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Emergency Science and Information Technology (ICESIT), IEEE International conference on

作者： Ehtisham Lodhi Pu Yang Lina Wang M. Adil Khan Zeeshan Lodhi Usman Javed Qasim Saleem School of Automation Science and Electrical Engineering Beihang University Beijing China The SKL for Management and Control of Complex Systems Chinese Academy of Sciences Institute of Automation Beijing China Chang'an University Xi'an China COMSATS University Islamabad Pakistan Centre for Advanced Studies in Physics (CASP) GC University Lahore Pakistan

ISBN: (纸本)9781665435321

Currently, Photovoltaic (PV) technology has higher demand in the market and gaining momentum day by day. However, partial shading is the most significant concern as it reduces the efficiency of standalone PV systems. Partially shading is typically induced by non-uniform sunlight and uncertain temperature fluctuations. The maximum power point tracking (MPPT) algorithms play a major role in determining the overall system's efficiency. The PV system creates several peaks in its power voltage (P-V) characteristic curve under partial shadowing. To make the PV system run under partial shading at global maximum power point (GMPP), the dragonfly optimization (DFO) algorithm is put forward in this research article. The proposed DFO technique and other commonly used MPPT techniques, such as Particle swarm optimization (PSO), Perturb and Observe (P&O), is investigated through theoretical analysis and simulation using Matlab/Simulink to authenticate the overall performance of the DFO approach under partial shading. Furthermore, the comparison demonstrates that the suggested DFO strategy provides very high reliability, efficiency, robustness, rapid power tracking and lower response time to trace the GMPP than PSO and P&O techniques. Hence, the DFO technique's overall performance under partial shading is appropriate and satisfying.

关键词： Maximum power point trackers Photovoltaic systems Temperature software algorithms Voltage Steady-state Time factors

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Reducing Voltage Variation and Active Power Degeneracy in Optimum IPR Problem using Elitist NSGA-II and GWO Algorithm

Reducing Voltage Variation and Active Power Degeneracy in Op...

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software, Systems and Information Technology (SSITCON), International conference on

作者： M. Kalimuthu P. S. Manoharan D. Suriya Kumari Usha. N R. Priyadarshini P. M. Devie Department of Electrical and Electronics Engineering Thiagarajar College of Engineering Madurai India

ISBN: (数字)9798350352931

ISBN: (纸本)9798350352948

Enhancement heuristics likely NSGA-II and Grey Wolf Optimisation Algorithm presented in this study as a way to reduce voltage variation and active power degeneracy. Active power degeneracy and bus voltage discrepancies need reduction among the optimum IPR problem, which is a nonlinear constrained multi-faceted refinement concern. Since the issue is handled as a real multi-faceted refinement concern, several trade-off remedies are given. The selection of trade-off remedies from variants is executed by Pareto-optimal front which finalizes the choices undertaken. The validation of efficient performance by NSGA-II is well showcased utilizing the industry-standard IEEE 14-bus test system and IEEE 30 bus system. In IEEE 14 and 30 bus system SVC connected with the bus the real power loss and voltage Deviation output is reduced compared to without SVC buses. A comparative scenario among PSAT, NSGA-II and Grey Wolf Optimisation (GWO) has been well established projecting NSGA-II is suited for only multi-objective functions. Although GWO is intended for single-objective functions, multi-objective function situations can be modified to use it. It is a quick method of *** method as dynamically efficient among others.

关键词： Heuristic algorithms Static VAr compensators Voltage Intellectual property software systems Computational efficiency Object recognition Information technology optimization

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Real time high precision harmonic analysis of signals in power systems using HW/SW Co-Design methodology on FPGAs

Real time high precision harmonic analysis of signals in pow...

