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European Signal Processing Conference

作者： Jesper Kjaer Nielsen Tobias Lindstrom Jensen Jesper Rindom Jensen Mads Grcesboll Christensen Soren Holdt Jensen Aalborg University Dept. of Electronic Systems Aalborg University Audio Analysis Lab

ISBN: (纸本)9781509018918

In many spectral estimation and array processing problems, the process of finding estimates of model parameters often involves the optimisation of a cost function containing multiple peaks and dips. Such non-convex problems are hard to solve using traditional optimisation algorithms developed for convex problems, and computationally intensive grid searches are therefore often used instead. In this paper, we establish an analytical connection between the grid size and the parametrisation of the cost function so that the grid size can be selected as coarsely as possible to lower the computation time. Additionally, we show via three common examples how the grid size depends on parameters such as the number of data points or the number of sensors in DOA estimation. We also demonstrate that the computation time can potentially be lowered by several orders of magnitude by combining a coarse grid search with a local refinement step.

关键词： Optimisation DOA estimation Fundamental frequency estimation Periodogram Direction of arrival estimation cyclogram Cost functions computational time Spectrum Analysis grids grid dimension Grid computing trellis search optimization algorithms Grates

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Method with Batching for Stochastic Finite-Sum Variational Inequalities in Non-Euclidean Setting

arXiv

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arXiv 2024年

作者： Pichugin, Alexander Pechin, Maksim Beznosikov, Aleksandr Novitskii, Vasilii Gasnikov, Alexander Moscow Institute of Physics and Technology Moscow Russia Ivannikov Institute for System Programming of RAS Moscow Russia Innopolis University Innopolis Russia

Variational inequalities are a universal optimization paradigm that incorporate classical minimization and saddle point problems. Nowadays more and more tasks require to consider stochastic formulations of optimization problems. In this paper, we present an analysis of a method that gives optimal convergence estimates for monotone stochastic finite-sum variational inequalities. In contrast to the previous works, our method supports batching, does not lose the oracle complexity optimality and uses an arbitrary Bregman distance to take into account geometry of the problem. Paper provides experimental confirmation to algorithm’s effectiveness. Copyright © 2024, The Authors. All rights reserved.

关键词： optimization algorithms

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H-DES: A Quantum-Classical Hybrid Differential Equation Solver

arXiv

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arXiv 2024年

作者： Jaffali, Hamza de Araujo, Jonas Bastos Milazzo, Nadia Reina, Marta de Boutray, Henri Baumann, Karla Holweck, Frédéric ColibriTD 91 Rue du Faubourg Saint Honoré Paris75008 France

In this article, we introduce an original hybrid quantum-classical algorithm based on a variational quantum algorithm for solving systems of differential equations. The algorithm relies on a spectral method, which involves encoding the solution functions in the amplitudes of the quantum states generated by different parametrized circuits and transforms the task of solving the differential equations into an optimization problem. We first describe the principle of the algorithm from a theoretical point of view. We provide a detailed pseudo-code of the algorithm, on which we conduct a complexity analysis to highlight its scaling properties. We apply it to a set of examples, showcasing its applicability across diverse sets of differential equations. We discuss the advantages of our method and potential avenues for further exploration and refinement. © 2024, CC BY-NC-ND.

关键词： optimization algorithms

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Silhouette-based 3D Model for Zebrafish High-throughput Imaging

Silhouette-based 3D Model for Zebrafish High-throughput Imag...

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International Conference on Image Processing Theory, Tools and Applications

作者： Yuanhao Guo Wouter J. Veneman Herman P. Spaink Fons J. Verbeek Imaging and BioInformatics Section LIACS Leiden University Department of Animal Sciences and Health Institute of Biology Leiden University

ISBN: (纸本)9781479986385

Good estimations of volume and surface area are important to biological systems measurement. In this paper we develop a 3D reconstruction from evenly sampled axial views in order to enable the volume and surface area measurement. We develop this system for high throughput applications with the zebrafish model system. The VAST BioImager is specifically developed for this purpose and with this system the axial views can be produced. Silhouettes derived from the axial sequence are shape priors which can be directly used to solve the camera calibration problem that is required for the accurate 3D reconstruction. Nonlinear optimisation algorithms have shown to be suitable for the further development of the reconstruction problem. The method proposed in this paper can be included in a measurement pipeline that is used in all kinds of high throughput applications in the zebrafish field. From the 3D reconstruction features can be derived that will contribute to the phenotyping of zebrafish.

关键词： VAST BioImager Zebrafish 3D model Shape carving Volume and surface area measurement three-dimensional displays Zebrafish optimization algorithms surface area AXIAL

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A new measurement matrix optimal algorithm based on SVD

A new measurement matrix optimal algorithm based on SVD

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2015 IET International Conference on Biomedical Image and Signal Processing (ICBISP 2015)

作者： Fei Zhong Yue Zhao Shuxu Guo College of Electrical and Information engineering Changchun Institute of Technology Changchun 130012 China College of Electronic Science and Engineering Jilin University Changchun Jilin 130012 P. R. China

This paper proposes a new compressed sensing (CS) measurement matrix optimal algorithms based on singular value decomposition (SVD). New measurement matrix can be obtained by using SVD for the decomposition of Gaussian measurement matrix. Simulation results prove that using the new measurement matrix can not only greatly improve the robustness and stability of CS algorithm, but also have better behaviors on image quality recovery. Moreover, this method is suitable for the further study of other random measurement matrix.

