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Journal articles on the topic 'MAYFLY ALGORITHM'

Author: Grafiati

Published: 11 September 2023

Last updated: 31 July 2025

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1

Du, Qianhang, and Honghao Zhu. "Dynamic elite strategy mayfly algorithm." PLOS ONE 17, no. 8 (2022): e0273155. http://dx.doi.org/10.1371/journal.pone.0273155.

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The mayfly algorithm (MA), as a newly proposed intelligent optimization algorithm, is found that easy to fall into the local optimum and slow convergence speed. To address this, an improved mayfly algorithm based on dynamic elite strategy (DESMA) is proposed in this paper. Specifically, it first determines the specific space near the best mayfly in the current population, and dynamically sets the search radius. Then generating a certain number of elite mayflies within this range. Finally, the best one among the newly generated elite mayflies is selected to replace the best mayfly in the curren

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Zhao, Mengling, Xinlu Yang, and Xinyu Yin. "An improved mayfly algorithm and its application." AIP Advances 12, no. 10 (2022): 105320. http://dx.doi.org/10.1063/5.0108278.

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An improved version of the mayfly algorithm called the golden annealing crossover-mutation mayfly algorithm (GSASMA) is proposed to address the low convergence efficiency and insufficient search capability of existing mayfly algorithms. First, the speed of individual mayflies is optimized using a simulated annealing algorithm to improve the update rate. The position of individuals is improved using the golden sine algorithm. Second, the impact of using different crossover and mutation methods in the algorithm is compared, and the optimal strategy is selected from the algorithm. To evaluate the

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LI, Linfeng, Weidong LIU, and Le LI. "Underwater magnetic field measurement error compensation based on improved mayfly algorithm." Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University 40, no. 5 (2022): 1004–11. http://dx.doi.org/10.1051/jnwpu/20224051004.

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This paper investigates the magnetic filed interference problem when the ROV equipped with a three-axis magnetometer measures the magnetic field of underwater magnetic targets within a short range, and a magnetic field compensation method based on an improved mayfly algorithm is proposed to improve the measurement accuracy of underwater magnetic field information. Firstly, a compensation model is established based on the installation error of the three-axis magnetometer and the interference magnetic field of the ROV. Then, in view of the problem that the original mayfly algorithm is easy to fa

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Oladimeji, A. I., A. W. Asaju-Gbolagade, and K. A. Gbolagade. "A proposed framework for face - iris recognition system using enhanced mayfly algorithm." Nigerian Journal of Technology 41, no. 3 (2022): 535–41. http://dx.doi.org/10.4314/njt.v41i3.13.

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Fused biometrics systems have proven to solve some problems associated with unimodal systems but also face challenges in various aspects of their implementation such as difficulty in design, user acceptance is quite low, and the performance tradeoff. This framework tends to address some of these implementation challenges by using an enhanced mayfly algorithm, a modification of the existing mayfly algorithm that was recently proposed, as feature selection. Mayfly algorithm combines advantages of particle swarm optimization, genetic algorithm, and firefly algorithm, simulated in different experi

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Nagarajan, Karthik, K. Balaji Nanda Kumar Reddy, Arul Rajagopalan, NMG Kumar, and Mohit Bajaj. "Improved Mayfly Algorithm for Optimizing Power Flow with Integrated Solar and Wind Energy." International Journal of Electrical and Electronics Research 12, no. 2 (2024): 415–20. http://dx.doi.org/10.37391/ijeer.120212.

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Across the globe, the transition towards sustainable energy systems necessitates seamless implementation of Renewable Energy Sources (RES) into traditional power grids. Such RESs include solar and wind power. The current research work intends to overcome the challenges associated with Optimal Power Flow (OPF) problem in power systems in which the traditional operation parameters ought to be optimized for effective and trustworthy integration of the RESs. The current study proposes an innovative nature-inspired approach by enhancing the Mayfly algorithm on the basis of mating behaviour of mayfl

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Zervoudakis, Konstantinos, and Stelios Tsafarakis. "A mayfly optimization algorithm." Computers & Industrial Engineering 145 (July 2020): 106559. http://dx.doi.org/10.1016/j.cie.2020.106559.

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Seifedine, Kadry, Rajinikanth Venkatesan, Koo Jamin, and Kang Byeong-Gwon. "Image multi-level-thresholding with Mayfly optimization." International Journal of Electrical and Computer Engineering (IJECE) 11, no. 6 (2021): 5420–29. https://doi.org/10.11591/ijece.v11i6.pp5420-5429.