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IEEE International conference on Multi Topic

作者： Etsam Anjum Fahad A. Khan Zubair A. Khan Embedded System Division Mentor Graphics Corporation Lahore Pakistan Department of Electrical Engineering University of Engineering and Technology Lahore Pakistan

Increase in use of nonlinear devices in power systems has caused serious harmonic pollution. There is always a need to measure these harmonics for power quality assessment and in cases for mitigating these harmonics. The problem of precision measurement becomes irksome because of effects of frequency deviation. Over the course of time a whole slew of digital signal processing algorithms have been proposed to accurately analyze harmonics in scenarios of frequency deviation but they come with a much increased cost in computational complexity. These computational requirements make them impractical for use in real-time monitoring systems. A computationally complex but highly precise algorithm has been selected for integration into real-time harmonic analysis systems. Due to its complexity it owes its suitability only in offline harmonic analysis system. We have proposed a scheme to realize this algorithm in a manner so that it meets real-time constraints. We have partitioned the algorithm using a Hardware/software (HW/SW) Co-Design methodology to optimize performance and resource utilization. The design fits well onto low cost Field Programmable Gate Arrays (FPGAs) which have moderate resource count. The computational time advantage achieved by our scheme is compared with an embedded software implementation and performance gain has been presented.

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Development of a Mathematical Model of a Brushless Direct Current Motor Based on the Finit Element Method to Optimize Motor's Geometry

Development of a Mathematical Model of a Brushless Direct Cu...

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International Ural conference on Measurements (UralCon)

作者： S. A. Gandzha S. D. M. Janabat D. S. Gandzha Department of Electronic Computing Machines South Ural Stat University Chelyabinsk Russia

ISBN: (数字)9798350386028

ISBN: (纸本)9798350386035

Brushless direct current motors are a class of electric machines that is dynamically developing. One of the directions of this development is related to the optimization of the geometry of the magnetic system, which provides high mass-energy performance. The existing mathematical models for optimization calculations based on the method of equivalent substitution schemes do not meet the requirements for the accuracy of determining the basic parameters. This reduces the quality of optimal design and slows down the development of electric drives. The purpose of the study: to develop a mathematical model that, on the one hand, would be simple, on the other hand, would have sufficient accuracy in determining the main energy parameters. Methods: the finite element method was chosen to build a mathematical model, but the number of elements into which the transverse geometry is divided is limited in advance. The model is parameterized and allows you to calculate any geometry. This approach allows you to create a simple and accurate model for optimization. Results: the technique is implemented in software code in the algorithmic Python language. The mathematical model includes 53 algebraic equations. The program takes into account the use of various electrical materials for electrical steel, high-coercive permanent magnets, copper armature windings. The mathematical model takes into account the lateral scattering fluxes of a permanent magnet, grooved scattering and scattering along the crowns of the teeth. Practical significance: the creation of a mathematical model with a limited number of elements is a new approach in electrical engineering. It allows you to make optimization calculations more accurate, thereby improving the mass-energy characteristics. This approach can be recommended for optimizing thermal conditions and aerodynamic calculations of electric machines. The proposed methodology will improve the design quality of brushless direct current motors and electric

关键词： Geometry Magnetic flux Accuracy Brushless DC motors Windings software algorithms Scattering Mathematical models Finite element analysis optimization

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optimization of custom MOS circuits by transistor sizing 96

Optimization of custom MOS circuits by transistor sizing

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Proceedings of the 1996 IEEE/ACM international conference on Computer-aided design

作者： Andrew R. Conn Paula K. Coulman Ruud A. Haring Gregory L. Morrill Chandu Visweswariah IBM T. J. Watson Research Center and IBM Microelectronics Division Yorktown Heights NY Austin TX and Burlington VT

