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第40届中国控制会议

作者： Peng Yuan Yiran Miao Deqing Huang Junkai Hao Na Qin School of Electrical Engineering Southwest Jiaotong University Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China

FLP（Facility layout problem） is a common problem in engineering field. The past research tend to focus on the twodimensional space and a small amount of three-dimensional box space as well as vertical cylinder space. The FLP in horizontal cylinder space is less researched. Lots of FLP of box space and vertical cylinder space can transform to FLP of two-dimensional space easily, however, the FLP of horizontal cylinder space need design special calculation method of overlap constraint and boundary constraint. This paper designed the calculation method of overlap constraint and boundary constraint, used adaptive gradient descent algorithm with heuristic strategy to optimize the facility layout in horizontal cylinder space. On this basis,added symmetry constraint, absolute height constraint and relative distance constraint to close to the real engineering *** experiment results confirm the feasible of proposed scheme.

关键词： facility layout problem horizontal cylinder space gradient descent algorithm

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Parallel tracing of multiple trajectories in gradient descent algorithm with Cell Broadband Engine 09

Parallel tracing of multiple trajectories in gradient descen...

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Proceedings of the 2009 Spring Simulation Multiconference

作者： Yuri Boiko Gabriel Wainer Carleton University Ottawa ON Canada

Explored here is the ability of Cell B.E. to efficiently reveal viable solutions of nonlinear function approximation with multilayer perceptron (MLP) employing gradient descent algorithm. The capacity of Cell BE to asynchronously trace several trajectories of implemented gradient descent algorithm from random set of starting points offers advantage of revealing statistical trends and classifying viable optimal approximations delivered by simulated function generator. Approximation conditions of surfaces of 2nd and 3rd order with saddle points, such as hyperbolic paraboloid z=x2-y2, and Monkey saddle z=x3-3xy2, are determined via implementation of gradient descent algorithm (its back propagation version) for 3 layers MPL. Demonstrated are conditions of generating function approximations with (1)highly irregular error distribution, (2)close to uniform error distribution as well as (3)enhanced approximation. In the last case the overall error is significantly smaller than that programmed in the algorithm to be attained via training patterns. Such enhanced solutions offer advantage of attaining highly accurate function representation within minimized resources of MLP (i.e. with minimized number of hidden neurons in the MLP).

关键词： cell broadband engine gradient descent algorithm multiple trajectories

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On-line modification of T-S fuzzy models based on gradient descent algorithm

On-line modification of T-S fuzzy models based on gradient d...

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第33届中国控制与决策会议

作者： FENG Haodong WEI Dong JIAO Huanyan School of Electrical and Information Engineering Beijing University of Civil Engineering and Architecture Beijing Key Laboratory of Intelligent Processing for Building Big Data Beijing Municipal Science and Technology Commission

The gradient descent algorithm is applied to the model parameter correction algorithm in view of the shortcoming that T-S fuzzy model cannot be used for real-time adaptive parameter *** this paper,an online model correction method combining T-S fuzzy model with gradient descent algorithm is proposed,and the operation data of a subway air-conditioning system in Wuhan is used for *** experimental results show that the T-S fuzzy model modified by gradient descent algorithm has better accuracy and higher operational efficiency.

关键词： T-S fuzzy model gradient descent algorithm Air conditioning system model

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A gradient descent based algorithm for lp minimization

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2020年第1期283卷 47-56页

作者： Jiang, Shan Fang, Shu-Cherng Nie, Tiantian Xing, Wenxun Xiamen Univ Sch Management Xiamen 361005 Peoples R China North Carolina State Univ Edward P Fitts Dept Ind & Syst Engn Raleigh NC 27695 USA Univ North Carolina Charlotte Charlotte NC 28223 USA Tsinghua Univ Dept Math Sci Beijing 100084 Peoples R China

In this paper, we study the linearly constrained l(p) minimization problem with p is an element of (0, 1). Unlike those known works in the literature that propose solving relaxed epsilon-KKT conditions, we introduce a scaled KKT condition without involving any relaxation of the optimality conditions. A gradient-descent-based algorithm that works only on the positive entries of variables is then proposed to find solutions satisfying the scaled KKT condition without invoking the nondifferentiability issue. The convergence proof and complexity analysis of the proposed algorithm are provided. Computational experiments support that the proposed algorithm is capable of achieving much better sparse recovery in reasonable computational time compared to state-of-the-art interior-point based algorithms. (C) 2019 Elsevier B.V. All rights reserved.