关键词： compressed sensing (CS) measurement matrix singular value decomposition (SVD) measurement matrix Singular value decomposition Swine vesicular disease optimization algorithms

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A goal-based weighting for composite indicators constructed through Ordered Weighted Averaging (OWA) operator

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METHODSX 2024年 12卷 102575页

作者： Liborio, Matheus Pereira Ekel, Petr Iakovlevitch Laudares, Sandro Martins, Carlos Augusto Paiva da Silva Pantifical Catholic Univ Minas Gerais 500 Dom Jose Gaspar St BR-30535901 Belo Horizonte MG Brazil

The Ordered Weighted Averaging (OWA) operator is a multicriteria method that has conquered space among researchers in the composite indicators field. Typically, OWA operator weights are defined by the decision maker. This type of weighting is highly criticized, as decision-makers are susceptible to errors and bias in judgment. Some methods have been used to define OWA operator weights objectively. However, none of them is concerned about the quality of the composite indicator. This paper introduces a method that defines the weights of the OWA operator based on two quality parameters of the composite indicator: the ability to capture the concept of the multidimensional phenomenon and the informational loss. The method can be implemented in Microsoft Excel Solver and has a high degree of flexibility and applicability in problems of a multidimensional nature and a high degree of appropriation by researchers and practitioners in the area. center dot Defines weights that maximize the ability of the composite indicator to capture the concept of the multidimensional phenomenon. center dot Considers restrictions to limit the informational loss of the composite indicator or emphasize positive or negative aspects of the multidimensional phenomenon. center dot Offers flexibility in setting the objective and constraints of the optimization algorithm.

关键词： Multicriteria methods Operation research Multidimensional problems Data-driven weighting scheme Informational loss optimization algorithms

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Advancing structural integrity prediction with optimized neural network and vibration analysis

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JOURNAL OF STRUCTURAL INTEGRITY AND MAINTENANCE 2024年第3期9卷

作者： Khatir, Abdelwahhab Capozucca, Roberto Magagnini, Erica Brahim, Abdelmoumin Oulad Osmani, Amine Khatir, Samir Abualigah, Laith Polytech Univ Marche Struct Sect DICEA Ancona Italy Univ Sci & Technol Mohamed Boudiaf Oran USTO MB Dept Civil Engn Oran Algeria Ho Chi Minh City Open Univ Ctr Engn Applicat & Technol Solut Ho Chi Minh City Vietnam Al Al Bayt Univ Dept Comp Sci Mafraq Jordan Lebanese Amer Univ Dept Elect & Comp Engn Beirut Lebanon Middle East Univ MEU Res Unit Amman Jordan

Detecting and locating damage is a crucial endeavor within the field of structural integrity. While Artificial Neural Networks (ANNs) have shown promise in this regard, they have certain limitations that can be overcome through modifications in terms of their structural design and training methodologies. In this study, we propose a new optimization approach, specifically leveraging the Grasshopper optimization Algorithm (GOA), to enhance the performance of ANNs for predicting multiple damages represented by holes in the aluminum plate. Input parameters are derived from natural frequencies, while hole locations serve as outputs. We utilize a Finite Element Model (FEM) to generate data through simulation, varying hole locations for comprehensive analysis. To authenticate our method, we gather experimental data from vibration analyses of damaged plates spanning various hole locations. A comparative analysis is conducted of proposed algorithm by evaluating its performance against two established metaheuristic algorithms: the Genetic Algorithm (GA) and Ant Colony optimization (ACO). This comparison was performed to assess the relative effectiveness of our approach. Our novel approach demonstrates superior performance in damage forecasting, offering promising prospects for structural integrity applications.

关键词： Structural integrity prediction GOA optimization algorithms vibration analysis

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DCFH: A dynamic clustering approach based on fire hawk optimizer in flying ad hoc networks

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Vehicular Communications 2024年 47卷

作者： Hosseinzadeh, Mehdi Ali, Saqib Ahmad, Husham Jawad Alanazi, Faisal Yousefpoor, Mohammad Sadegh Yousefpoor, Efat Darwesh, Aso Rahmani, Amir Masoud Lee, Sang-Woong Institute of Research and Development Duy Tan University Da Nang Viet Nam School of Medicine and Pharmacy Duy Tan University Da Nang Viet Nam Department of Information Systems College of Economics and Political Science Sultan Qaboos University Al Khoudh Muscat Oman Department of Communication and Computer Engineering Cihan University-Erbil Kurdistan Region Iraq Department of Electrical Engineering College of Engineering Prince Sattam bin Abdulaziz University Al-Kharj 11942 Saudi Arabia Center of Research and Strategic Studies Lebanese French University Kurdistan Region Iraq Department of Information Technology University of Human Development Kurdistan Region Sulaymaniyah Iraq Future Technology Research Center National Yunlin University of Science and Technology Yunlin Taiwan Pattern Recognition and Machine Learning Lab Gachon University 1342 Seongnamdaero Sujeonggu Seongnam 13120 South Korea

