Article
Mathematics
Amir Masoud Rahmani, Saqib Ali, Mohammad Sadegh Yousefpoor, Efat Yousefpoor, Rizwan Ali Naqvi, Kamran Siddique, Mehdi Hosseinzadeh
Summary: This study proposed an optimal area coverage method for wireless sensor networks, including calculating overlap, designing fuzzy scheduling, predicting node replacement time, and reconstructing network holes. Simulation results showed that the proposed scheme outperformed other methods in various performance metrics.
Article
Computer Science, Interdisciplinary Applications
Milad Sharifipour, Ali Nakhaee, Reza Yousefzadeh, Mojtaba Gohari
Summary: The study successfully applied the SFLA algorithm to the well placement problem, achieving better results compared to other algorithms in reservoir optimization.
COMPUTATIONAL GEOSCIENCES
(2021)
Article
Energy & Fuels
Yun Liu, Ali Asghar Heidari, Xiaojia Ye, Chen Chi, Xuehua Zhao, Chao Ma, Hamza Turabieh, Huiling Chen, Rongrong Le
Summary: The study introduces an efficient solver called SFLBS for extracting unknown parameters in photovoltaic systems. Experimental results demonstrate that SFLBS performs well in parameter extraction and evaluation of commercial PV modules, with satisfactory convergence speed.
Article
Computer Science, Artificial Intelligence
Yao Huang, Xiao-Ning Shen, Xuan You
Summary: A discrete shuffled frog-leaping algorithm based on heuristic information is proposed for the traveling salesman problem, with four improved searching strategies to enhance the algorithm performance. Validation on TSP instances shows that the proposed algorithm outperforms classical and state-of-the-art algorithms in terms of accuracy and stability.
APPLIED SOFT COMPUTING
(2021)
Article
Computer Science, Artificial Intelligence
Yanika Kongsorot, Pakarat Musikawan, Paisarn Muneesawang, Chakchai So-In
Summary: Wireless sensor networks (WSNs), an important technology for the Internet of Things (IoT), consist of small sensor nodes communicating in a large-scale network. To address the limited battery capacity of each node, a clustering-based approach is used to conserve energy and increase network lifetime. This paper proposes an enhanced fuzzy-based clustering protocol optimized by an improved shuffled frog leaping algorithm (ISFLA) to maintain network lifetime. The experimental results show improved network lifetime, stability, and data packet delivery to the base station (BS).
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Computer Science, Artificial Intelligence
Yafei Dong, Quanwang Wu, Junhao Wen
Summary: The multiple traveling salesman problem (mTSP) is an extended version of the well-known traveling salesman problem, involving multiple salesmen visiting a set of cities, aiming to balance workload among salesmen or find the optimal solution when travel time is prioritized. The novel improved shuffled frog-leaping algorithm (ISFLA) proposed in this paper outperforms some state-of-the-art approaches for this problem, demonstrating its superiority in solving the minmax mTSP.
NEURAL COMPUTING & APPLICATIONS
(2021)
Article
Energy & Fuels
Yi Fan, Pengjun Wang, Ali Asghar Heidari, Xuehua Zhao, Hamza Turabieh, Huiling Chen
Summary: The importance of developing an accurate mathematical model for studying and optimizing PV systems has been emphasized, and a new algorithm called DDSFLA was proposed to address the low convergence accuracy issue in solving PV problems using SFLA. Testing on benchmark functions and extracting various models showed that the DDSFLA algorithm has better performance and stability.
Article
Computer Science, Interdisciplinary Applications
Lianguo Wang, Xiaojuan Liu
Summary: The improved shuffled frog leaping algorithm with contraction factor can learn from the best individual more effectively, accelerate the convergence rate, and enhance optimization accuracy.
ENGINEERING WITH COMPUTERS
(2022)
Article
Energy & Fuels
Yanxiao Wu, Jiaqi Li, Xincheng Tang, Zhuoer Yuan, Xinyu Dong, Zhenchang Fang, Chunhua Sun, Xinqi Qiao, Xinling Li
Summary: This study establishes a simplified mechanism for n-butanol using the decoupling methodology and optimizes the rate constants using the Shuffled Frog Leaping Algorithm. The optimized mechanism shows good agreement with experimental data and is computationally efficient. This study provides a theoretical basis for the application of n-butanol fuel.
Article
Nuclear Science & Technology
Fei Li, Xiao-Fei Huang, Yue-Lu Chen, Bing-Hai Li, Tang Wang, Feng Cheng, Guo-Qiang Zeng, Mu-Hao Zhang
Summary: An improved SFLA-PSO CNN method is proposed in this study for large-sample quantitative analysis of airborne gamma-ray spectra. The method trains the neural network weight, optimizes the network structure, and enables the network to perform quantitative spectrum processing. The results show that the algorithm has high processing efficiency and accuracy, and can meet the requirements of practical engineering measurement.
NUCLEAR SCIENCE AND TECHNIQUES
(2023)
Article
Multidisciplinary Sciences
Fei Li, Wentai Guo, Xiaotong Deng, Jiamei Wang, Liangquan Ge, Xiaotong Guan
Summary: This paper proposes an improved shuffled frog leaping algorithm of threshold oscillation based on simulated annealing (SA-TO-SFLA) to enhance the convergence accuracy and convergence time of the ensemble learning of swarm intelligence evolutionary algorithm of artificial neural network (ANN).
Article
Computer Science, Artificial Intelligence
Yi Chen, Mingjing Wang, Ali Asghar Heidari, Beibei Shi, Zhongyi Hu, Qian Zhang, Huiling Chen, Majdi Mafarja, Hamza Turabieh
Summary: In this study, a multi-strategy-driven shuffled frog leaping algorithm with horizontal and vertical crossover search (HVSFLA) is proposed for medical image segmentation. The algorithm achieves a better balance between diversification and intensification through horizontal and vertical crossover search. Experimental results demonstrate that HVSFLA outperforms other competing algorithms, showing great potential for medical image segmentation.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Computer Science, Information Systems
Rasmita Dash, Rajashree Dash, Rasmita Rautray
Summary: Microarray technology has been widely used in biomedical research, but its efficient application in this field remains challenging and expensive. This study proposes a new metaheuristic approach, utilizing binary shuffled frog leaping algorithm for gene selection, and demonstrates the superiority of the selected gene subset through comparison with various classifiers.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2022)
Article
Energy & Fuels
Xuemeng Weng, Ali Asghar Heidari, Huiling Chen
Summary: Accurate determination of photovoltaic (PV) parameters is crucial for the reliable operation of solar systems, uninterrupted power supply, and efficient energy management. This paper proposes a novel parameter extraction model using the Q-learning-based multistrategy improved shuffled frog leading algorithm (CRNSFLA). The comprehensive test results show that CRNSFLA outperforms existing algorithms in parameter extraction problems, making it an effective tool for solar cell parameter extractions.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2023)
Article
Computer Science, Artificial Intelligence
Yun Liu, Ali Asghar Heidari, Zhennao Cai, Guoxi Liang, Huiling Chen, Zhifang Pan, Abdulmajeed Alsufyani, Sami Bourouis
Summary: This paper proposes an improved shuffled frog leaping algorithm that incorporates dynamic step size adjustment, specular reflection learning, and simulated annealing mechanisms. Experimental results show that the algorithm achieves superior solutions and performs well in feature selection tasks.