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Image thresholding is a well approved pre-processing methodology and enhancing the image information based on a chosen threshold is always preferred. This research implements the mayfly optimization algorithm (MOA) based image multi-level-thresholding on a class of benchmark images of dimension 512x512x1. The MOA is a novel methodology with the algorithm phases, such as; i) Initialization, ii) Exploration with male-mayfly (MM), iii) Exploration with female-mayfly (FM), iv) Offspring generation and, v) Termination. This algorithm implements a strict two-step search procedure, in which every May

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Kadry, Seifedine, Venkatesan Rajinikanth, Jamin Koo, and Byeong-Gwon Kang. "Image multi-level-thresholding with Mayfly optimization." International Journal of Electrical and Computer Engineering (IJECE) 11, no. 6 (2021): 5420. http://dx.doi.org/10.11591/ijece.v11i6.pp5420-5429.

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<span>Image thresholding is a well approved pre-processing methodology and enhancing the image information based on a chosen threshold is always preferred. This research implements the mayfly optimization algorithm (MOA) based image multi-level-thresholding on a class of benchmark images of dimension 512x512x1. The MOA is a novel methodology with the algorithm phases, such as; i) Initialization, ii) Exploration with male-mayfly (MM), iii) Exploration with female-mayfly (FM), iv) Offspring generation and, v) Termination. This algorithm implements a strict two-step search procedure, in whi

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Prasanna, S. L., and Nagendra Panini Challa. "Heart Disease Prediction Using Optimal Mayfly Technique with Ensemble Models." International Journal of Swarm Intelligence Research 13, no. 1 (2022): 1–22. http://dx.doi.org/10.4018/ijsir.313665.

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This paper proposes a methodology consisting of two phases: attributes selection and classification based on the attributes selected. Phase 1 uses the introduced new feature selection algorithm which is the optimal mayfly algorithm (OMA) to solve the feature selection technique problem. Mayfly algorithm has derived features of physiological and anatomical relevance, like ST depression, the highest heart rate, cholesterol, chest pain, and heart vessels. In the second phase, the selected attributes use the ensemble classifiers like random subspace, bagging, and boosting. Optimal mayfly algorithm

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Dilip Kumar Bagal, Soudamini Behera,. "Optimizing Power Generation Scheduling: A Comparative Analysis of Metaheuristic Algorithms." Journal of Electrical Systems 20, no. 2 (2024): 2212–30. http://dx.doi.org/10.52783/jes.1989.

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Purpose: This research compares six optimization methods, including the Mayfly Optimization Algorithm, Genetic Algorithm, Simulated Annealing, Firefly Algorithm, and Differential Evolution (DE). Design/Methodology/Approach: The evaluation of any algorithm is predicated on its ability to strike a balance between meeting demand, taking into account renewable energy sources, and lowering the total cost of producing power. Findings: The analysis shows that although PSO and GA converge to similar overall costs, the algorithms' performances differ. Then come SA, FA, and DE in close succe

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Zhao, Juan, and Zheng-Ming Gao. "The negative mayfly optimization algorithm." Journal of Physics: Conference Series 1693 (December 2020): 012098. http://dx.doi.org/10.1088/1742-6596/1693/1/012098.

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Gao, Zheng-Ming, Juan Zhao, Su-Ruo Li, and Yu-Rong Hu. "The improved mayfly optimization algorithm." Journal of Physics: Conference Series 1684 (November 2020): 012077. http://dx.doi.org/10.1088/1742-6596/1684/1/012077.

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Zhao, Yanpu, Changsheng Huang, Mengjie Zhang, and Yang Cui. "AOBLMOA: A Hybrid Biomimetic Optimization Algorithm for Numerical Optimization and Engineering Design Problems." Biomimetics 8, no. 4 (2023): 381. http://dx.doi.org/10.3390/biomimetics8040381.

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The Mayfly Optimization Algorithm (MOA), as a new biomimetic metaheuristic algorithm with superior algorithm framework and optimization methods, plays a remarkable role in solving optimization problems. However, there are still shortcomings of convergence speed and local optimization in this algorithm. This paper proposes a metaheuristic algorithm for continuous and constrained global optimization problems, which combines the MOA, the Aquila Optimizer (AO), and the opposition-based learning (OBL) strategy, called AOBLMOA, to overcome the shortcomings of the MOA. The proposed algorithm first fu

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J, Jenifer, and Jemima Priyadarsini R. "Improved Mayfly Optimization and LightGBM Classifier for Smart City Traffic Prediction." Indian Journal of Science and Technology 15, no. 40 (2022): 2085–92. https://doi.org/10.17485/IJST/v15i40.1155.

