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A DVL calibration method based on a two-layer calibration model during combined navigation

MEASUREMENT 2025年 250卷

作者： Hou, Yudong Wang, Qing Wu, Jianbo Li, Jiangxiong Ke, Yinglin Zhejiang Univ State Key Lab Fluid Power Components & Mechatron S Hangzhou 310027 Peoples R China Zhejiang Univ Sch Mech Engn Key Lab Adv Mfg Technol Zhejiang Prov Hangzhou 310027 Peoples R China Hangzhou AME Aerosp Mfg Equipment Co Ltd Hangzhou 311200 Peoples R China Zhejiang Univ Hangzhou 310027 Peoples R China

During the integrated navigation of underwater strapdown inertial navigation systems (SINS) with doppler velocity logs (DVL), the DVL's scale factor error and its mounting misalignment with respect to the inertial navigation system significantly affect positioning accuracy. Conventional calibration methods typically depend on long-term filter estimates or specific maneuvers, and are highly sensitive to parameters such as convergence parameters. To address these challenges, this paper proposes a two-layer calibration model that incorporates singular value decomposition (SVD) within the iterative framework of the harmony search (HS) algorithm. By leveraging the global search capability of the HS algorithm and the computational stability of SVD, and incorporating both velocity and position data, the method accurately estimates the DVL's scale factor and mounting misalignment through iterative optimization. Simulation and experimental results demonstrate that this approach significantly improves both computational efficiency and stability compared with traditional methods and other intelligent optimization algorithms.

关键词： Integrated navigation Calibration harmony search algorithm SVD

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Optimal coordination of overcurrent relays in microgrids using meta-heuristic algorithms NSGA-II and harmony search

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SUSTAINABLE COMPUTING-INFORMATICS & SYSTEMS 2024年 43卷

作者： Abdi, Gholamreza Jirdehi, Mehdi Ahmadi Mehrjerdi, Hasan Kermanshah Univ Technol Dept Elect Engn Kermanshah Iran George Washington Univ Dept Elect & Comp Engn Washington DC USA

The emergence of distributed generation from renewable energy sources has led to the adoption microgrids as an alternative energy solution. However, implementing microgrids presents challenges, particularly in coordinating relay protection, due to factors like distributed generation sources, bidirectional power flow, variable shortcircuit levels, and changes in network behavior. Although overcurrent relays (OCR) are frequently utilized in microgrid protection, a more adaptable strategy is needed as grid architectures transition from radial to nonradial. This paper proposes a new method to optimize the coordination of OCRs in microgrids by adjusting parameters like time multiplier settings (TMS), plug settings (PS), and characteristic curve selection. The study utilizes meta-heuristic techniques such as the harmony search algorithm (HSA) and the non-dominated sorting genetic algorithm-II (NSAGA-II) for optimal coordination. Simulations on a microgrid and bus test system demonstrate the effectiveness of the proposed approach in enhancing protection indicators like sensitivity, speed, selectivity, and reliability in microgrid operations. The results also indicate that the computation time of HSA is less than NSGA-II, but with an increase in DGs capacity, there is a continuous tendency to reduce the relay operation time.

关键词： harmony search algorithm Microgrid NSGA-II algorithm Overcurrent relay Optimal coordination

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The restaurant delivery problem with uncertain cooking time and travel time

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COMPUTERS & INDUSTRIAL ENGINEERING 2024年 190卷

作者： Xue, Guiqin Wang, Zheng Wang, Yong Xian Univ Sci & Technol Sch Management Xian 710054 Peoples R China Dalian Maritime Univ Sch Maritime Econ & Management Dalian 116000 Peoples R China Chongqing Jiaotong Univ Sch Econ & Management Chongqing 400074 Peoples R China

Eliminating delays under uncertain delivery conditions presents a formidable challenge for meal delivery platforms. Nevertheless, by implementing effective measures, these platforms can successfully mitigate the impacts of uncertainties on delays. This paper introduces a scenario -based chance -constrained programming model tailored for meal delivery services with uncertain cooking time and travel time, ensuring a more accurate representation of real -world scenarios. The objective is to minimize the delivery cost while considering the decision preferences of a platform. To generate high -quality solutions, this work proposes a novel island harmony search algorithm that incorporates several key components, including greedy search, harmony selection, neighborhood reduction, island migration, and scenario -based simulation. Additionally, a matheuristic is introduced for the purpose of comparison. Comparative evaluation against a set of adopted benchmarks reveals the superior performance of both algorithms. A series of sensitivity analyses are conducted to explore the advantages of considering uncertainty, and investigate how decision preference values influence the feasibility of solutions for meal delivery platforms. The proposed formulation and algorithm yield high -quality solutions for delivery platforms with various preferences, facilitating decision -making that aligns with their operational context.

