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New energy efficient management approach for wireless sensor networks in target tracking using vortex search algorithm

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Heliyon 2025年第5期11卷

作者： Tabatabaei, Shayesteh Department of Computer Engineering University of Saravan Saravan Iran

With the advancement of technology, the use of sensor nodes in mobile target-tracking applications is increasing day by day. However, the design of wireless sensor networks faces constraints such as energy consumption, processing power, memory, environmental dimensions, number of sensor nodes, and bandwidth. Among these constraints, energy consumption is particularly important because wireless sensor networks are composed of low-power sensors. In this article, a new method is introduced to optimize energy consumption in wireless sensor networks for mobile target-tracking applications. The proposed method consists of two stages. In the first stage, the path and position of the target are determined using the vortex search algorithm. In the second stage, the transfer of data related to the target's movement between sensor nodes and the sink, and the adjustment of the sleep/awake period of sensor nodes, are performed. The performance of this method is compared and evaluated with the Tracking-45-Degree-Vectors method in the OPNET simulator in terms of energy consumption, data transmission delay, media access delay, throughput, signal-to-noise ratio, and packet error rate. The results demonstrate that the proposed method outperforms the Tracking-45-Degree-Vectors method in mobile target tracking. © 2025

关键词： Mobile target tracking Tracking-45-degree-vectors protocol vortex search algorithm Wireless sensor network

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vortex search algorithm Applied to the Parametric Estimation in PV Cells Considering Manufacturer Datasheet Information

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IEEE LATIN AMERICA TRANSACTIONS 2021年第9期19卷 1581-1589页

作者： Montoya, Oscar Danilo Gil-Gonzalez, Walter Lopez-Lezama, Jesus M. Univ Dist Francisco Jose de Caldas Fac Ingn Bogota 11021 DC Colombia Univ Tecnol Bolivar Smart Energy Lab Cartagena 131001 Colombia Inst Univ Pascual Bravo Fac Ingn Grp GIIEN Campus Robledo Medellin 050036 Colombia Univ Antioquia Res Grp GIMEL Dept Elect Engn Medellin 1226 Colombia

This paper addresses the problem of parametric estimation in solar cells considering manufacturer datasheet information regarding open-circuit, short-circuit, and maximum power points from the point of view of mathematical optimization. To represent this problem a single-objective function is formulated associated with the minimization of the mean square error of the single-diode model evaluated in the operational points reported by the manufacturer. The solution of this nonlinear non-convex optimization model is addressed with a metaheuristic optimization technique known in specialized literature as a vortex search algorithm (VSA). This metaheuristic optimization method works with Gaussian distribution functions and variable radius to explore and exploit the solution space by generating hyperspheres that move through the solution space as a function of the best current solution. The VSA is implemented in MATLAB environment by using commercial photovoltaic module information, where numerical results demonstrate the efficiency of this optimization method with objective functions lower than 1times10-25 and processing times around 6.13s.

关键词： Mathematical model Integrated circuit modeling Numerical models Estimation IEEE transactions Silicon compounds Reactive power Photovoltaic modules parametric estimation vortex search algorithm metaheuristic optimization Manufacturer information single-diode information

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vortex search algorithm for the analog active filter component selection problem

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AEU-INTERNATIONAL JOURNAL OF ELECTRONICS AND COMMUNICATIONS 2015年第9期69卷 1243-1253页

作者： Dogan, Berat Olmez, Tamer Istanbul Tech Univ Dept Elect & Commun Engn Istanbul Turkey

Optimal selection of passive components is one of the most crucial design steps in analog active filter design problems. As the number of possible combinations increases, it becomes infeasible to perform an exhaustive search for optimum component values. Thus, intelligent algorithms are required for a fast and optimum selection of the passive component values. In this study, a newly proposed metaheuristic, the vortex search (VS) algorithm, is utilized for this purpose. To evaluate the performance of the VS algorithm, two different analog active filter topologies, the fourth-order Butterworth low-pass filter and the state variable low-pass filter, are used. The component values of the active filter topologies are selected within three different series of (E12, E24 and E96) passive components for both the resistors and the capacitors. The results are compared to other metaheuristics such as the particle swarm optimization (PSO2011), artificial bee colony (ABC), differential evolution (DE) and harmony search (HS) algorithms. It is shown that, the VS algorithm finds the minimum fitness values for both of the active filter topologies which in turn provides the optimum component values for each of the used component series. (C) 2015 Elsevier GmbH. All rights reserved.