关键词： Global optimization Nonsmooth optimization Nonconvex optimization gradient descent algorithm KKT condition

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Backflow Power Optimization of DAB with gradient descent algorithm Based Extended-Phase-Shift Control in EER Application

Backflow Power Optimization of DAB with Gradient Descent Alg...

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China International Electrical and Energy Conference (CIEEC)

作者： Bingkai Zhou Xiaofeng Yang Zhi Zhang Zejie Li Trillion Q. Zheng Xiaojie You School of Electrical Engineering Beijing Jiaotong University Beijing China

ISBN: (数字)9781728116754

ISBN: (纸本)9781728116761

To reduce the backflow power of dual-active- bridge (DAB) DC-DC converter and improve the operating efficiency, this paper proposes a gradient descent algorithm (GD- EPS) based extended-phase-shift (EPS) control. Firstly, the transmission and backflow power models of DAB converter with EPS and single-phase-shift (SPS) control are established, and the influencing factors of backflow power are analyzed. Secondly, according to the backflow power model, the gradient descent algorithm for solving the optimal solution of backflow power is obtained. On this basis, the output voltage closed-loop control is added to derive the DAB overall optimal control scheme. At last, the simulation models of DAB converter with GD-EPS and SPS control are built and compared, it is verified that the GD-EPS control can optimize the backflow power better than the SPS control when the load and input voltage change.

关键词： dual-active-bridge extended-phase-shift backflow power optimization gradient descent algorithm Audio recording steepest descent algorithm shift control powered models Encapsulated PostScript exophthalmos producing substance descent control ring Power (Psychology) Energy sources optimal solution SAFETY PRECEDENCE SEQUENCE solar power satellites Special purpose ships energy efficiency ratio

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gradient descent Localization algorithm Based on Received Signal Strength Technique in a Noisy Wireless Sensor Network 4

Gradient Descent Localization Algorithm Based on Received Si...

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4th International Conference on Advances in Computational Tools for Engineering Applications (ACTEA)

作者： Hijazi, Hussein Kandil, Nahi Zaarour, Nour Hakem, Nadir Univ Quebec Abitibi Temiscamingue Lab Rech Telebec Commun Souterraines Val Dor PQ Canada

ISBN: (纸本)9781728101309

In this article we propose an improved RSS-based localization technique in a wireless sensor network based on the gradient descent optimization algorithm in a noisy propagation model, usually RSS is susceptible to the noise factor affecting the estimated distance of the sensor network Generally, to localize an unknown node, a specific number of anchors (reference nodes) is required this number of needed anchors will increase in the presence of noise factor. Results have shown that, using our improved technique, the number of used anchors is reduced despite the existence of the noise aspect A comparison with other techniques is made to show the effectiveness of our proposed approach.

关键词： Wireless sensor network localization technique optimization technique gradient descent algorithm

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Implementation of hybrid neuro-fuzzy controller based on radial basis function network with gradient descent algorithm for non-linear system

Implementation of hybrid neuro-fuzzy controller based on rad...

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IEEE Power, Communication and Information Technology Conference

作者： Ravi Kumar Soni M. J. Nigam R. Mitra Electronics & Communication Engineering Department IIT Roorkee

ISBN: (纸本)9781479974566

The main focus of this paper is on stabilization of non-linear system using proposed Hybrid Neuro-fuzzy Logic Controller based on Radial Basis Function Network (HNFRBFN). A control unit matrix has been introduced according to the non-linearity and uncertainty of the plant. The parameters used to obtain the individual control action in this matrix are optimized by gradient descent algorithm. IF part of the fuzzy rules is approximated using Radial Basis Function (RBF) Network & THEN part of fuzzy rules are synthesized by the control action matrix which incorporates Error-correction algorithm. This error correction algorithm forms the basis of HNFRBFN. The simulation results obtained show that the suggested controller gives promising improvement and better performance.

关键词： Radial basis membership function Neural network Fuzzy logic controller gradient descent algorithm

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Optimization of industrial energy consumption for sustainability using time-series regression and gradient descent algorithm based on historical electricity consumption data

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Sustainability Analytics and Modeling 2022年 2卷

作者： Richard Opoku George Y. Obeng Louis K. Osei John P. Kizito Department of Mechanical Engineering Kwame Nkrumah University of Science and Technology Kumasi Ghana The Brew-Hammond Energy Centre College of Engineering KNUST Kumasi Ghana Technology Consultancy Centre College of Engineering KNUST Kumasi Ghana Bulk Oil Storage and Transportation (BOST) Company Kumasi Ghana North Carolina Agricultural and Technical State University Greensboro United States