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Abstract <strong>Objectives:</strong> This research work focuses on predicting traffic for the Smart City. <strong>Methods:</strong> Current research methods for traffic prediction are based on machine learning (ML) model. This article presents two contributions related to it. First, it provides feature engineering that includes feature extraction and a nature inspired optimization algorithm for selecting the best features. The mayfly optimization algorithm is improved by using the mode-based ranking method to select the best feature. Second, it uses the light-weight boosting me

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YOGA DWI WAHYU NUGRAHA, HENDRAWAN ARMANTO, and YOSI KRISTIAN. "Single Objective Mayfly Algorithm with Balancing Parameter for Multiple Traveling Salesman Problem." Journal of Electronics, Electromedical Engineering, and Medical Informatics 5, no. 3 (2023): 193–204. http://dx.doi.org/10.35882/jeemi.v5i3.299.

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The Multiple Travelling Salesman Problem (MTSP) is a challenging combinatorial problem that involves multiple salesman visiting a set of cities, each exactly once, starting and ending at the same depot. The aim is to determine the optimal route with minimal cost and node cuts for each salesman while ensuring that at least one salesman visits each city. As the problem is NP-Hard, a single-objective metaheuristic algorithm, called the Mayfly Algorithm, inspired by the collective behavior of mayflies, is employed to solve the problem using the TSPlib95 test data. Since the Mayfly Algorithm employ

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Wang, Xing, Jeng-Shyang Pan, Qingyong Yang, Lingping Kong, Václav Snášel, and Shu-Chuan Chu. "Modified Mayfly Algorithm for UAV Path Planning." Drones 6, no. 5 (2022): 134. http://dx.doi.org/10.3390/drones6050134.

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The unmanned aerial vehicle (UAV) path planning problem is primarily concerned with avoiding collision with obstacles while determining the best flight path to the target position. This paper first establishes a cost function to transform the UAV route planning issue into an optimization issue that meets the UAV’s feasible path requirements and path safety constraints. Then, this paper introduces a modified Mayfly Algorithm (modMA), which employs an exponent decreasing inertia weight (EDIW) strategy, adaptive Cauchy mutation, and an enhanced crossover operator to effectively search the UAV con

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Chen, Zhan, Yangwang Fang, Ruitao Zhang, and Wenxing Fu. "Layout of Detection Array Based on Multi-Strategy Fusion Improved Adaptive Mayfly Algorithm in Bearing-Only Sensor Network." Sensors 24, no. 8 (2024): 2415. http://dx.doi.org/10.3390/s24082415.

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The various applications of bearing-only sensor networks for detection and localization are becoming increasingly widespread and important. The array layout of the bearing-only sensor network seriously impacts the detection performance. This paper proposes a multi-strategy fusion improved adaptive mayfly algorithm (MIAMA) in a bearing-only sensor network to perform layout planning on the geometric configuration of the optimal detection. Firstly, the system model of a bearing-only sensor network was constructed, and the observability of the system was analyzed based on the Cramer–Rao Lower Boun

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Zhang, Shoujing, Tiantian Hou, Qing Qu, et al. "An Improved Mayfly Method to Solve Distributed Flexible Job Shop Scheduling Problem under Dual Resource Constraints." Sustainability 14, no. 19 (2022): 12120. http://dx.doi.org/10.3390/su141912120.

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Aiming at the distributed flexible job shop scheduling problem under dual resource constraints considering the influence of workpiece transportation time between factories and machines, a distributed flexible job shop scheduling problem (DFJSP) model with the optimization goal of minimizing completion time is established, and an improved mayfly algorithm (IMA) is proposed to solve it. Firstly, the mayfly position vector is discrete mapped to make it applicable to the scheduling problem. Secondly, three-layer coding rules of process, worker, and machine is adopted, in which the factory selectio

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Annisa Jamali, Aida Nur Syafiqah Shaari, Muhamad Sukri Hadi, and Intan Zaurah Mat Darus. "Mayfly Algorithm for Modelling a Horizontal Flexible Plate Structure." Journal of Advanced Research in Applied Mechanics 118, no. 1 (2024): 167–82. http://dx.doi.org/10.37934/aram.118.1.167182.