关键词： Analog active filter design Optimization vortex search algorithm Component selection

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vortex search algorithm for Optimal Power Flow Analysis in DC Resistive Networks With CPLs

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS 2020年第8期67卷 1439-1443页

作者： Montoya, Oscar Danilo Gil-Gonzalez, Walter Grisales-Norena, L. F. Univ Tecnol Bolivar Program Elect & Elect Engn Cartagena 131001 Colombia Univ Tecnol Pereira Dept Elect Power Engn Pereira 660003 Colombia Inst Tecnol Metropolitano Dept Mechatron & Electromech Engn Medellin 050012 Colombia

This express brief addresses the optimal power flow (OPF) analysis in direct-current (DC) resistive networks with constant power loads (CPLs). The OPF employs the vortex search algorithm (VSA) in conjunction with a power flow method based on successive approximations by proposing a master-slave optimization methodology. The VSA is a powerful numerical optimization method that works with Gaussian distributions and variable radius for intensive exploration and exploitation in the solution space of the OPF problem. The power flow based on successive approximations allows evaluating the objective function by solving the non-convex equality constraints related to the power balance equations. Numerical implementations in two distribution DC feeders with 10 and 21 nodes show that the proposed approach attains the optimal solution reported by convex approximations, sequential quadratic models and nonlinear optimization methods. All the simulations have been conducted in MATLAB software.

关键词： Voltage control Optimization Mathematical model Approximation algorithms Gaussian distribution Power generation Generators Direct current networks pure-algorithmic methodology optimal power flow vortex search algorithm

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vortex search algorithm for Optimal Sizing of Distributed Generators in AC Distribution Networks with Radial Topology 6th

Vortex Search Algorithm for Optimal Sizing of Distributed Ge...

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6th Workshop on Engineering Applications (WEA)

作者： Danilo Montoya, Oscar Fernando Grisales-Norena, Luis Tadeo Amin, William Alejandro Rojas, Luis Campillo, Javier Univ Tecnol Bolivar Programa Ingn Elect & Ingn Elect Cartagena Colombia Inst Tecnol Metropolitano Dept Electromecan & Mecatron Medellin Colombia Fdn Tecnol Antonio Arevalo Escuela Diseno & Ingn Cartagena Colombia

ISBN: (纸本)9783030310196;9783030310189

This paper proposes a vortex search algorithm (VSA) optimization for optimal dimensioning of distributed generators (DGs), in radial alternating current (AC) distribution networks. The VSA corresponds to a metaheuristic optimization technique that works in the continuous domain, to solve nonlinear, non-convex, large scale optimization problems. Here, this technique is used to determine the optimal power generation capacity of the DGs from the top-down analysis. From the bottom-up, a conventional backward/forward power flow is employed for determining the voltage behavior and calculate the power losses of the network, for each power output combination in the DGs. Numerical results demonstrate that the proposed approach is efficient and robust for reducing power losses on AC grids by optimally sizing the capacity the DGs, compared with other approaches found on literature reports. All the simulations were conducted using the MATLAB software.

关键词： Electrical distribution networks Distributed generation Optimal power flow Metaheuristic optimization vortex search algorithm

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vortex search algorithm based Machine Learning Classification for IDS 6

Vortex Search Algorithm based Machine Learning Classificatio...

