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Gotowe bibliografie tematyczne / Salp swarm optimization

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Gotowa bibliografia na temat „Salp swarm optimization”

Autor: Grafiati

Data publikacji: 2 czerwca 2025

Data aktualizacji: 31 lipca 2025

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Artykuły w czasopismach na temat "Salp swarm optimization"

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Castelli, Mauro, Luca Manzoni, Luca Mariot, Marco S. Nobile, and Andrea Tangherloni. "Salp Swarm Optimization: A critical review." Expert Systems with Applications 189 (March 2022): 116029. http://dx.doi.org/10.1016/j.eswa.2021.116029.

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Kulhari, Ankur, and Anil Saroliya. "Lévy-inspired Salp Swarm Optimization Algorithm." Procedia Computer Science 260 (2025): 796–804. https://doi.org/10.1016/j.procs.2025.03.260.

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Chabane, Djabali, and Bouktir Tarek. "SIMULTANEOUS ALLOCATION OF MULTIPLE DISTRIBUTED GENERATION AND CAPACITORS IN RADIAL NETWORK USING GENETIC-SALP SWARM ALGORITHM." Electrical engineering & electromechanics, no. 4 (August 21, 2020): 59–66. https://doi.org/10.20998/2074-272X.2020.4.08.

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<strong><em>Purpose. In recent years, the problem of allocation of distributed generation and capacitors banks has received special attention from many utilities and researchers. The present paper deals with single and simultaneous placement of dispersed generation and capacitors banks in radial distribution network with different load levels: light, medium and peak using genetic-salp swarm algorithm. The developed genetic-salp swarm algorithm (GA-SSA) hybrid optimization takes the system input variables of radial distribution network to find the optimal solutions to maximize the benefits of t

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Yıldız, Ali Rıza, and Mehmet Umut Erdaş. "A new Hybrid Taguchi-salp swarm optimization algorithm for the robust design of real-world engineering problems." Materials Testing 63, no. 2 (2021): 157–62. http://dx.doi.org/10.1515/mt-2020-0022.

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Abstract In this paper, a new hybrid Taguchi salp swarm algorithm (HTSSA) has been developed to speed up the optimization processes of structural design problems in industry and to approach a global optimum solution. The design problem is posed for the shape optimization of a seat bracket with a mass objective function and a stress constraint. Objective function evaluations are based on finite element analysis, while the response surface method is used to obtain the equations necessary for objective and constraint functions. Recent optimization techniques such as the salp swarm algorithm, gras

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Fan, Yuqi, Junpeng Shao, Guitao Sun, and Xuan Shao. "A Modified Salp Swarm Algorithm Based on the Perturbation Weight for Global Optimization Problems." Complexity 2020 (November 18, 2020): 1–17. http://dx.doi.org/10.1155/2020/6371085.

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Metaheuristic algorithms are often applied to global function optimization problems. To overcome the poor real-time performance and low precision of the basic salp swarm algorithm, this paper introduces a novel hybrid algorithm inspired by the perturbation weight mechanism. The proposed perturbation weight salp swarm algorithm has the advantages of a broad search scope and a strong balance between exploration and exploitation and retains a relatively low computational complexity when dealing with numerous large-scale problems. A new coefficient factor is introduced to the basic salp swarm algo

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Somasundaram, Deepa, Sasikala Arumugham, Puviarasi Ramalingam, Kirubakaran Dhandapani, and Kalaivani Ramaiyan. "Optimal fuzzy controller for speed control of DC drive using salp swarm algorithm." International Journal of Power Electronics and Drive Systems (IJPEDS) 15, no. 3 (2024): 1951. http://dx.doi.org/10.11591/ijpeds.v15.i3.pp1951-1958.

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The inherent non-linearity of the system being investigated highlights the limitations of traditional proportional integral or PI tuning approaches. Consequently, the primary objective of this study is to construct and refine the PI controller by leveraging the salp swarm algorithm, aiming to enhance the performance of the DC drive output. Through the application of the salp swarm algorithm, the fuzzy PI controller undergoes dynamic online modifications, leading to optimal results. The controller's superior performance is achieved by employing an optimization approach to identify the optimal s

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Somasundaram, Deepa, Sasikala Arumugham, Puviarasi Ramalingam, Kirubakaran Dhandapani, and Kalaivani Ramaiyan. "Optimal fuzzy controller for speed control of DC drive using salp swarm algorithm." International Journal of Power Electronics and Drive Systems (IJPEDS) 15, no. 3 (2024): 1951–58. https://doi.org/10.11591/ijpeds.v15.i3.pp1951-1958.