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Flexible plates are widely used in engineering and the industry, primarily due to the lightweight nature compared to rigid counterparts. These structures offer benefits such as cost savings, lower energy consumptions and improved operational safety. However, a notable drawback is that flexible structures are vulnerable to unwanted vibrations, which can cause structural damages. Hence, the development of specialized models are essential to effectively addressing this challenge. Researchers have devised various approaches to suppress unwanted vibrations, with contemporary studies often employing

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Zhao, Juan, and Zheng-Ming Gao. "The improved mayfly optimization algorithm with Chebyshev map." Journal of Physics: Conference Series 1684 (November 2020): 012075. http://dx.doi.org/10.1088/1742-6596/1684/1/012075.

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Abdulsalam, S. O., R. A. Ayofe, M. F. Edafeajiroke, J. F. Ajao, and R. S. Babatunde. "Development of an intrusion detection system using mayfly feature selection and artificial neural network algorithms." LAUTECH Journal of Engineering and Technology 8, no. 2 (2024): 148–60. http://dx.doi.org/10.36108/laujet/4202.81.0241.

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Protecting the privacy and confidentiality of information and devices in computer networks requires reliable methods of intrusion detection. However, effective intrusion detection is made more difficult by the enormous dimensions of data available in computer networks. To boost intrusion detection classification performance in computer networks, this study developed a feature selection mode for the classification task. The proposed model utilized the Mayfly feature selection algorithm and ANN as the classifiers. The model was also tested without a mayfly algorithm. The model's efficacy was det

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Ansah, Kwabena, Justice Kwame Appati, Ebenezer Owusu, and Jamal-Deen Abdulai. "A Hybrid Heuristic Model for Duty Cycle Framework Optimization." International Journal of Distributed Sensor Networks 2024 (January 27, 2024): 1–12. http://dx.doi.org/10.1155/2024/9972429.

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This paper proposes a hybrid metaheuristic approach to optimize a duty cycle framework based on Seagull and Mayfly Optimization (HSMO-DC) Algorithm. This approach becomes crucial as current clustering protocols are unable to efficiently tune the clustering parameters in accordance to the diversification of varying WSNs. The proposed HSMO-DC primarily has two parts, where the first part takes care of the online cluster head selection and network communication using the seagull algorithm while the second part performs parameter optimization using the mayfly algorithm. The seagull is aimed at imp

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Prasanth, Vidhya, M. Ramachandran, and Kurinjimalar Ramu. "A Study on Mayfly Algorithm and Its Recent Developments." Data Analytics and Artificial Intelligence 2, no. 2 (2022): 109–16. http://dx.doi.org/10.46632/daai/2/2/6.

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It is to define its relationship with the partners during the formation and registration process of S Company Is a legal document prepared and also refers to the minute of the angle corresponding to the MOA 360 minute mark. Each minute represents 1/60 of a degree, just like the minutes of an hour. When shooting, even a small angle can cause you to miss the mark, so it is important to adjust your MOA to a precise angle or fine for a minute. Stands for Memorandum of Association, which refers to articles of association. They help protect and build your business and help establish the company's id

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JESI, MARIA, AHILAN APPATHURAI, MUTHU KUMARAN, and ARUL KUMAR. "LOAD BALANCING IN CLOUD COMPUTING VIA MAYFLY OPTIMIZATION ALGORITHM." REVUE ROUMAINE DES SCIENCES TECHNIQUES — SÉRIE ÉLECTROTECHNIQUE ET ÉNERGÉTIQUE 69, no. 1 (2024): 79–84. http://dx.doi.org/10.59277/rrst-ee.2024.1.14.

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Cloud computing is a new technology that enables users to store and retrieve data via the Internet on demand rather than using their hardware. Cloud computing comprises distinct data centers (servers) and clients (users). Load unbalancing is a multi-variant, multi-constraint issue that lowers the efficacy and performance of system resources. Therefore, a load scheduling technique is needed to distribute work among the right VMs and preserve the trade-off between them. To achieve better performance, this paper presents a novel mayfly optimization algorithm for load balancing (MFO-LB), which uti

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Amirthalingam, M., and R. Ponnusamy. "Enhancing Wireless Capsule Endoscopic Image Classification using Mayfly Algorithm with Deep Learning Approach." International Journal of Science and Research (IJSR) 12, no. 11 (2023): 1113–24. http://dx.doi.org/10.21275/sr231115113636.