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6th International Conference on Trends in Electronics and Informatics (ICOEI)

作者： Krishnan, V. Gokula Lakshmi, P. Vasantha Julaiha, A. G. Noorul Jemina, S. Lincy Sunitha, A. Divya, V. CVR Coll Engn CSIT Dept Hyderabad Telangana India Rajalakshmi Inst Technol CSE Dept Chennai Tamil Nadu India Panimalar Inst Technol CSE Dept Chennai Tamil Nadu India St Joseph Coll Engn CSE Dept Chennai Tamil Nadu India Sathyabama Inst Sci & Technol Sch Elect & Elect Engn Chennai Tamil Nadu India

ISBN: (纸本)9781665483285;9781665483292

Internet and communication advancements have resulted in a massive expansion of network scale and the corresponding data. When it comes to hacking and security breaches, a company's network infrastructure is always at risk because of the range of attacks that might take place. One such instrument is an intrusion detection system (IDS), which inspects network traffic to safeguard the network's in the case of an intrusion. Feature selection has a considerable impact on the performance of IDSs. In order to detect anomalies, a large number of time-consuming features are used. Therefore, the selection of features has a direct impact on the amount of time it takes to examine traffic patterns and increase accuracy. Feature selection-based machine learning models for IDSs were the goal of this research. When it comes to classifying network intrusions, the researchers start with the vortex search algorithm (VSA), then move on to Support Vector Machines (SVM) and the J48 algorithm. Normalization, feature selection, and classification are the three stages of the proposed perfect. Tensor flow and python are used to implement the experiments on the NSL-KDD benchmark dataset. Accuracy, precision and recall are assessed and compared to existing approaches. F1-score is also calculated. The proposed VSA was found to be 93.45% accurate when using SVM and 90.48 percent accurate when using J48, according to the results.

关键词： Intrusion Detection System Feature Selection vortex search algorithm Machine Learning Anomaly Detection

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A novel hybrid global optimization algorithm having training strategy: hybrid Taguchi-vortex search algorithm

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TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES 2021年第4期29卷 1908-+页

作者： Saka, Mustafa Coban, Melih Eke, Ibrahim Tezcan, Suleyman Sungur Taplamacioglu, Muslum Cengiz Gazi Univ Dept Elect & Elect Engn Fac Engn Ankara Turkey Kirikkale Univ Dept Elect & Elect Engn Fac Engn Kirikkale Turkey

In this paper, a novel hybrid Taguchi-vortex search algorithm (HTVS) is proposed for solving global optimization problems. Taguchi orthogonal approximation and vortex search algorithm (VS) are hybridized in presenting method. In HTVS, orthogonal arrays in the Taguchi method are trained and obtained better solutions are used to find global optima in VS. Thus, HTVS has better relation between exploration and exploitation, and it exhibits more powerful approximation to find global optimum value. Proposed HTVS algorithm is applied to sixteen well-known benchmark optimization test functions with different dimensions. The results are compared with the Taguchi orthogonal array approximation (TOAA), vortex search algorithm, grey wolf optimizer (GWO), sine cosine algorithm (SCA), moth-flame optimization algorithm (MFO), whale optimization algorithm (WOA) and salp swarm algorithm (SSA). In order to compare the effectiveness of HTVS statistically, Wilcoxon signed-rank test (WSRT) is used in this study. Furthermore, HTVS is applied to two different real engineering problems having some constraints (tension/compression spring design and pressure vessel design). All obtained results suggested that HTVS can find optimal or very close to optimal results. Moreover, it has good computational ability and fast convergence behavior as well.

关键词： Hybrid Taguchi-vortex search algorithm Taguchi orthogonal arrays vortex search algorithm global optimization engineering design problems with constraints

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Combustion optimization of a boiler based on the chaos and Levy flight vortex search algorithm

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APPLIED MATHEMATICAL MODELLING 2018年 58卷 3-18页

作者： Li, Xia Niu, Peifeng Liu, Jianping Yanshan Univ Sch Elect Engn Qinhuangdao 066004 Peoples R China Hebei Normal Univ Sci & Technol Qinhuangdao 066004 Peoples R China

