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generic algorithm to calculate Jacobian matrix used for ladder network parameters identification and winding fault diagnosis

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IET GENERATION TRANSMISSION & DISTRIBUTION 2019年第15期13卷 3370-3377页

作者： Ren, Fuqiang Ji, Shengchang Zhu, Lingyu Zhang, Fan Liu, Yong Xi An Jiao Tong Univ State Key Lab Elect Insulat & Power Equipment Xian 710049 Shaanxi Peoples R China Zhongyuan Univ Technol Sch Elect Informat Zhengzhou 450007 Henan Peoples R China

Ladder network parameters identification of transformer winding based on frequency response analysis data is crucial to winding fault diagnosis. In the authors' previous study, the Gauss-Newton iteration algorithm (GNIA) had been proposed to efficiently identify the network parameters. The core in GNIA is the Jacobian matrix, composed of derivative of frequency response function (FRF) to network components. This study proposes a generic algorithm to calculate this Jacobian matrix. Two key problems concerning the algorithm are solved elaborately. The first problem is the method for derivative calculation toward an arbitrary FRF based on adjoint network method (ANM). The other issue is the mathematical model construction of double ladder network and its adjoint network toward different FRFs to obtain all network branch voltages and currents, which are required in the derivative calculation by ANM. This generic algorithm can efficiently and effectively calculate the Jacobian matrix, which can be applied on ladder network parameters identification and winding fault diagnosis.

关键词： ladder networks Jacobian matrices power transformers frequency response Newton method fault diagnosis transformer windings parameter estimation iterative methods generic algorithm Jacobian matrix ladder network parameters identification winding fault diagnosis frequency response analysis data Gauss-Newton iteration algorithm frequency response function derivative calculation adjoint network method double ladder network network branch voltages currents

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EXPERIMENTAL COMPARISON OF TWO FEATURE SELECTION METHODS BASED ON generic algorithm 16

EXPERIMENTAL COMPARISON OF TWO FEATURE SELECTION METHODS BAS...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Liu, Bo Zhai, Jun-Hai Liu, Hai-Bo Hebei Univ Coll Comp Sci & Technol Baoding 071002 Hebei Peoples R China Hebei Univ Coll Math & Informat Sci Key Lab Machine Learning & Computat Intelligence Baoding 071002 Hebei Peoples R China Zhejiang Normal Univ Coll Math Phys & Informat Engn Jinhua 321004 Peoples R China

ISBN: (纸本)9781538604083

Feature selection is an important preprocessing in data mining, it aims to reduce the computational complexity of learning algorithm, and to improve the performance of data mining algorithms by removing irrelevant and redundant features. In the framework of discrete-valued feature selection, this paper experimentally compares two feature selection methods which are based on generic algorithm. The former uses relative classification information entropy to measure the significance of the candidate feature subsets, while the later uses inconsistency ratio to evaluate feature subsets. Both methods use genetic algorithm to search the optimal feature subset, we find by experimental comparisons that the former outperforms the latter.

关键词： Data mining feature selection information entropy inconsistency ratio generic algorithm

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Optimum design of formable CFRP sheets by generic algorithm and FE analysis by homogenization of multilayered structure with macroscopic anisotropy

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INTERNATIONAL JOURNAL OF MATERIAL FORMING 2016年第5期9卷 697-703页

作者： Takahashi, Yuma Uriya, Yu Yanagimoto, Jun Univ Tokyo Grad Sch Engn Tokyo Japan Univ Tokyo Inst Ind Sci Tokyo Japan

A new method for designing carbon-fiber-reinforced plastic (CFRP) sheets with a suitable ply structure for stamping is proposed. This method combines a generic algorithm with a three-dimensional finite element method (FEM) to reproduce a layered structure by homogenizing the fiber structure with elastic-plastic anisotropy of each layer. The maximum strain is used as a fracture index to evaluate the severity of sheet deformation under stamping. The ply structure of the CFRP is optimized for elliptic cup drawing, and the optimized ply structure is validated experimentally. Through the experimental validation, it is proven that the proposed method gives acceptable results for the optimization of the ply structure of thermosetting CFRP sheets for cold/warm stamping.