In flying ad hoc networks (FANETs), unmanned aerial vehicles (UAVs) communicate with each other without any fixed infrastructure. Because of frequent topological changes, instability of wireless communication, three-dimensional movement of UAVs, and limited resources, especially energy, FANETs deal with many challenges, especially the instability of UAV swarms. One solution to address these problems is clustering because it maintains network performance and increases scalability. In this paper, a dynamic clustering scheme based on fire hawk optimizer (DCFH) is proposed for FANETs. In DCFH, each cluster head calculates the period of hello messages in its cluster based on its velocity. Then, a fire hawk optimizer (FHO)-based dynamic clustering operation is carried out to determine the role of each UAV (cluster head (CH) or cluster member (CM)) in the network. To calculate the fitness value of each fire hawk, a fitness function is suggested based on four elements, namely the balance of energy consumption, the number of isolated clusters, the distribution of CHs, and the neighbor degree. To improve cluster stability, each CH manages the movement of its CMs and adjusts it based on its movement in the network. In the last phase, DCFH defines a greedy routing process to determine the next-hop node based on a score, which consists of distance between CHs, energy, and buffer capacity. Finally, DCFH is simulated using the network simulator version 2 (NS2), and its performance is compared with three methods, including the mobility-based weighted cluster routing scheme (MWCRSF), the dynamic clustering mechanism (DCM), and the Grey wolf optimization (GWO)-based clustering protocol. The simulation results show that DCFH well manages the number of clusters in the network. It improves the cluster construction time (about 55.51%), cluster lifetime (approximately 11.13%), energy consumption (about 15.16%), network lifetime (about 2.6%), throughput (approximately 3.9%), packet deliver

关键词： Artificial intelligence (AI) Clustering Flying ad hoc networks (FANETs) optimization algorithms Unmanned aerial vehicles (UAVs)

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Hardware-in-the-loop testing of grid-tied PMSG-based wind power generation system with optimum PI parameters

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e-Prime - Advances in Electrical Engineering, Electronics and Energy 2023年 5卷

作者： Tripathi, S.M. Singh, U.P. Singh, Sonu Rai, N.K. Himani Srivastava, A.K. Power & Energy Research Centre (PERC) Department of Electrical Engineering Kamla Nehru Institute of Technology (U.P.) Sultanpur India Rail Vikas Nigam Limited U.P. Pilibhit India Indian Railways India Department of Electrical Engineering Institute of Engineering and Technology Dr. Rammanohar Lohia Avadh University U.P. Ayodhya India

The regulators based on PI control law continue to be the key elements in many of the industrial systems for their control. Likewise, the wind power generation systems (WPGSs) also make extensive use of PI regulators in their control schemes. The enhanced performance of these WPGS depends on proper selection of the PI regulator parameters. This paper deals with the control of a grid-tied permanent magnet synchronous generator (PMSG)-based WPGS wherein, a new attempt has been depicted to apply the most optimum design of the involved PI regulator parameters for the proposed WPGS based on standard performance indices making use of four popular optimization algorithms namely genetic algorithm (GA), cultural algorithm (CA), particle swarm optimization (PSO) and artificial bee colony (ABC). An informative discussion has also been presented which would be useful for practicing engineers/researchers to select flexibly and reasonably the PI regulators parameters meant for the control of the proposed WPGS. A detailed simulation model developed in MATLAB/Simulink has been used to analyze the performance of the proposed PMSG-based WPGS employed with the most optimum values of PI regulator parameters. The performances of WPGS have been compared while the most optimum PI regulator parameters have been included in the control system, and also when incorporating the PI regulator parameters in WPGS control designed via classical D-partition technique. The results obtained under gradually changing wind speed profile show the improvement in the performance of WPGS in terms of peak overshoot, time response and waveform oscillations. The experimental validation of the control performances have been carried out by way of real-time hardware-in-the-loop (HIL) testing making use of Typhoon HIL402 emulator and TMS320F28335 digital signal controller. The obtained real time HIL results are in close agreement to the results obtained in simulations using MATLAB/Simulink. A deviation of less than

关键词： Hardware-in-the-loop testing optimization algorithms Permanent magnet synchronous generator (PMSG) PI regulator Wind power generation systems (WPGS)

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Application of the Monte Carlo Method in Simulative Generation Test Problems Simulative Generation Test Problems

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Journal of Beijing Institute of Technology 1992年第2期1卷 158-165页

作者：黄心渊万耀青北京理工大学车辆工程学院

An approach for generating test problems by a computer using the Monte Carlo method based upon user-given characterizations is described.A single point X~* is prespocified by the user to be a solution of the test *** approach is flex- ible enough to specify function values,gradients,Hesse,degeneracy degree and ill- conditioned degree at the point X~*.Other numerical features such as indefiniteness, convexity are also under user's control.

关键词： optimization algorithms Monte Carlo method convex optimum value ill-conditioned matrices

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