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IEEE International Conference on Industrial Technology (ICIT)

作者： Jianxiao Zheng Jixiang Tan Wenhao Li Fuchao Song School of Mechanical and Electrical Engineering Xi'an University of Architecture and Technology Xi'an China

ISBN: (数字)9798331521950

ISBN: (纸本)9798331521967

To efficiently plan the coverage path of UAVs during the visual inspection of building facades, the task is divided into two parts: viewpoint planning and path planning. First, a K-medoid clustering method is proposed to generate the initial set of candidate viewpoints based on the point cloud model of the building facade. A greedy optimization algorithm is then employed to select the optimal subset of viewpoints, addressing the viewpoint planning problem. Second, an incomplete graph is constructed, and the objective function is defined for path planning, which is solved using the Gaussian Zenith-Ant Colony Optimization (GZ-ACO) algorithm. The path length and turning angles are considered optimization objectives. Simulation results demonstrate that the proposed viewpoint planning method reduces the number of viewpoints by 66.67% and 98.67%, respectively, compared to the iterative random sampling method and the displacement method. Furthermore, the GZ-ACO algorithm outperforms the traditional ant colony algorithm, achieving a 19.97% reduction in the objective function value and a 21.76% decrease in the average steering angle. The validity and feasibility of the proposed method are thus verified.

关键词： Visualization Simulation Buildings Clustering algorithms Inspection linear programming Autonomous aerial vehicles Path planning Planning Optimization

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Design of Merging and Classifying System of Digital Chinese Teaching Resources Based on Fuzzy Clustering Algorithm

Design of Merging and Classifying System of Digital Chinese ...

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Digital Analysis and Processing, Intelligent Computation (DAPIC), International Conference on

作者： Junyi Li School of Culture and Health Communication Tianjin University of Traditional Chinese Medicine Tianjin China

ISBN: (数字)9798331536169

ISBN: (纸本)9798331536176

Digitalization, networking and intelligent management of Chinese language teaching resources are of great significance for improving teaching efficiency and promoting cultural exchange. However, in the face of massive Chinese language teaching resources, the traditional classification method has been difficult to adapt to the characteristics of huge resources, diverse types and complex content. Because of its unique advantages in dealing with uncertainty and fuzziness, fuzzy clustering algorithm is applied to the design of this system to realize the intelligent and automatic classification of Chinese language teaching resources. The system architecture design includes four core parts: front-end user interface layer, back-end service layer, data processing layer and database storage layer. It adopts modular design, supports front-end separation mode and interacts through API. The functional modules of the system are divided into data preprocessing module, fuzzy clustering algorithm module, result display module, user management module and system maintenance module to ensure the maintainability, expansibility and efficiency of the system. In this study, the fuzzy C-means (FCM) algorithm is selected as the core algorithm, and the optimal clustering of data points and the center of each cluster are found by iteratively optimizing the objective function. The system test and evaluation show that FCM algorithm has achieved good clustering effect in the merging and classification of digital Chinese teaching resources, with contour coefficient of 0.75 and ARI index of 0.82, which shows high accuracy. The performance test results also show that the system has good response speed and stability, the throughput reaches 1050 requests per second, and the average utilization rate of CPU and memory is 57.3% and 68.9% respectively, which meets the requirements of high concurrency and big data processing. This system has high practicability and value in practical application, which ca

关键词： Uncertainty Education Merging Stability criteria Clustering algorithms User interfaces Throughput linear programming Classification algorithms Maintenance

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MONAS-ESNN: Multi-Objective Neural Architecture Search for Efficient Spiking Neural Networks

MONAS-ESNN: Multi-Objective Neural Architecture Search for E...