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The inherent non-linearity of the system being investigated highlights the limitations of traditional proportional integral or PI tuning approaches. Consequently, the primary objective of this study is to construct and refine the PI controller by leveraging the salp swarm algorithm, aiming to enhance the performance of the DC drive output. Through the application of the salp swarm algorithm, the fuzzy PI controller undergoes dynamic online modifications, leading to optimal results. The controller's superior performance is achieved by employing an optimization approach to identify the optimal s

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Duan, Qing, Lu Wang, Hongwei Kang, Yong Shen, Xingping Sun, and Qingyi Chen. "Improved Salp Swarm Algorithm with Simulated Annealing for Solving Engineering Optimization Problems." Symmetry 13, no. 6 (2021): 1092. http://dx.doi.org/10.3390/sym13061092.

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Swarm-based algorithm can successfully avoid the local optimal constraints, thus achieving a smooth balance between exploration and exploitation. Salp swarm algorithm(SSA), as a swarm-based algorithm on account of the predation behavior of the salp, can solve complex daily life optimization problems in nature. SSA also has the problems of local stagnation and slow convergence rate. This paper introduces an improved salp swarm algorithm, which improve the SSA by using the chaotic sequence initialization strategy and symmetric adaptive population division. Moreover, a simulated annealing mechani

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Cheruiyot, Fabian, and Davies Segera. "A Master-Slave Salp Swarm Algorithm Optimizer for Hybrid Energy Storage System Control Strategy in Electric Vehicles." Journal of Energy 2022 (September 14, 2022): 1–20. http://dx.doi.org/10.1155/2022/1648433.

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Pure electric vehicles provide an enticing ecofriendly alternative to traditional fossil fuel combustion engine locomotives. Batteries have primarily been used to store energy in electric vehicles; however, peak load demand and transient power leading to decreased battery lifespan have bred interest in hybrid energy storage systems in electric vehicles. Management of energy drawn from a hybrid energy storage system (HESS) in electric vehicles is a real-time multistage optimization problem aimed at minimizing energy consumption while aptly distributing energy drawn from the battery and capacito

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Yang, Heng, Yuhang Ren, and Gening Xu. "Optimization of Rotary Drilling Rig Mast Structure Based on Multi-Dimensional Improved Salp Swarm Algorithm." Applied Sciences 14, no. 21 (2024): 10040. http://dx.doi.org/10.3390/app142110040.

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The mast is a critical component of rotary drilling rigs, which has a cross-section consisting of a rectangular shape formed by two web plates and two flange plates. Structural optimization of the mast is necessary to address the issue of excessive weight. The shortcomings of the traditional structural optimization algorithms are summarized as follows: the optimized steel plate thickness is a non-integer, where rounding upwards may increase the cost to a certain extent, but it can ensure the safety of the structure; rounding downwards its load carrying capacity may not satisfy the requirements

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Części książek na temat "Salp swarm optimization"

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Jain, Shashank. "Sea Creatures: Salp Swarm Optimization." In Nature-Inspired Optimization Algorithms with Java. Apress, 2021. http://dx.doi.org/10.1007/978-1-4842-7401-9_5.

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Kashani, Ali R., Saman Ebrahimi, and Charles V. Camp. "Salp Swarm Algorithm for Optimization of Shallow Foundations." In Handbook of Formal Optimization. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-3820-5_33.

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Kashani, Ali R., Saman Ebrahimi, and Charles V. Camp. "Salp Swarm Algorithm for Optimization of Shallow Foundations." In Handbook of Formal Optimization. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-8851-6_33-1.

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Rani, Nibha, and Tanmoy Malakar. "Enhancement of Reactive Power Reserve Using Salp Swarm Algorithm." In Modeling, Simulation and Optimization. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-9829-6_27.

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Bairathi, Divya, and Dinesh Gopalani. "Opposition Based Salp Swarm Algorithm for Numerical Optimization." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-16660-1_80.

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Nasri, Dallel, and Diab Mokeddem. "Improved Salp Swarm Optimization Algorithm for Engineering Problems." In Advances in Computing Systems and Applications. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-12097-8_22.

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Khaitana, Supriya, Shrddha Sagar, and Rashi Agarwal. "Chaos-Based Image Encryption with Salp Swarm Key Optimization." In Emerging Technologies in Data Mining and Information Security. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-4193-1_32.

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Rekha, Gillala, V. Krishna Reddy, and Amit Kumar Tyagi. "Chaotic Salp Swarm Optimization Using SVM for Class Imbalance Problems." In Hybrid Intelligent Systems. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-49336-3_22.

