键词： Noise reduction Signal processing algorithms Internet of Things Gaussian noise Wavelet transforms Signal to noise ratio Wavelet domain adaptive algorithm machine-to-machine interaction threshold function wavelet transform (WT)

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Advanced adaptive Rule-Based Energy Management for Hybrid Energy Storage Systems (HESSs) to Enhance the Driving Range of Electric Vehicles

VEHICLES

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VEHICLES 2025年第1期7卷 6-6页

作者： Wai, Chew Kuew Sadeq, Taha Hau, Lee Cheun Univ Tunku Abdul Rahman Lee Kong Chian Fac Engn & Sci Sungai Long Campus Kajang 43000 Selangor Malaysia Univ Tun Hussein Onn Malaysia Fac Mech & Mfg Engn Parit Raja Campus Parit Raja 86400 Johor Malaysia

The energy storage system (ESS) plays a crucial role in electric vehicles (EVs), impacting their performance and efficiency. While batteries are the standard choice for energy storage, they come with drawbacks like low power density and limited life cycles, which can hinder pure battery electric vehicles (PBEVs). To address these issues, a hybrid energy storage system (HESS) that combines a battery with a supercapacitor provides a more effective solution. The battery delivers consistent power, while the supercapacitor manages peak power demands and regenerative braking energy. This study proposes a new energy management strategy for the HESS, an advanced adaptive rule-based algorithm. The results of the standard rule-based and adaptive rule-based algorithms are used to verify the proposed control algorithm. The system was modeled in MATLAB/Simulink and evaluated across three driving cycles-UDDS, NYCC, and Japan1015-while varying states of charge for the supercapacitors. The findings indicate that the HESS significantly alleviates battery stress compared to a pure battery system, enhancing both efficiency and lifespan. Among the algorithms tested, the advanced adaptive rule-based algorithm yielded the best results, increasing the number of viable drive cycles.

关键词： batteries supercapacitors adaptive algorithm hybrid energy storage electric vehicle

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Application of adaptive algorithms in Accounting Budget Forecasting 23

Application of Adaptive Algorithms in Accounting Budget Fore...

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Proceedings of the 3rd International Conference on Electronic Information Technology and Smart Agriculture

作者： Zhiqiang Wu School of Business Henan University China

ISBN: (纸本)9798400716775

With the continuous changes in the economic environment and the intensification of market competition, the accuracy of accounting budget forecasts has become increasingly important for corporate strategic planning and decision-making. Traditional forecasting methods often rely on historical data and linear models, but these methods may not provide sufficient accuracy and flexibility when facing complex and dynamic market environments. In recent years, adaptive algorithms have received widespread attention due to their advantages in dealing with complex systems and dynamic environments. This article explores the application of adaptive algorithms in accounting budget forecasting and verifies its effectiveness through empirical analysis. We use the financial statement data of 1,000 different listed companies in the "GlobalFinance" database over the past ten years, use adaptive algorithms to make predictions, and compare them with traditional prediction methods. The results show that the adaptive algorithm outperforms the traditional method in multiple performance indicators, showing its great potential in accounting budget forecasting. This article not only provides strong empirical support for the application of adaptive algorithms in the field of financial forecasting, but also provides theoretical basis and practical guidance for enterprises to adopt this advanced technology in actual operations.

关键词： accounting budget forecast adaptive algorithm empirical analysis financial statements forecast performance

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