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IEEE Workshop on Applications of Computer Vision (WACV)

作者： Esmat Ghasemi Saghand Susana K. Lai-Yuen University of South Florida

ISBN: (数字)9798331510831

ISBN: (纸本)9798331510848

Spiking Neural Networks (SNNs) have emerged as a compelling alternative to traditional Artificial Neural Networks (ANNs) due to their energy efficiency and biological plausibility. However, current SNN models often rely on ANN architectures that may not fully exploit the unique properties of SNNs. Neural Architecture Search (NAS) approaches have been shown to automate the identification of suitable architectures for various applications. Nevertheless, very few works have been presented on NAS for SNNs and particularly for identifying architectures that achieve high accuracy while capitalizing on the energy efficiency property of SNNs. In this paper, we present a Multi-Objective Neural Architecture Search for Efficient SNNs (MONAS-ESNN) approach that utilizes a training-free NAS to discover SNN architectures that optimize both accuracy and energy efficiency. The proposed MONAS-ESNN uses the NSGA-II evolutionary algorithm to optimize both objective functions while leveraging the unique temporal dynamics of SNNs. We also introduce a new Adjusted Sparsity-Aware Hamming Distance (ASAHD) that enhances the evaluation of potential architectures by representing diverse spike activation patterns for different types of spiking neurons. Experimental results on CIFAR-10, CIFAR-100, and Tiny-ImageNet-200 datasets demonstrate that MONAS-ESNN identifies SNN architectures that have higher accuracy and are more efficient, as measured by the number of generated spikes, than existing methods. Therefore, the proposed MONAS-ESNN can automate the search and discovery of SNN architectures with higher accuracy, fewer generated spikes, and faster convergence paving the way for more energy-efficient neural networks.

关键词： Training Measurement Accuracy Neurons Computer architecture Spiking neural networks linear programming Energy efficiency Neural architecture search Hamming distances

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All coefficients interval number linear programming model with equality constrains and its solution method

All coefficients interval number linear programming model wi...

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Chinese Control Conference (CCC)

作者： Yucheng Wan Xinbin Liu Fuhong Wang Department of Air-Material Management Air Force Logistics College Xuzhou China

All coefficients interval number linear programming model with equality constrains and its solution method are discussed in this paper. A new solution method is presented to solve the all coefficients interval number linear programming model containing not only inequality constrains but also strict equality constrains. The characteristic of the method is via the optimal value of deterministic linear programming to get the equality constrains to satisfy the decision maker's preference. With the method, the decision maker can obtain a satisfactory solution. Finally, the application value of the method is given by a portfolio investment case. And the result shows that the method is scientific and feasible.

关键词： linear programming Investment programming Mathematical model Portfolios Uncertainty Optimization

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Exact conic programming reformulations of two-stage adjustable robust linear programs with new quadratic decision rules

arXiv

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arXiv 2020年

作者： Woolnough, D. Jeyakumar, V. Li, G. Department of Applied Mathematics UNSW SydneyNSW Australia

In this paper we introduce a new parameterized Quadratic Decision Rule (QDR), a generalisation of the commonly employed Affine Decision Rule (ADR), for two-stage linear adjustable robust optimization problems with ellipsoidal uncertainty and show that (affinely parameterized) linear adjustable robust optimization problems with QDRs are numerically tractable by presenting exact semi-definite program (SDP) and second order cone program (SOCP) reformulations. Under these QDRs, we also establish that exact conic program reformulations also hold for two-stage linear ARO problems, containing also adjustable variables in their objective functions. We then show via numerical experiments on lot-sizing problems with uncertain demand that adjustable robust linear optimization problems with QDRs improve upon the ADRs in their performance both in the worst-case sense and after simulated realization of the uncertain demand relative to the true *** Codes 90C22 Copyright © 2020, The Authors. All rights reserved.

关键词： linear programming

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Optimized Electromagnetic Parameters of a Six-Phase SPMSM with Fractional-Slot Concentrated Winding for Electric Vehicles

Optimized Electromagnetic Parameters of a Six-Phase SPMSM wi...