关键词： CFRP Sheet forming FEM Structure optimization generic algorithm

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A Novel generic algorithm for Robust Physiological Signal Classification 14th

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14th Mediterranean Conference on Medical and Biological Engineering and Computing (MEDICON)

作者： Mahdiani, S. Vanhala, J. Viik, J. Tampere Univ Technol Dept Elect & Commun Engn FIN-33101 Tampere Finland

ISBN: (纸本)9783319327037;9783319327013

The last decade has witnessed a significant interest in widespread usage of wearable monitoring devices that could provide continuous measurements of physiological parameters. The design and development of these devices has attracted lots of attention in industry and scientific associations. Advanced and miniaturized electronics with signal acquisition technologies provide a possibility for designing only one device for several physiological measurement purposes. Therefore for designing such an automatic system, a simple generic algorithm for physiological signal classification is required. In this paper, a novel generic algorithm for robust physiological signal classification is presented. The architecture of the proposed system includes preprocessing, feature extraction and a neural network method. Our generic algorithm was able to distinguish different physiological signals such as electrocardiogram (ECG), respiratory signal, seismocardiogram (SCG), electromyogram (EMG) and photoplethysmogram with 100 % accuracy. The algorithm was also evaluated by noisy signals with 10 and 20 dB levels of added noise and the same results were achieved. The algorithm could be implemented in healthcare monitoring systems and it can provide the possibility of monitoring various physiological signals with only one device.

关键词： Classifier physiological signals neural network generic algorithm wearable devices

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Timetabling Problems and the Effort Toward generic algorithms: A Comprehensive Survey

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IEEE ACCESS 2024年 12卷 143854-143868页

作者： Gusti Agung Premananda, I. Tjahyanto, Aris Muklason, Ahmad Inst Teknol Sepuluh Nopember ITS Dept Informat Syst Kampus ITS Sukolilo Surabaya Surabaya 60111 East Java Indonesia

The timetabling problem, a well-known NP-Hard optimization challenge, spans multiple domains such as education, healthcare, sports, and transportation. Due to its computational complexity, heuristic methods have become the dominant method for solving these problems. However, a lack of consistent comparisons across studies has led to difficulties in evaluating the effectiveness of these algorithms. This paper provides a comprehensive survey of 64 studies published between 2012 and 2022, focusing on timetabling algorithms and their performance on established benchmarks. The algorithms are categorized into metaheuristics, hybrid metaheuristics, and hyper-heuristics, with their efficacy evaluated across six major benchmarks. The analysis highlights the superiority of single-solution-based metaheuristics, with Simulated Annealing emerging as the most effective algorithm, particularly for educational timetabling problems. Additionally, the challenge of developing generic algorithms capable of performing across different timetabling problem domains is addressed. Despite advances in the field, cross-domain adaptability remains a critical area for further exploration. This survey serves as a guide for future research, providing insights into algorithmic strategies that can enhance the efficiency and generalizability of solutions for timetabling problems.

关键词： Benchmark testing Metaheuristics Simulated annealing Surveys Classification algorithms Heuristic algorithms Schedules Genetic algorithms Timetabling heuristic generic algorithm survey

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Ammonia storage and slip under steady and transient state in close-coupled SCR

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Journal of Environmental Sciences 2024年第4期138卷 470-481页

作者： Shiyu Liu Zhaohuan Zhang Zexian Guo Boyuan Wang Buyu Wang Xiao Ma Shijin Shuai State Key Laboratory of Automotive Safety and Energy Tsinghua UniversityBeijing 100084China Institute for Aero Engine Tsinghua UniversityBeijing 100084China

The close-coupled selective catalytic reduction(cc-SCR)catalyst is an effective technology to reduce tailpipe NOx emission during cold *** paper investigated the optimal ammonia storage under steady and transient state in the *** study showed that a trade-off between NOx conversion efficiency and ammonia slip is observed on the pareto solutions under steady state,and the optimal ammonia storage is calculated with ammonia slip less than 10μL/L based on the ChinaⅥemission *** rapid temperature increase will lead to severe ammonia slip in the transient test cycle.A simplified 0-D calculation method on ammonia slip under transient state is proposed based on kinetic model of ammonia adsorption and *** addition,the effect of ammonia storage,catalyst temperature and temperature increasing rate on ammonia slip are *** optimal ammonia storage is calculated with maximum ammonia slip less than 100μL/L according to the oxidation efficiency of ammonia slip catalyst(ASC)downstream *** was found that the optimal ammonia storage under transient state is much lower than that under steady state in cc-SCR at lower temperature,and a phase diagram is established to analyze the influence of temperature and temperature increasing rate on optimal ammonia storage.