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Li, Linfeng, Weidong Liu, Le Li, Huifeng Jiao, Junqi Qu, and Gongwu Sun. "Compensation of Optical Pump Magnetometer Using the Improved Mayfly Optimization Algorithm." Journal of Marine Science and Engineering 10, no. 12 (2022): 1982. http://dx.doi.org/10.3390/jmse10121982.

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In order to solve the problem that the cesium optical pump magnetometer is disturbed by the carrier’s interference magnetic field during magnetic field anomaly detection, an interference magnetic field compensation method based on an improved mayfly optimization algorithm (IMOA) was proposed in this paper. First, by combining the measurement results of the attitude sensor with the geomagnetic inclination and magnetic declination in the locality, the measurement results of the optical pump magnetometer can be decomposed into the component values under the three axes of the carrier coordinate sy

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Wang, Ji-Quan, Hong-Yu Zhang, Hao-Hao Song, Pan-Li Zhang, and Jin-Ling Bei. "Prediction of Pork Supply Based on Improved Mayfly Optimization Algorithm and BP Neural Network." Sustainability 14, no. 24 (2022): 16559. http://dx.doi.org/10.3390/su142416559.

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Focusing on the issues of slow convergence speed and the ease of falling into a local optimum when optimizing the weights and thresholds of a back-propagation artificial neural network (BPANN) by the gradient method, a prediction method for pork supply based on an improved mayfly optimization algorithm (MOA) and BPANN is proposed. Firstly, in order to improve the performance of MOA, an improved mayfly optimization algorithm with an adaptive visibility coefficient (AVC-IMOA) is introduced. Secondly, AVC-IMOA is used to optimize the weights and thresholds of a BPANN (AVC-IMOA_BP). Thirdly, the t

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Gao, Zheng-Ming, Juan Zhao, Su-Ruo Li, and Yu-Rong Hu. "The improved mayfly optimization algorithm with opposition based learning rules." Journal of Physics: Conference Series 1693 (December 2020): 012117. http://dx.doi.org/10.1088/1742-6596/1693/1/012117.

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Barhanpurkar, Atharva, Deepak Hujare, Omkar Kulkarni, and Abhijeet Birari. "Optimization of Flywheel for Reciprocating Air Compressor using Mayfly Algorithm." International Journal of Engineering Trends and Technology 71, no. 8 (2023): 191–200. http://dx.doi.org/10.14445/22315381/ijett-v71i8p217.

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Pratap Singh, Akhilendra, Manish Srivastava, K. Soumya, and Kuldeep Singh Kulhar. "Mayfly Optimization Algorithm for MPPT of PV System under Partial Shading Conditions." E3S Web of Conferences 540 (2024): 12004. http://dx.doi.org/10.1051/e3sconf/202454012004.

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Maximum power point tracking (MPPT)methods are most popular to harvest maximum energy from renewable energy sources for generating electric power. Among many renewable energy sources, solar energy is a primary and mostly available on the earth. Generally photovoltaic (PV) panel are arranging in a proper sequence to produce required electric power. Many conventional MPPT algorithms are available on PV system but working on uniform irradiances. Partial shading is a common phenomenon on PV systems. During partial shading conditions, conventional MPPT algorithms will fail to exhibits its best perf

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Al-Karawi, Saja Bilal Hafedh, and Hakan Koyuncu. "Hybrid Neural Network Approach for Tea Leaf Disease Detection Using Pelican and Mayfly Optimization Algorithms." Jurnal Riset Informatika 6, no. 2 (2024): 119–30. http://dx.doi.org/10.34288/jri.v6i2.274.

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This study addresses the problem of plant diseases and the difficulty of detecting them, and it presents a unique technique for the automatic detection of tea leaf diseases by combining neural networks and optimization techniques. Our research uses a curated database of tea plant leaf photographs that includes healthy and diseased specimens. The neural network (CNN) is trained and fine-tuned using optimization algorithms. To increase disease identification accuracy, we used a hybrid novel optimization algorithm called (POA-MA) which is Pelican Optimization Algorithm (POA), and Mayfly Optimizat

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Liu, Ximu, Mi Zhao, Zihan Wei, and Min Lu. "Economic Optimal Scheduling of Wind–Photovoltaic-Storage with Electric Vehicle Microgrid Based on Quantum Mayfly Algorithm." Applied Sciences 12, no. 17 (2022): 8778. http://dx.doi.org/10.3390/app12178778.