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Consumer Technology (ICCT-Pacific), International Conference on

作者： Vuong Dang Quoc Nguyen Gia Minh Thao Thanh Pham Thi Tuyet Trinh Truong Cong Tu Pham Minh Dinh Bui Minh School of Electrical Engineering Hanoi University of Science and Technology Hanoi Vietnam Department of Mechanical Electrical and Electronic Engineering Shimane University Matsue Japan Department of English Hanoi Univeristy of Civil Engineering Hanoi Vietnam

ISBN: (数字)9798331504120

ISBN: (纸本)9798331504137

Permanent magnet synchronous motors (PMSMs) are widely utilized in a variety of applications due to their high efficiency, dependability, and exceptional dynamic performance. The increase in the number of phases of the PMSMs is a crucial step forward in improving the motor's overload and fault tolerance. Moreover, the PMSMs with outer rotor are extensively used in traction applications such as ship propulsion, mining, lifting, etc., due to their large torque density, which increases the ability to produce more torque. In this study, a unique optimal design technique with the goals of reducing material cost and boosting efficiency is proposed for a six-phase surface-mounted PMSM (SPMSM). Initially, an analytical model is developed to calculate main dimensions of a 145kW six-phase SPMSM. Next, an optimization process is presented to define optimal electromagnetic parameters of the proposed motor. Once optimal parameters are defined, a finite element approach is presented to simulate and analyze the electromagnetic parameters of the optimal motor. The obtained results after optimization are compared to the traditional motors After optimization, not only the material cost decreases 8USD and the efficiency increases 0.224 %, which achieve the objective functions, but also other output parameters such as back EMF THD, torque ripple, etc., of the optimal motor find better outcomes when compared to the initial model.

关键词： Analytical models Torque Costs Windings linear programming Finite element analysis Torque measurement Electromagnetics Vehicle dynamics Genetic algorithms

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Multi-Stage Energy Storage Configuration Method Considering the Evolution Path of New Energy Penetration

Multi-Stage Energy Storage Configuration Method Considering ...

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Smart Grid and Green Energy (ICSGGE), International Conference on

作者： Junzhi Chen Jian Wu Wei Wang Yingxue Li Xueting Zhang Jiawei Gong State Grid Jiangxi Electric power Company Economic Research Institute Nanchang Jiangxi China

ISBN: (数字)9798331542139

ISBN: (纸本)9798331542146

Under the impetus of the “dual-carbon” goals, the rapid increase in new energy penetration has imposed higher demands on the flexibility and economy of power systems. Traditional static planning methods struggle to adapt to the dynamic evolution of new energy and the iterative technoeconomics of energy storage. To address this, this paper proposes a multi-stage collaborative planning method for wind-thermalstorage hybrid systems. First, based on the logistic growth model and learning curve, the evolution of new energy penetration under different policy scenarios is quantified. Second, a mixedinteger linear programming model is established to optimize the economy by coordinating the intertemporal coupling of energy storage lifecycle costs, thermal power retrofitting costs, and peakvalley arbitrage revenue. Simulation results from a case study in a large-scale new energy base in Northwest China demonstrate that the proposed multi-stage planning reduces typical daily total costs by 37.89% compared to static planning, while thermal coal costs decrease by 1.16%. This research provides an economically viable decision-making framework for energy storage temporal planning and thermal power transition in high-penetration renewable energy systems.

关键词： Costs Simulation Power system dynamics linear programming Planning Smart grids Iterative methods Optimization Energy storage Logistics

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Coati-Based Optimal Design of a 2-DOF PID Controller for a KY Buck-Boost Converter

Coati-Based Optimal Design of a 2-DOF PID Controller for a K...