关键词： Close-coupled SCR Ammonia storage and slip Steady and transient state generic algorithm

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A genetic-based random ensemble forest learning for cloud-based automotive data transformation in internet of vehicle

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ALEXANDRIA ENGINEERING JOURNAL 2025年 120卷 74-86页

作者： Qureshi, Salwa Umar Souri, Alireza Inanc, Nihat Lansky, Jan Hosseinzadeh, Mehdi Halic Univ Fac Engn Dept Software Engn TR-34060 Istanbul Turkiye Halic Univ Fac Engn Dept Elect & Elect Engn TR-34060 Istanbul Turkiye Univ Finance & Adm Fac Econ Studies Dept Comp Sci & Math Prague 10100 Czech Republic Duy Tan Univ Sch Comp Sci Da Nang Vietnam Chulalongkorn Univ Fac Dent Ctr Excellence Genom & Precis Dent Dept Physiol Bangkok 10330 Thailand

The Internet of Vehicles (IoV) is a constantly changing field, and the fast convergence of automotive technology and connectivity has brought about a new era marked by enormous cybersecurity risks. A crucial component of the inquiry is a thorough examination of the IoV infrastructure's vulnerabilities, which highlights potential sources of compromise and places where strong cybersecurity measures are required for data transformations in cloud-edge computing. Additionally, the Controller Area Network (CAN) and the Electronic Control Units (ECUs) are critical points in automotive networking to connect user data from smart applications to electric vehicles. Therefore, finding a safe automotive data transformation approach for incorporating Connected and Autonomous Vehicles (CAVs) and investigating particular cybersecurity issues is a critical and key challenge in the IoV ecosystem. To ensure the safe development of the IoV landscape, the research introduces two innovative genetic algorithms, Genetic algorithm Random Forest (GA-RF) and Genetic algorithm Ensemble Bagged Trees (GA-EBT), to improve the identification of cyber threats in the IoV context. The simulation results demonstrate that the proposed hybrid algorithm achieves exceptional performance, attaining a high accuracy rate of 99.92 %, the lowest mean absolute error of 0.0028, and the highest precision, recall, and F1 measures near to 100 %. These results are especially noteworthy on real automotive data transformation datasets. These results highlight the significance of the suggested strategy for defending IoV systems from suspicious threats.

关键词： Internet of vehicles Cloud-edge computing Automotive transformation Electronic control units Controller area network Cybersecurity generic algorithm

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Investigation of combined process characteristics in hydrogen production and liquefaction by PEM electrolyzer and Claude cycle with liquid nitrogen precooling under varying pressure using genetic algorithm

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ENERGY CONVERSION AND MANAGEMENT 2025年 325卷

作者： Kim, Jungwoog Choi, Minsoo Jung, Wongwan Chang, Daejun Korea Adv Inst Sci & Technol KAIST Dept Mech Engn 291 Daehak Ro Daejeon 34141 South Korea Dong A Univ Dept Naval Architecture & Ocean Engn 37 Nakdong Daero 550 Beon Gil Busan 49315 South Korea

The potential of green hydrogen supply chains as a sustainable energy solution for addressing the climate crisis has garnered increasing attention. However, within the supply chain, the production and liquefaction facilities are interconnected;yet their systems have been developed independently. This study examines the integrated process characteristics of green hydrogen production and liquefaction systems, with a particular focus on pressure, and it proposes optimal operating pressures. A proton exchange membrane electrolyzer, which offers the benefit of supplying high-pressure hydrogen without the necessity for separate mechanical compression, was utilized in the production process. The produced hydrogen was liquefied through the hydrogen Claude cycle with liquid nitrogen precooling. The case studies provided the SEC at fixed pressures of 10, 30, 50, and 70 bar to understand characteristics of systems, as well as the case where pressure was an optimization variable. The optimal pressures were 27.57 and 27.29 bar, with the estimated Specific Energy Consumption (SEC) being 49.90 and 62.77 kWh/kg-H2 at 0.1 and 1 A/cm2, respectively. The SEC for the liquefaction process was estimated to be 8.10 kWh/kg-H2. As the pressure increased from 10 to 70 bar, the SEC for the production increased by 0.76 and 1.84 kWh/kg-H2 at 0.1 and 1 A/cm2, respectively, while that of the liquefaction decreased by 1.24 kWh/kg-H2. At the optimized pressures, the exergy efficiency of the integrated system was 69.35 % and 55.56 %, at 0.1 and 1 A/cm2, respectively.