The boiler combustion optimization has attracted growing research interest of more and more researchers in thermal energy engineering field. To achieve combustion optimization objective, the combustion characteristics model of the boiler needs to be built, and the efficient optimization algorithm also needs to be found. Therefore, in this study, a logic self map chaos and Levy flight vortex search (I-VS) algorithm is proposed. Then, comparative study between the I-VS algorithm and some other state-of-the-art optimization algorithms is performed. Next, the combustion efficiency model is built based on fast learning network (FLN). The I-VS algorithm is used to optimize FLN, and then an I-VS-FLN model is built for predicting NOx emissions of a boiler. Experimental results show that the I-VS-FLN model has better generalization ability than five other models. Finally, the I-VS algorithm is used to tune the operating parameters of the boiler based on the FLN model and the I-VS-FLN model to achieve the combustion optimization objective. (C) 2018 Elsevier Inc. All rights reserved.

关键词： vortex search algorithm Fast learning network Logic self-map chaos Levy flight I-VS-FLN model Combustion optimization

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Power system harmonic and interharmonic estimation using vortex search algorithm

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ELECTRIC POWER SYSTEMS REsearch 2020年第0期182卷 106187-000页

作者： Altintasi, Cagri Aydin, Omer Taplamacioglu, M. Cengiz Salor, Ozgul Gazi Univ Dept Elect & Elect Engn TR-06570 Ankara Turkey Kyrgyz Turkish Manas Univ Dept Elect & Elect Engn Bishkek Kyrgyzstan

In this paper, a vortex search algorithm (VSA) based method designed to estimate power system harmonics and interharmonics for highly time-varying cases is presented. Time-variation in the power system is due to the nonlinear and stochastic loads such as electric arc furnaces (EAF) and it is one of the major cause of the power quality problems. The proposed algorithm is tested on both synthetic signals and also field data obtained from transmission system substations supplying EAF plants. The results are compared with other search algorithm-based methods reported in the literature and shown that VSA algorithm exhibits better estimation performance and has less computational complexity. In addition, the VSA algorithm is also tested on real field data and the results are compared with those obtained by Kalman Filtering method, which is claimed to provide fastest results in the literature. It has been shown that the proposed method has better convergence results in noisy environment with less computational complexity.

关键词： Harmonic estimation Harmonics Interharmonics vortex search algorithm Time-varying harmonics

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A novel metaheuristic for multi-objective optimization problems: The multi-objective vortex search algorithm

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INFORMATION SCIENCES 2017年 402卷 124-148页

作者： Ozkis, Ahmet Babalik, Ahmet Selcuk Univ Fac Engn Dept Comp Engn TR-42075 Konya Turkey

This study investigates a multi-objective vortex search algorithm (MOVS) by modifying the single-objective vortex search algorithm or VS. The VS is a metaheuristic-based algorithm that uses a new adaptive step-size adjustment strategy to improve the performance of the search process. search mechanism of the VS is inspired by the vortex pattern, so it is called a "vortex search" algorithm. The original VS is an improved way of solving single-objective continuous problems. To improve the MOVS algorithm, the VS algorithm is enhanced with added calculation approaches, such as fast-nondominated-sorting and crowding-distance, in order to identify the degree of non-dominance of the solutions and the densities of their occurrence. In addition, a crossover operation is added to the MOVS algorithm in order to enhance the Pareto front convergence capacity of the solutions. Finally, to spread the solutions more successfully over the Pareto front, it has been randomly produced using the inverse incomplete gamma function using a parameter between 0 and 1. The proposed MOVS algorithm is tested against 36 different benchmark problems together with NSGAII, MOCeII, IBEA and MOEA/D algorithms. The test results indicate that the MOVS algorithm achieves a better performance on accuracy and convergence speed than any other algorithms when comparisons are made against several test problems, and they also show that it is a competitive algorithm. (C) 2017 Elsevier Inc. All rights reserved.

关键词： vortex search algorithm Multi-objective optimization Metaheuristics Non-dominated sorting genetic algorithm-II

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