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Iranian Conference on Renewable Energy and Distributed Generation (ICREDG)

作者： Hamed Mojarad Hossein Shayeghi Reza Mohajery Energy Management Research Center University of Mohaghegh Ardabili Ardabil Iran

ISBN: (数字)9798331525132

ISBN: (纸本)9798331525149

Renewable energy is increasingly being recognized as a viable solution to the world’ growing energy demands. DC-DC converters, however, can be utilized to address low output voltage of renewable sources requirements. Nonlinearity is one of the main problems with DC-DC converters. This characteristic results in voltage instability, causing nonlinear variations in response to circuit parameter changes. Consequently, the accurate selection of the controller and the proper design of its components are essential. In this paper, a two-degree-of-freedom PID (2-DOFPID) controller is designed using the Coati Optimization Algorithm (COA) for KY buck-boost converter. In order to ensure that the output voltage remains steady regardless of disturbances, the coefficients of the mentioned controller have been optimized using the COA. For minimizing the time-domain indexes of the closed-loop system, the suggested controller coefficients are obtained using the ISTSE index as the objective function. The performance of the 2-DOFPID controller and conventional PID controller was compared using various evaluation indexes under different cases to assess the proposed controller's performance and closed-loop system behavior.

关键词： Renewable energy sources Energy consumption Heuristic algorithms DC-DC power converters linear programming Indexes Closed loop systems Voltage control Time-domain analysis Optimization

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Data Privacy Protection Algorithm for Carrier Communication Nodes in Power Internet of Things Based on Frequent Itemsets

Data Privacy Protection Algorithm for Carrier Communication ...

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Smart Grid and Artificial Intelligence (SGAI), International Conference on

作者： Hua Li Zhengrong Wu Wenqin Chen Jialin Luo Xun Min CHINA SOUTHERN POWER GRID Guangzhou Guangdong China Digital Power Grid Technology (Guangdong) Co. Ltd China Southern Power Grid. Guangzhou Guangdong China Guizhou Grid Company Limited Guiyang Guizhou China

ISBN: (数字)9798331518806

ISBN: (纸本)9798331518813

Because the original data of the carrier communication node of power Internet of Things is non-stationary and nonlinear, its discreteness is large, which is not conducive to feature extraction, which leads to the possibility of data privacy protection and low data security. Therefore, this paper proposes a data privacy protection algorithm based on frequent itemsets for power Internet of Things carrier communication nodes. Through the set rules, the network resources of the power Internet of Things are analyzed, the corresponding itemsets are connected, the residual components are calculated, and the correlation between two adjacent data is extracted by using frequent itemsets. The comprehensive attributes of the data set are obtained, the local information entropy of the communication node data privacy is described, and the data sequence characteristics of the privacy data are extracted, to construct the data privacy protection objective function and realize the data privacy protection algorithm design of the power Internet of Things carrier communication node. The experimental results show that the algorithm in this paper shows a low data information loss rate on multiple data sets, which can effectively reduce data information loss and protect the privacy and security of data. Under both internal and external attacks, the anti-attack performance is over 98%, after privacy processing by this algorithm, privacy leakage can be limited to the maximum extent, and privacy protection performance is excellent.

关键词： Data privacy Privacy Itemsets Data security Power system stability linear programming Stability analysis Smart grids Internet of Things Protection

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Estimating Multi-chirp Parameters using Curvature-guided Langevin Monte Carlo

Estimating Multi-chirp Parameters using Curvature-guided Lan...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Sattwik Basu Debottam Dutta Yu-Lin Wei Romit Roy Choudhury University of Illinois at Urbana-Champaign

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

This paper considers the problem of estimating chirp parameters from a noisy mixture of chirps. While a rich body of work exists in this area, challenges remain when extending these techniques to chirps of higher order polynomials. We formulate this as a non-convex optimization problem and propose a modified Langevin Monte Carlo (LMC) sampler that exploits the average curvature of the objective function to reliably find the minimizer. Results show that our Curvature-guided LMC (CG-LMC) algorithm is robust and succeeds even in low SNR regimes, making it viable for practical applications.

关键词： Monte Carlo methods Chirp Signal processing algorithms linear programming Polynomials Reliability Noise measurement Speech processing Optimization Signal to noise ratio

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