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The effectiveness of energy management systems is a great concern for wind–photovoltaic-storage electric vehicle systems, which coordinate operation optimization and flexible scheduling with the power grid. In order to save system operation cost and reduce the energy waste caused by wind and light abandonment, a time-sharing scheduling strategy based on the state of charge (SOC) and flexible equipment is proposed, and a quantum mayfly algorithm (QMA) is innovatively designed to implement the strategy. Firstly, a scheduling strategy is produced according to the SOC of the battery and electric v

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Hu, Zhixiang, Huiyu Zhu, Lei Huang, and Cheng Cheng. "Damage Identification Method and Uncertainty Analysis of Beam Structures Based on SVM and Swarm Intelligence Algorithm." Buildings 12, no. 11 (2022): 1950. http://dx.doi.org/10.3390/buildings12111950.

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A two-stage damage identification method for beam structures based on support vector machine and swarm intelligence optimization algorithms is proposed. First, the frequencies and mode shapes of the beam structure are obtained using the smooth orthogonal decomposition method, and the normalized modal curvature is calculated as the input of a pre-trained support vector machine to determine the damage location. Then, the stiffness loss at the damaged location of the structure is calculated using swarm intelligence algorithms. The fitness function is the sum of the residual squares of the frequen

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Yousaf, Muhammad Zain, Ali Raza, Ghulam Abbas, et al. "MTDC Grids: A Metaheuristic Solution for Nonlinear Control." Energies 15, no. 12 (2022): 4263. http://dx.doi.org/10.3390/en15124263.

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This scientific paper aims to increase the voltage source converter (VSC) control efficiency in a multi-terminal high voltage direct current (MTDC) network during dynamic operations. In the proposed study, the Mayfly algorithm (MA) is used to modify the control parameters of VSC stations. Traditional strategies that modify VSC control settings using approximate linear models fail to produce optimal results because VSCs are nonlinear characteristics of the MTDC system. Particle swarm optimization (PSO) may produce optimal outcomes, but it is prone to becoming stuck in a local optimum. To modify

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Kyomugisha, Rebeccah, Christopher Maina Muriithi, and George Nyauma Nyakoe. "Performance of Various Voltage Stability Indices in a Stochastic Multiobjective Optimal Power Flow Using Mayfly Algorithm." Journal of Electrical and Computer Engineering 2022 (April 29, 2022): 1–22. http://dx.doi.org/10.1155/2022/7456333.

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The performance of voltage stability indices in the multiobjective optimal power flow of modern power systems is presented in this work. Six indices: the Voltage Collapse Proximity Index (VCPI), Line Voltage Stability Index (LVSI), Line Stability Index (Lmn), Fast Voltage Stability Index (FVSI), Line Stability Factor (LQP), and Novel Line Stability Index (NLSI) were considered as case studies on a modified IEEE 30-bus consisting of thermal, wind, solar and hybrid wind-hydro generators. A multiobjective evaluation using the multiobjective mayfly algorithm (MOMA) was performed in two operational

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Bhattacharyya, Trinav, Bitanu Chatterjee, Pawan Kumar Singh, Jin Hee Yoon, Zong Woo Geem, and Ram Sarkar. "Mayfly in Harmony: A New Hybrid Meta-Heuristic Feature Selection Algorithm." IEEE Access 8 (2020): 195929–45. http://dx.doi.org/10.1109/access.2020.3031718.

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Dodda, Ratnam, and Alladi Suresh Babu. "Text document clustering using mayfly optimization algorithm with k-means technique." Indonesian Journal of Electrical Engineering and Computer Science 35, no. 2 (2024): 1099. http://dx.doi.org/10.11591/ijeecs.v35.i2.pp1099-1109.

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Text clustering is a subfield of machine learning (ML) and natural language processing (NLP) that consists of grouping similar sentences or documents based on their content. However, insignificant features in the documents minimize the accuracy of information retrieval which makes it challenging for the clustering approach to efficiently cluster similar documents. In this research, the mayfly optimization algorithm (MOA) with a k-means approach is proposed for text document clustering (TDC) to effectively cluster similar documents. Initially, the data is obtained from Reuters-21678, 20-Newsgro

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Ratnam, Dodda Alladi Suresh Babu. "Text document clustering using mayfly optimization algorithm with k-means technique." Indonesian Journal of Electrical Engineering and Computer Science 35, no. 2 (2024): 1099–109. https://doi.org/10.11591/ijeecs.v35.i2.pp1099-1109.