关键词： Meal delivery Chance constraint programming Island Model harmony search algorithm Scenario-based simulation

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A new mathematical model and meta-heuristic algorithm for order batching, depot selection, and assignment problem with multiple depots and pickers

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COMPUTERS & INDUSTRIAL ENGINEERING 2024年 197卷

作者： Gulyesil, Selma Durmusoglu, Zeynep Didem Unutmaz Gaziantep Islam Sci & Technol Univ Dept Ind Engn TR-27010 Gaziantep Turkiye Samsun Univ Dept Ind Engn Samsun Turkiye

The 'order picking problem' involves the efficient and organized retrieval of items from shelves to fulfill customer orders. In this study, we consider a new configuration of warehouse system with multiple pickers and depots (m-pickers &n-depots) for manually operated 'picker-to-parts' warehouses. The efficiency of the process is measured based on two metrics: i- total order picking distance of each picker ii- total number of pickers assigned to each of depots. The handled problem is called as 'Order Batching, Depot Selection and Assignment Problem with Multiple Depots and Multiple Pickers (OBDSAPMDMP)1'. To solve this complex problem, a new bi-objective Mixed-Integer Linear Programming (MILP) formulation for small-sized problems and a meta-heuristic called 'Dependent harmony search (DHS)2' for large-sized problems are proposed. The performance of DHS algorithm is evaluated by comparing the optimal results attained by MILP model. For the problem size of 10 orders, the average gap (%) in distance between the solution of DHS and MILP is 4.22%, although in some experiments DHS can find the optimal solution in a very short time. Also, in related analysis, it is seen that constructing multiple depots instead of one left-most located depot decreases total order picking distance by 7.11% on average.

关键词： Order batching Assignment Multiple depots Multiple pickers harmony search algorithm Joint order picking

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A JAYA algorithm based on normal clouds for DNA sequence optimization

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CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS 2024年第2期27卷 2133-2149页

作者： Zhu, Donglin Wang, Siwei Huang, Zuwei Zhou, Changjun Zhang, Lin Zhejiang Normal Univ Coll Math & Comp Sci Jinhua 321004 Peoples R China Jiangxi Univ Sci & Technol Sch Informat Engn Ganzhou 341000 Jiangxi Peoples R China Jiangxi Univ Sci & Technol Sch Software Engn Nanchang 330000 Peoples R China

DNA computing is one of the more popular computational methods currently studied, but the requirements for nucleic acid molecules in DNA sequences are high, and it is an important challenge to design reasonable and high-quality DNA sequences while satisfying various constraints. Evolutionary algorithms have good applications in DNA sequence optimization problems, but they still have some limitations. To this end, this paper proposes a JAYA algorithm based on normal clouds, referred to as IJAYA, which uses a combinatorial learning approach to update the optimal and worst positions, which is used to manipulate the subsequent merit search means, and then enhances the local search ability of individuals through the normal cloud model, and finally rejects the worst solutions through a harmony search algorithm to find more reasonable and high-quality solutions. The validity of IJAYA is verified in six benchmark functions, in comparison with multiple variants of JAYA and two statistical tests. In the DNA sequence design optimization problem, the average DNA metrics optimized by IJAYA are: 0 (Continuity), 0 (Hairpin), 59.43 (H-measure), 46.57 (Similarity) and 63.79 (Similarity). The feasibility and practicality of IJAYA was verified by comparing it with the solution algorithms proposed in recent years and ablation experiments.