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Mondal, Amiya Kumar, and Prerna Saxena. "Synthesis of Thinned Antenna Arrays Using Salp Swarm Optimization Techniques." In Lecture Notes in Electrical Engineering. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-2761-3_78.

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Yu, Jin-tao, He Tong, Xiao-wei Lu, Zhen-hua Gao, and Dai-zhi Jin. "Coverage Optimization of WSN Based Upon Improved Salp Swarm Algorithm." In Smart Innovation, Systems and Technologies. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-3980-6_2.

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Streszczenia konferencji na temat "Salp swarm optimization"

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Agrawal, Deepika. "Cluster Head Selection in IoT Networks Using Salp Swarm Optimization." In 2024 IEEE 1st International Conference on Advances in Signal Processing, Power, Communication, and Computing (ASPCC). IEEE, 2024. https://doi.org/10.1109/aspcc62191.2024.10881286.

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Zorig, Anwar, Reda Achdad, Ahmed Belkheiri, Abdelhamid Rabhi, and Mohammed Belkheiri. "BLDC Motor Parameter Identification using Metaheuristic Optimization: Salp Swarm Algorithm." In 2025 33rd Mediterranean Conference on Control and Automation (MED). IEEE, 2025. https://doi.org/10.1109/med64031.2025.11073218.

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Li, Guangqiang, Ruoxi Liu, Lehao Xie, Hao Chen, Xinyue Chen, and Xunkai Zhu. "Location optimization of logistics distribution centers based on improved salp swarm algorithm." In Fourth International Conference on Advanced Algorithms and Neural Networks (AANN 2024), edited by Qinghua Lu and Weishan Zhang. SPIE, 2024. http://dx.doi.org/10.1117/12.3049688.

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Pathak, Sanjai, Ashish Mani, and Amlan Chatterjee. "Quantum Delta Potential Inspired Salp Swarm Optimization Algorithm with Parameter Adaptation Approach." In 2024 IEEE 21st India Council International Conference (INDICON). IEEE, 2024. https://doi.org/10.1109/indicon63790.2024.10958296.

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Adamu, Shamsuddeen, Hitham Siddig A. A, Said Jadid Abdulkadir, et al. "Optimizing Cancer Gene Selection with Salp Swarm Optimization and Ensemble Filtering Techniques." In 2024 16th International Conference on Knowledge and System Engineering (KSE). IEEE, 2024. https://doi.org/10.1109/kse63888.2024.11063581.

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Cai, Tianrun, Jinpeng Wen, Xian Jiang, et al. "Advanced Salp Swarm Algorithm Based Hyper-Parameter Optimization for Cell-Level Traffic Prediction Model." In 2024 6th International Conference on Data-driven Optimization of Complex Systems (DOCS). IEEE, 2024. http://dx.doi.org/10.1109/docs63458.2024.10704378.

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Patil, Sidagouda Basagouda, and Mukund A. Kulkarni. "Symmetric Adaptive Population Division Based Salp Swarm Algorithm for Resource Optimization in Cloud Computing." In 2024 International Conference on Intelligent Algorithms for Computational Intelligence Systems (IACIS). IEEE, 2024. http://dx.doi.org/10.1109/iacis61494.2024.10721697.

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Hussein, Layth, K. Sudheer Kumar, S. Trisheela, R. Rana Veer Samara Sihman Bharattej, and Jajimoggala Sravanthi. "Modified Salp Swarm Optimization for Mobile Secure Routing in Intrusion Detection System for Wireless Sensor Network." In 2024 Second International Conference on Networks, Multimedia and Information Technology (NMITCON). IEEE, 2024. http://dx.doi.org/10.1109/nmitcon62075.2024.10699289.

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Gu, Nanhui, Zairan Liu, Xiaotong Ren, Yuting Tao, and Yang Li. "Optimization of Local Energy Internet Based on a Multi-objective Linear Weighted Sum Salp Swarm Algorithm." In 2024 IEEE 8th Conference on Energy Internet and Energy System Integration (EI2). IEEE, 2024. https://doi.org/10.1109/ei264398.2024.10991932.

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Shen, Xue. "Research on 3D Digital Clothing Design Based on Optimized Capsule Network Using Enhanced Salp Swarm Optimization Algorithm." In 2024 International Conference on Data Science and Network Security (ICDSNS). IEEE, 2024. http://dx.doi.org/10.1109/icdsns62112.2024.10690948.

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