ISBN: (纸本)9780818675973

optimization of a circuit by transistor sizing is often a slow, tedious and iterative manual process which relies on designer intuition. Circuit simulation is carried out in the inner loop of this tuning procedure. Automating the transistor sizing process is an important step towards being able to rapidly design high-performance, custom circuits. JiffyTune is a new circuit optimization tool that automates the tuning task. Delay, rise/fall time, area and power targets are accommodated. Each (weighted) target can be either a constraint or an objective function. Minimax optimization is supported. Transistors can be ratioed and similar structures grouped to ensure regular layouts. Bounds on transistor widths are supported. JiffyTune uses LANCELOT, a large-scale nonlinear optimization package with an augmented Lagrangian formulation. Simple bounds are handled explicitly and trust region methods are applied to minimize a composite objective function. In the inner loop of the optimization, the fast circuit simulator SPECS is used to evaluate the circuit. SPECS is unique in its ability to efficiently provide time-domain sensitivities, thereby enabling gradient-based optimization. Both the adjoint and direct methods of sensitivity computation have been implemented in SPECS. To assist the user, interfaces in the Cadence and SLED design systems have been constructed. These interfaces automate the specification of the optimization task, the running of the optimizer and the back-annotation of the results on to the circuit schematic. JiffyTune has been used to tune over 100 circuits for a custom, high-performance microprocessor that makes use of dynamic logic circuits. Circuits with over 250 tunable transistors have been successfully optimized. Automatic circuit tuning has been found to facilitate design re-use. The designers' focus shifts from solving the optimization problem to specifying it correctly and completely. This paper describes the algorithms of JiffyTune, the environ

关键词： Circuits

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Genetic algorithm-based power transmission expansion planning

Genetic algorithm-based power transmission expansion plannin...

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IEEE International conference on Electronics, Circuits and Systems (ICECS)

作者： A.R. Abdelaziz Electrical Enginering Deparixnent Alexandria University Egypt

ISBN: (纸本)0780365429

Large-scale combinatorial problems such as the network expansion problem present an amazingly high number of alternative configurations with practically the same investment, but with substantially different structures (configurations obtained with different sets of circuit/transformer additions). This paper presents a development of a genetic algorithm (GA) and its application to a least-cost and reliable transmission expansion-planning (TEP) problem. TEP problem is concerned with a highly constrained nonlinear dynamic optimization problem that can only be fully solved by complete enumeration, a process that is computationally impossible in a real-world TEP problem. In this paper, a GA incorporating a stochastic reproduction technique and an artificial initial population scheme are developed to provide a faster search mechanism. The objective is to optimize the system adequacy (cost, and reliability). The proposed genetic string represents the number of reinforcement ways, which is limited to a certain ways for each line of the system, subjected in total to a prespecified maximum number of reinforcements as well as the project budget. Excellent performance is reported in the test results.

关键词： Power transmission Genetic algorithms Biological cells Costs Genetic mutations Large-scale systems Stochastic processes Power transmission lines optimization methods Cells (biology)

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Particle Swarm Optimized Unscented Particle Filter for Target Tracking

Particle Swarm Optimized Unscented Particle Filter for Targe...

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Congress on Image and Signal Processing, CISP

作者： Shuying Yang Qin Ma Wenjuan Huang Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Key Laboratory of Computer Vision and System Ministry of Education Tianjin University of Technology Tianjin China

In this paper, a novel particle swarm optimized (PSO) unscented particle filter (PSO-UPF) algorithm is proposed for target tracking. Unscented particle filter (UPF) can obtain the better sequential importance sampling than the traditional PF algorithm. Then we use PSO to optimize the state equation of UPF. So that the particle set can tend to the high likelihood region before the weights updated, thereby the impoverishment of particles can be overcome. While, the optimization process makes the particles which far away from the true state tend to the region where the true state has a greater probability of emergence, it can enhance the effect of each particle. Experiment results show that our modified particle filter algorithm uses fewer particles than the general particle filters and its performance outperforms them. And the accuracy of video tracking is improved.

关键词： Particle swarm optimization Particle filters Target tracking Signal processing algorithms Educational technology Monte Carlo methods nonlinear dynamical systems Laboratories Computer vision Equations

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A VERSION OF ISOMAP WITH EXPLICIT MAPPING

A VERSION OF ISOMAP WITH EXPLICIT MAPPING

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2006 International conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)

作者： CHUN-GUANG LI JUN GUO GUANG CHEN XIANG-FEI NIE ZHEN YANG Pattern Recognition and Intelligent System Lab School of Information Engineering Beijing University of Posts and Telecommunications Beijing 100876 China

Recently several manifold learning algorithms have been presented for nonlinear dimensionality reduction. Isomap is one of them. However, Isomap suffers from a deficiency that it does not give an explicit mapping function, which is from high dimensional space to low dimensional target space. In this paper, a version of Isomap with explicit mapping, called E-Isomap, is proposed. In E-Isomap, the geodesic distance matrix is fed into a cost function and then Iterative Majorization is adopted to solve an optimization problem for obtaining both the low dimensional configuration and the nonlinear mapping. Owing to the existence of explicit mapping, this version of Isomap can be more easily used in pattern recognition than the original ones. The experiments on two benchmark data sets are given to demonstrate the performance of the presented method.