关键词： DNA computing Normal cloud model JAYA Combinatorial learning harmony search algorithm Benchmark functions DNA sequence optimization Ablation experiments

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Optimizing Smart Home Intrusion Detection With harmony-Enhanced Extra Trees

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IEEE ACCESS 2024年 12卷 117761-117786页

作者： Abdusalomov, Akmalbek Kilichev, Dusmurod Nasimov, Rashid Rakhmatullayev, Ilkhom Im Cho, Young Gachon Univ Dept Comp Engn Seongnam 13120 South Korea Tashkent State Univ Econ Dept Informat Syst & Technol Tashkent 100066 Uzbekistan Tashkent Univ Informat Technol Dept Informat Secur Samarkand 140100 Uzbekistan

In this study, we present an innovative network intrusion detection system (IDS) tailored for Internet of Things (IoT)-based smart home environments, offering a novel deployment scheme that addresses the full spectrum of network security challenges. Distinct from existing approaches, our comprehensive strategy not only proposes a model but also incorporates IoT devices as potential vectors in the cyber threat landscape, a consideration often neglected in previous research. Utilizing the harmony search algorithm (HSA), we refined the extra trees classifier (ETC) by optimizing an extensive array of hyperparameters, achieving a level of sophistication and performance enhancement that surpasses typical methodologies. Our model was rigorously evaluated using a robust real-time dataset, uniquely gathered from 105 IoT devices, reflecting a more authentic and complex network scenario compared to the simulated or limited datasets prevalent in the literature. Our commitment to collaborative progress in cybersecurity is demonstrated through the public release of our source code. The system underwent exhaustive testing in 2-class, 8-class, and 34-class configurations, showcasing superior accuracy (99.87%, 99.51%, 99.49%), precision (97.41%, 96.02%, 96.07%), recall (98.45%, 87.14%, 87.1%), and f1-scores (97.92%, 90.65%, 90.61%) that firmly establish its efficacy. This work marks a significant advancement in smart home security, providing a scalable and effective network IDS solution that is adaptable to the intricate dynamics of modern IoT networks. Our findings pave the way for future endeavors in the realm of cyber defense, ensuring that smart homes remain safe havens in an era of digital vulnerability.

关键词： Smart homes Internet of Things Security Data models Radio frequency Ecosystems Random forests Hyperparameter optimization Intrusion detection Machine learning Extra trees classifier harmony search algorithm hyperparameter optimization intrusion detection system machine learning smart home

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Enhanced Conditional Ground Motion Selection Model Considering Spectral Compatibility and Variability of Three Components for Multi-Directional Analysis

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APPLIED SCIENCES-BASEL 2025年第8期15卷 4135-4135页

作者： Demir, Ahmet Palanci, Mehmet Kayhan, Ali Haydar Bolu Abant Izzet Baysal Univ Dept Civil Engn TR-14030 Bolu Turkiye Istanbul Arel Univ Dept Civil Engn TR-34537 Istanbul Turkiye Pamukkale Univ Dept Civil Engn TR-20070 Denizli Turkiye

In this study, the solution model based on the stochastic harmony search algorithm was proposed to obtain real ground motion (GM) records for nonlinear dynamic analysis of structures. Obtaining the GM record problem was formulated as a constrained engineering optimization problem. The solution model ensures spectral compatibility between the mean horizontal spectrum of selected ground motion (GM) records and the target horizontal spectrum, as well as the mean vertical spectrum of the selected GMs with the target vertical spectrum. This model also allows the management of record-to-record variability in both horizontal and vertical components of the selected GMs. Moreover, the model effectively addresses the period-dependent record-to-record variability in all orientations of seismic excitations simultaneously using a single-scale value, preserving the relative amplitude and phasing of actual GM components. The efficiency of the model has been demonstrated through numerical examples with various uniform hazard spectra, specifically those based on Eurocode-8 and the Turkish Building Earthquake Code, as well as scenario-based target spectra. The results demonstrate that through using the proposed model it is possible to obtain GM records with the desired spectral compatibility and spectral dispersion for both horizontal and vertical GM components. Thus, the model can be used as an efficient way to obtain appropriate GM records for nonlinear dynamic analyses of both two- and three-dimensional structural models for performance-based designs and/or evaluation frameworks, considering seismic excitations in both horizontal and vertical directions.