Optimizing electricity consumption to minimize wastage and reduce cost is a major challenge in many industries. This is because, in many cases, the effect of the independent variables contributing to the total electricity consumption and cost are latent. The purpose of this study is to apply numerical techniques to identify and optimize these independent variables in order to improve sustainable energy management in industries to minimize wastage. Regression analysis was first applied to identify and decouple the independent variables to determine their individual effects on electricity consumption and cost. A cost function called the Mean Square Error (MSE) was then used to optimize these independent variables using gradient descent algorithm (GDA). In a case study, the developed approach that combines time series regression analysis with gradient descent optimization was used to analyze the electricity consumption data of an oil distribution company for the period 2015 to 2018. The results showed potential electricity savings of 124,684 kWh and cost savings of US$ 25,375 annually, when the facility is operated at optimum parameters of 0.95 power factor, 260 kVA maximum demand and 25,000 kWh active electricity consumption. The novelty of this study is that a procedure that combines time series regression analysis (RA) and gradient descent algorithm (GDA) has been developed and applied to decouple and optimize the independent variables that affect electricity consumption in an industry.

关键词： minimizing industrial energy wastage sustainability regression analysis optimization mean square error gradient descent algorithm

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Accurate Design of Very-High-Frequency Resonant Converter Based on gradient descent and Considering Multiple Harmonics

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2025年第3期72卷 2529-2539页

作者： Chen, Shikai Chen, Yanfeng Zhang, Bo Qiu, Dongyuan South China Univ Technol Sch Elect Power Guangzhou 510640 Peoples R China

Due to the inherent strong coupling and nonlinearity in typical very-high-frequency (VHF, 30-300 MHz) resonant converters, conventional design methods face challenges in considering multiple harmonics and identifying their complex coupling relationships, which limits the design accuracy of resonant parameters. In order to solve this issue, this article presents a new design method, which involves considering multiple harmonics for the separate design of the inverter and rectifier stages and identify their coupling relationships by using the gradient descent algorithm. The simulation result shows that the output power, particularly the soft-switching feature are very consistent with the design requirement. Compared to the conventional design methods, the proposed one in theoretical design has higher accuracy and reduces dependence on simulation tools, which helps to guide the further consideration of parasitic parameters in practical design and develop it into a computer program for easier application. Finally, the feasibility and effectiveness of the proposed method are experimentally verified by a 30 MHz prototype with a rated input power of 20W.

关键词： Harmonic analysis Inverters Design methodology Couplings Accuracy Voltage Time-domain analysis gradient descent algorithm resonant dc-dc converter very-high-frequency (VHF)

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Hybrid gradient descent Golden Eagle Optimization (HGDGEO) algorithm-Based Efficient Heterogeneous Resource Scheduling for Big Data Processing on Clouds

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WIRELESS PERSONAL COMMUNICATIONS 2023年第2期129卷 1175-1195页

作者： Jagadish Kumar, N. Balasubramanian, C. Velammal Inst Technol Dept Informat Technol Chennai 601204 Tamil Nadu India PSR Engn Coll Dept Comp Sci & Engn Sivakasi 626140 Tamil Nadu India

Resource scheduling is indispensable for enhancing the system performance during big data processing on clouds. It is highly useful for attaining significant utilization of computing resources completely concentrating towards the facilitation of resource scalability and on-demand services. The resources essential for running different applications is determined to be maximum heterogeneous in cloud computing. This heterogeneous resource demand introduces a resource gap in which some of the resource potentialities are drained on par with the other resource potentialities still available in the same server resulting in imbalanced resource utilization. This imbalanced resource allocation condition is more apparent when the computing resources are more heterogeneous. At this juncture, intelligent resource scheduling strategy becomes essential to distribute resources for big data processing by adopting a potential decision-making process that focusses on the objective of achieving necessitated tasks over time. In this paper, Hybrid gradient descent Golden Eagle Optimization (HGDGEO) algorithm-based efficient heterogeneous resource scheduling process is proposed for handling the challenges that are highly possible during big data processing in the Hadoop heterogenous cloud environment. This HGDGEO algorithm is proposed as an adaptive resource scheduling strategy that handles the dynamic characteristics of the resources and users' fluctuating demand during big data stream processing by mimicking the golden eagles' intelligence which alternates the speed of tuning at different spiral trajectory stages of hunting. It handles big data processing by adopting two adaptive parameters which completely concentrates on optimal resource allocation to suitable VMs in the shortest time possible depending on their requirements. The simulation results of HGDGEO algorithm confirmed its predominance in terms of makespan, load balance and throughput on par with the competitive resource sche

关键词： gradient descent algorithm Golden eagle optimization Big data processing Hadoop cloud environment Hunting spiral trajectory

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