关键词： Hydrogen production Hydrogen liquefaction Process simulation Integrated design generic algorithm Energy analysis Exergy analysis

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Enhanced Real Coded Genetic algorithm for Optimal DG Placement in a Radial Distribution System

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JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY 2023年第4期18卷 2581-2597页

作者： Almabsout, Emad Ali El-Sehiemy, Ragab A. Bayoumi, Ahmed Saeed Abdelrazek Higher Inst Engn Technol Benghazi Benghazi Libya Coll Elect & Elect Technol Benghazi Libya Kafrelsheikh Univ Fac Engn Elect Engn Dept Kafr Al Sheikh Egypt Kafrelsheikh Univ Fac Engn Dept Engn Phys & Math Kafr Al Sheikh Egypt

Active and reactive power flows in distribution systems have a significant impact on the efficiency of power distribution systems. The optimal placement of distributed power generation units is the most popular approach for improving power quality, voltage profile and reducing the total power loss of distribution systems. This paper presents an enhanced algorithm to handle the optimal capacity and placement of multi-distributed generation units in radial distribution networks (RDN). In this light, a proposed local search scheme has been integrated into the real coded genetic algorithm by the proposed algorithm to exploit its advantages reduce the search time required for finding the optimal placement and size of DG in RDN. The proposed genetic algorithm evaluates population solutions by minimizing total real power losses in a system and improve the voltage profile. To investigate the performance of the proposed algorithm, two common radial systems have been used, namely, IEEE 33-bus, 69-bus networks. The experimental results demonstrate that the implemented enhanced genetic algorithm can find the best solutions to the problem effectively reducing the power loss and improving the voltage profile and outperform other current literature algorithms. Moreover, the energy losses cost, and total voltage deviation have been investigated. Significant improvement in the power losses and voltage profile enhancement with the increasing of distributed generation units has been reached. The feasibility of the method for practical application has been investigated and validated with preserving the constraints and operational restrictions.

关键词： generic algorithm Local search Distribution systems Radial distribution networks Power loss Allocation of DGs

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SecuPath: A Secure and Privacy-Preserving Multiparty Path Planning Framework in UAV Applications 29th

SecuPath: A Secure and Privacy-Preserving Multiparty Path Pl...

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29th Australasian Conference on Information Security and Privacy (ACISP)

作者： Shen, Yanjun Liu, Joseph Yuan, Xingliang Sun, Shifeng Cui, Hui Monash Univ Melbourne Vic 3800 Australia CSIRO Data61 Melbourne Vic 3008 Australia Shanghai Jiao Tong Univ Shanghai Peoples R China

ISBN: (纸本)9789819751006;9789819751013

With the increasing deployment and growing popularisation of autonomous unmanned aerial vehicle (UAVs), such as surveillance, package delivery, and environmental monitoring, the need for efficient and secure UAV path planning algorithms has gained a high level of attention and importance. However, existing path planning methodologies often overlook strict security measures, resulting in sensitive information, from both civilian and even military use scenarios, vulnerable to security attacks. Moreover, the involvement of multiple parties, each with its own set of sensitive information, raises concerns regarding data privacy and security. To bridge this gap, this paper presents a novel approach that employs Multi-Party Secure Computation (SMPC) techniques atop generic path planning algorithms to address these security and privacy challenges. We propose SecuPath, a secure framework that leverages cryptographic protocols for secure communication and computation, enabling multiple entities to jointly compute optimal drone paths without revealing their private inputs to any party. By integrating this privacy-preserving layer onto generic drone path planning algorithms, we ensure the optimality of the planning process while significantly elevating the privacy and security standards of UAV path planning operations. This framework not only preserves the confidentiality and privacy of sensitive data, but also fosters collaboration in scenarios where data sharing is essential, such as in urban airspace management or disaster response. Moreover, we analyse the communication and computation overhead introduced by the SMPC and demonstrate the protocol remains practical and efficient. This research contributes to the growing field of work addressing privacy concerns in drone applications and provides a foundation for the development of secure and collaborative UAV systems. The integration of SMPC techniques with generic drone path planning algorithms sets the groundwork for privac

关键词： UAV Path Planning Secure Multi-Party Computation Privacy Preserving generic algorithm

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