关键词： ground motion selection harmony search algorithm horizontal components nonlinear dynamic analysis vertical components

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A Portrayal of Sliding Mode Control Through Adaptive Neuro Fuzzy Inference System With Optimization Perspective

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IEEE ACCESS 2024年 12卷 3222-3239页

作者： George, Jim Mani, Geetha Vellore Inst Technol Sch Elect Engn SELECT Vellore 632014 Tamil Nadu India Muthoot Inst Technol & Sci Dept Elect & Elect Engn Ernakulam 682308 Kerala India

Sliding mode control is a promising approach for designing controllers for systems with empirical characteristics. This is a favored nonlinear control strategy that effectively addresses the uncertainties present in derived mathematical models. To further enhance the stability of such systems, an Adaptive Neuro Fuzzy Inference System is employed by adapting to dynamic changes and inconsistent correlations between excitation and response. In this study, Sliding Mode Control was deployed in the feedback loop, effectively serving as a state feedback controller based on a nonlinear control law. As a two-parameter control approach, Sliding Mode Control requires careful tuning to achieve optimal performance. The integration of the Adaptive Neuro-Fuzzy System aims to bestow the two parameters of Sliding Mode Control with the ability to rapidly reduce errors to zero, thereby enhancing overall control efficiency. The research focuses on utilizing an Adaptive Neuro Fuzzy Inference System to implement Sliding Mode Control for a DC servo system while emphasizing state feedback control. The harmony search Optimization method is employed to optimize controller parameters effectively. The results of the research demonstrate the achievement of a best-fit value, where the minimal standard error and Best fitness are considered. This highlights the successful integration of the proposed control strategy and validates its effectiveness in providing accurate and reliable control of the real-time DC servo system.

关键词： Adaptive neuro fuzzy inference system (ANFIS) best fitness DC servo harmony search algorithm sliding mode control (SMC) standard error standard deviation (sigma) integral square error (ISE)

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Opposition-Based Learning harmony search algorithm with Mutation for Solving Global Optimization Problems

Opposition-Based Learning Harmony Search Algorithm with Muta...

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第26届中国控制与决策会议

作者： Hao WANG Haibin OUYANG Liqun GAO Wei QIN School of Information Science & Engineering Northeastern University Information engineering department LiaoNing provincial College of Communications China Academy of Aerospace Aerodynamics (CAAA)

This paper develops an opposition-based learning harmony search algorithm with mutation(OLHS-M) for solving global continuous optimization problems. The proposed method is different from the original harmony search(HS) in three aspects. Firstly, opposition-based learning technique is incorporated to the process of improvisation to enlarge the algorithm search space. Then, a new modified mutation strategy is instead of the original pitch adjustment operation of HS to further improve the search ability of HS. Effective self-adaptive strategy is presented to fine-tune the key control parameters(e.g. harmony memory consideration rate HMCR, and pitch adjustment rate PAR) to balance the local and global search in the evolution of the search process. Numerical results demonstrate that the proposed algorithm performs much better than the existing improved HS variants that reported in recent literature in terms of the solution quality and the stability.

关键词： harmony search algorithm Mutation Operation Opposition-Based Learning search Space Stability

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An Optimization-based Adaptive Sliding Mode Control for an Inverted Pendulum

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IETE JOURNAL OF REsearch 2024年第1期70卷 542-557页

作者： Pathak, Rajeev Ranjan Mohanty, Sidhanta Sengupta, Anindita Indian Inst Engn Sci & Technol Dept Elect Engn Howrah 711103 W Bengal India

The work proposes an optimization-based robust adaptive gain sliding mode control technique to handle bounded behavior of uncertainties/perturbations without having the exact knowledge of the bound a priori. The constant of the sliding surface follows dynamical adaptive nature using three optimization techniques, i.e. harmony search algorithm, Bacterial Foraging Optimization algorithm and Gradient search algorithm to extenuate the extent of chattering. The gain of the switching control law, which is a part of the sliding mode control design, is calculated using the gain adaption technique. Lyapunov Stability Criterion is applied to assure the stability of the closed-loop system with adaptable gain and the optimized value of the sliding constant. An inverted Pendulum system has been taken to validate the proposition both in the simulation environment and the hardware platform.

关键词： Adaptive sliding mode control Bacterial foraging optimization algorithm Gradient search algorithm harmony search algorithm Inverted pendulum Sliding mode control

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