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Text clustering is a subfield of machine learning (ML) and natural language processing (NLP) that consists of grouping similar sentences or documents based on their content. However, insignificant features in the documents minimize the accuracy of information retrieval which makes it challenging for the clustering approach to efficiently cluster similar documents. In this research, the mayfly optimization algorithm (MOA) with a k-means approach is proposed for text document clustering (TDC) to effectively cluster similar documents. Initially, the data is obtained from Reuters-21678, 20-Newsgro

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Mukase, Sandrine, and Kewen Xia. "Multi-Objective Optimization with Mayfly Algorithm for Periodic Charging in Wireless Rechargeable Sensor Networks." World Electric Vehicle Journal 13, no. 7 (2022): 120. http://dx.doi.org/10.3390/wevj13070120.

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Wireless energy transfer (WET) is a revolutionary method that has the power to tackle the energy and longevity challenges in wireless sensor networks (WSN). This paper uses a mobile charger (MC) to discover the procedure of WET based on a wireless sensor network (WSN) for a periodic charging technique to maintain the network operational. The goal of this work is to lower overall system energy consumption and total distance traveled while increasing the mobile charger device vacation time ratio. Based on an analysis of total energy consumption, a new metaheuristic called mayfly algorithm (MA) i

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Hui, Jizhuang, Shaowei Zhi, Weichen Liu, Changhao Chu, and Fuqiang Zhang. "An Integrated Implementation Framework for Warehouse 4.0 Based on Inbound and Outbound Operations." Mathematics 13, no. 14 (2025): 2276. https://doi.org/10.3390/math13142276.

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Warehouse 4.0 adopts automation, IoT, and big data technologies to establish an intelligent warehousing system for efficient, real-time management of storage, handling, and picking. Addressing challenges like unreasonable storage allocation and inefficient order fulfillment, this paper presents an integrated framework that utilizes swarm intelligence algorithms and collaborative scheduling strategies to optimize inbound/outbound operations. First, for inbound processes, an algorithm-driven storage allocation model is proposed to solve stacker crane scheduling problems. Then, for outbound opera

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Olaniyan, Olatayo Moses, Ayobami Taiwo Olusesi, Bolaji Abigail Omodunbi, Wajeed Bolanle Wahab, Olusogo Julius Adetunji, and Bamidele Musiliu Olukoya. "A Data Security Model for Mobile Ad Hoc Network Using Linear Function Mayfly Advanced Encryption Standard." International Journal of Emerging Technology and Advanced Engineering 13, no. 3 (2023): 101–10. http://dx.doi.org/10.46338/ijetae0323_10.

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Mobile Ad Hoc network (MANET) is a connection of mobile nodes that are joined together to communicate and share information using a wireless link.Some of the MANET in use include mobile smart phones, laptops, personal digital assistant (PDAs), among others.However, MANET has been known for the major challenge of being vulnerable to malicious attacks within the network. One of the techniques which have been used by several research works is the cryptographic approach using advanced encryption technique (AES). AES has been found suitable in the MANET domain because it does not take much space in

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Lim, Ming K., Yan Li, Chao Wang, and Ming-Lang Tseng. "Prediction of cold chain logistics temperature using a novel hybrid model based on the mayfly algorithm and extreme learning machine." Industrial Management & Data Systems 122, no. 3 (2022): 819–40. http://dx.doi.org/10.1108/imds-10-2021-0607.

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PurposeThe transportation of fresh food requires cold chain logistics to maintain a low-temperature environment, which can reduce food waste and ensure product safety. Therefore, temperature control is a major challenge that cold chain logistics face.Design/methodology/approachThis research proposes a prediction model of refrigerated truck temperature and air conditioner status (air speed and air temperature) based on hybrid mayfly algorithm (MA) and extreme learning machine (ELM). To prove the effectiveness of the proposed method, the mayfly algorithm–extreme learning machine (MA-ELM) is comp

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Hu, Aihua, Zhongliang Deng, Hui Yang, Yao Zhang, Yuhui Gao, and Di Zhao. "An Optimal Geometry Configuration Algorithm of Hybrid Semi-Passive Location System Based on Mayfly Optimization Algorithm." Sensors 21, no. 22 (2021): 7484. http://dx.doi.org/10.3390/s21227484.