关键词： nonlinear Dimensionality Reduction Manifold Learning Isomap Geodesic Distance E-Isomap

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Linearized Data Center Workload and Cooling Management

arXiv

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arXiv 2023年

作者： Rostami, Somayye Down, Douglas G. Karakostas, George The Department of Computing and Software McMaster Univercity HamiltonON Canada

With the current high levels of energy consumption of data centers, reducing power consumption by even a small percentage is beneficial. We propose a framework for thermal-aware workload distribution in a data center to reduce cooling power consumption. The framework includes linearization of the general optimization problem and proposing a heuristic to approximate the solution for the resulting Integer Linear Programming (ILP) problems. We first define a general nonlinear power optimization problem including several cooling parameters, heat recirculation effects, and constraints on server temperatures. We propose to study a linearized version of the problem, which is easier to analyze. As an energy saving scenario and as a proof of concept for our approach, we also consider the possibility that the red-line temperature for idle servers is higher than that for busy servers. For the resulting ILP problem, we propose a heuristic for intelligent rounding of the fractional solution. Through numerical simulations, we compare our heuristics with two baseline algorithms. We also evaluate the performance of the solution of the linearized system on the original system. The results show that the proposed approach can reduce the cooling power consumption by more than 30 percent compared to the case of continuous utilizations and a single red-line temperature. © 2023, CC BY.

关键词： Integer programming

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SmOOD: Smoothness-based Out-of-Distribution Detection Approach for Surrogate Neural Networks in Aircraft Design 22

SmOOD: Smoothness-based Out-of-Distribution Detection Approa...

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Proceedings of the 37th IEEE/ACM International conference on Automated software Engineering

作者： Houssem Ben Braiek Ali Tfaily Foutse Khomh Thomas Reid Ciro Guida École Polytechnique de Montréal Canada Bombardier Aerospace Inc. Canada Sycodal Inc. Canada

ISBN: (纸本)9781450394758

Aircraft industry is constantly striving for more efficient design optimization methods in terms of human efforts, computation time, and resources consumption. Hybrid surrogate optimization maintains high results quality while providing rapid design assessments when both the surrogate model and the switch mechanism for eventually transitioning to the HF model are calibrated properly. Feedforward neural networks (FNNs) can capture highly nonlinear input-output mappings, yielding efficient surrogates for aircraft performance factors. However, FNNs often fail to generalize over the out-of-distribution (OOD) samples, which hinders their adoption in critical aircraft design optimization. Through SmOOD, our smoothness-based out-of-distribution detection approach, we propose to codesign a model-dependent OOD indicator with the optimized FNN surrogate, to produce a trustworthy surrogate model with selective but credible predictions. Unlike conventional uncertainty-grounded methods, SmOOD exploits inherent smoothness properties of the HF simulations to effectively expose OODs through revealing their suspicious sensitivities, thereby avoiding over-confident uncertainty estimates on OOD samples. By using SmOOD, only high-risk OOD inputs are forwarded to the HF model for re-evaluation, leading to more accurate results at a low overhead cost. Three aircraft performance models are investigated. Results show that FNN-based surrogates outperform their Gaussian Process counterparts in terms of predictive performance. Moreover, SmOOD does cover averagely of actual OODs on all the study cases. When SmOOD plus FNN surrogates are deployed in hybrid surrogate optimization settings, they result in a decrease error rate of and a computational speed up rate of 58.36 ×, respectively.

关键词： Neural network aircraft design optimization out-of-distribution detection surrogate modeling

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