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In view of the demand of location awareness in a special complex environment, for an unmanned aerial vehicle (UAV) airborne multi base-station semi-passive positioning system, the hybrid positioning solutions and optimized site layout in the positioning system can effectively improve the positioning accuracy for a specific region. In this paper, the geometric dilution of precision (GDOP) formula of a time difference of arrival (TDOA) and angles of arrival (AOA) hybrid location algorithm is deduced. Mayfly optimization algorithm (MOA) which is a new swarm intelligence optimization algorithm is

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Qassem, Deema Yahya, and Najla Akram Al_saati. "A Solution to the Next Release Problem by Swarm Intelligence." Technium: Romanian Journal of Applied Sciences and Technology 12 (August 22, 2023): 58–64. http://dx.doi.org/10.47577/technium.v12i.9439.

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First of all, in this research, we solve the problem of the next release ((NRP) (Next Release Problem)), which is classified as a multi-objective difficult problem (NP_ hard problem) using swarm intelligence, since the programs are spread in all areas of our life and process The development on it is constantly ongoing and the selection of the optimal requirements to satisfy customers for the following versions is a very important process, as the requirements that have been dealt with are complicated due to interdependence and other limitations. Therefore, we will highlight it in our research t

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Mo, Shixun, Qintao Ye, Kunping Jiang, Xiaofeng Mo, and Gengyu Shen. "An improved MPPT method for photovoltaic systems based on mayfly optimization algorithm." Energy Reports 8 (August 2022): 141–50. http://dx.doi.org/10.1016/j.egyr.2022.02.160.

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Jayagayathri, I., and C. Mythili. "Inertia weight updated mayfly optimisation algorithm-based thermal breast cancer image segmentation." International Journal of Bio-Inspired Computation 22, no. 3 (2023): 139–51. http://dx.doi.org/10.1504/ijbic.2023.135469.

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Jaber, Fatimah. "PID CONTROLLER FOR SPEED CONTROL OF PMSM BASED ON MAYFLY OPTIMIZATION ALGORITHM." Kufa Journal of Engineering 16, no. 1 (2025): 104–20. https://doi.org/10.30572/2018/kje/160107.

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Permanent magnet synchronous motor (PMSM) is extensively employed in AC servo drives owing to their superior torque-to-inertia ratio, power density, efficiency, and power factor compared to other motors. So, it is a crucial point to regulate the PMSM speed. Conventional proportional, integral, and differential (PID) is a simple controller and easy to implement but it is coefficients are essentially determined by experience when used in PMSM to control the speed. This invariably produces unacceptable outcomes, in addition when it comes to low-power application drives, PID controller gains typic

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Boopathi, Dhanasekaran, Kaliannan Jagatheesan, Baskaran Anand, Sourav Samanta, and Nilanjan Dey. "Frequency Regulation of Interlinked Microgrid System Using Mayfly Algorithm-Based PID Controller." Sustainability 15, no. 11 (2023): 8829. http://dx.doi.org/10.3390/su15118829.

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The primary goal of this article is to design and implement a secondary controller with which to control the system frequency in a networked microgrid system. The proposed power system comprises of Renewable energy sources (RESs), energy-storing units (ESUs), and synchronous generator. RESs include photovoltaic (PV) and wind turbine generator (WTG) units. The ESU is composed of a flywheel and a battery. Because renewable energy sources are not constant in nature, their values fluctuate from time to time, causing an effect on system frequency and power flow variation in the tie line. The nonlin

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Qian, Weifeng, Hao Sun, Peng Shi, and Imre Rudas. "A General Chip Subpixel Segmentation Localization Method Based on Improved Mayfly Algorithm." Acta Polytechnica Hungarica 21, no. 10 (2024): 331–48. http://dx.doi.org/10.12700/aph.21.10.2024.10.21.

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Yildiz, Betül Sultan, Sujin Bureerat, Natee Panagant, Pranav Mehta, and Ali Riza Yildiz. "Reptile search algorithm and kriging surrogate model for structural design optimization with natural frequency constraints." Materials Testing 64, no. 10 (2022): 1504–11. http://dx.doi.org/10.1515/mt-2022-0048.

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Abstract This study explores the use of a recent metaheuristic algorithm called a reptile search algorithm (RSA) to handle engineering design optimization problems. It is the first application of the RSA to engineering design problems in literature. The RSA optimizer is first applied to the design of a bolted rim, which is constrained optimization. The developed algorithm is then used to solve the optimization problem of a vehicle suspension arm, which aims to solve the weight reduction under natural frequency constraints. As function evaluations are achieved by finite element analysis, the Kr

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