Optimizing firefighting resilience in airports through genetic algorithms and decision-making frameworks by Yulong Zhu, Wei Tian, Xuhong Jia, Quanyi Liu

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Multiobjective Optimization of Irreversible Thermal Engine Using Mutable Smart Bee Algorithm by M. Gorji-Bandpy, A. Mozaffari

“…The results have been checked with some of the most common optimizing algorithms like Karaboga’s original artificial bee colony, bees algorithm (BA), improved particle swarm optimization (IPSO), Lukasik firefly algorithm (LFFA), and self-adaptive penalty function genetic algorithm (SAPF-GA). …”
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Algorithm on joint optimization of power allocation and slot allocation in satellite communication systems by Han HAN, Ying LI, Xu DONG, Xiao-bo GUO, Qin-fei HUANG

“…An algorithm to jointly optimize the power allocation and the slot allocation in order to improve the utilization efficiency of the limited resources on the satellite was proposed.The basic principles of the mutual compensation and mutual independence between these two resources are explored to pave the way for joint optimization.Considering the differences about each station’s channel condition and capacity requirement,a state-combination model for optimally allocating the resources is setted up,so as to adapt the multi-resource usage pattern with each earth station.Targeting at the energy efficiency,an iterative dual optimization algorithm is proposed,and the final optimal policy for resource allocation with low complexity is obtained.With the simulation and analysis,the proposed joint optimization is verified to perform better than the non-joint ones in the perspective of the energy efficiency,especially when the frequency resource (the carrier number) is less.…”
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Optimization of Communication Quality for Energy-Limited Inspection AAV: A Hybrid Algorithm by Wei Wang, Jiangling Cao, Dingcheng Yang, Hao He, Zhihai Xu

“…Numerical results show that the proposed algorithm is effective in optimizing the communication quality of the inspection AAV with limited energy, and its performance is improved by about 15%-50% compared with other benchmarks.…”
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A navigation satellite selection algorithm for optimized positioning based on Gibbs sampler by Na Xia, Qinan Zhi, Menghua He, Yunqing Hong, Huazheng Du

“…In addition, the scheme is updated by the conditional probability distribution model of the Gibbs sampler algorithm, and it gradually approaches the global optimal solution of the satellite combination with better geometric distribution of the space satellite. …”
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A Novel Optimization Algorithm for Modifying the Parameter Unit of Solar PV Cell by V. Senthil Nayagam, S. Sanal Kumar, V. Thiyagarajan, Neel Kamal, N. Nisha, J. Samson Isaac, Adane Kassa

“…As a result, combining these two mechanisms can considerably improve the whale optimization algorithm capacity to find the optimal answer. …”
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Graph neural processes for molecules: an evaluation on docking scores and strategies to improve generalization by Miguel García-Ortegón, Srijit Seal, Carl Rasmussen, Andreas Bender, Sergio Bacallado

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Adaptive Particle Swarm Optimization with Landscape Learning for Global Optimization and Feature Selection by Khalil Abbal, Mohammed El-Amrani, Oussama Aoun, Youssef Benadada

“…Particle swarm optimization (PSO), an important solving method in the field of swarm intelligence, is recognized as one of the most effective metaheuristics for addressing optimization problems. …”
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Optimizing diabetic retinopathy detection with electric fish algorithm and bilinear convolutional networks by Udayaraju Pamula, Venkateswararao Pulipati, G. Vijaya Suresh, M. V. Jagannatha Reddy, Anil Kumar Bondala, Srihari Varma Mantena, Ramesh Vatambeti

“…To enhance classification accuracy, the system introduces a hybrid Electric Fish Optimization Arithmetic Algorithm (EFAOA), which refines the exploration phase, ensuring rapid convergence. …”
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The optimal route search in Bengaluru city transport using Hamilton circuit algorithm by Parkavi S, Parthiban A

“…So, drawing inspiration and motivation from the outstanding work of Mungporn, Pongsiri et al., “Modeling and control of multiphase interleaved fuel-cell boost converter based on Hamiltonian control theory for transportation applications, IEEE Transactions on Transportation Electrification 6.2, 2020, pp. 519-529”, in this paper, we study an intelligent agent model to perform route engineering for public transportation in the Bengaluru city, based on the Hamilton circuit algorithm and analyze the best and optimal route among the three significant routes out of twelve available using various parameters. …”
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IGWO-MALSTM: An Improved Grey Wolf-Optimized Hybrid LSTM with Multi-Head Attention for Financial Time Series Forecasting by Mingfu Zhu, Haoran Qi, Panke Qin

“…The IGWO algorithm improves population diversity during initialization using the Mersenne Twister, thereby enhancing the convergence speed and search capability of the optimizer. …”
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Reducing hydrogen consumption in hybrid electric vehicles using aquila optimization algorithm by A.M. Nassef, H.E. Ghadbane, E.T. Sayed, H. Rezk

“…The aquila optimization algorithm is one of the most recent and efficient algorithms. …”
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Study on Trajectory Optimization for a Flexible Parallel Robot in Tomato Packaging by Tianci Guo, Jiangbo Li, Yizhi Zhang, Letian Cai, Qicheng Li

“…To improve the efficiency of the tomato packaging process, a hybrid algorithm combining particle swarm optimization (PSO) and genetic algorithms (GA) was developed to optimize the operation time of the parallel robot. …”
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Multi-Level Particle System Modeling Algorithm with WRF by Julong Chen, Bin Wang, Rundong Gan, Xuepeng Mou, Shiping Yang, Ling Tan

“…To improve modeling efficiency, cascade Bezier curves are designed at different line-of-sights (LoSs), utilizing the weight information of boundary particles to optimize cloud contours. …”
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Autonomous Parking Path Planning Method for Intelligent Vehicles Based on Improved RRT Algorithm by Jian Chen, Rongqi Ma, Cunhao Lu, Yaoji Deng

“…Firstly, the environment is modelled by the raster method; then, the PSBi-RRT algorithm is used for path planning, and a B-spline curve is used for path optimization. …”
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Improved DBO algorithm tunes fuzzy-PD controller for robot manipulator trajectory tracking by Ma Haohao, Azizan As’arry, Li Chaoqun, Mohd Idris Shah Ismail, Hafiz Rashidi Ramli, Aidin Delgoshaei, M.Y.M. Zuhri

“…Based on the dynamic modeling of the robot manipulator, the PD control law is designed, and the improved dung beetle optimization (DBO) algorithm is introduced using the good point set (GPS) method for population initialization and the sine strategy for convergence factor adjustment. …”
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An Improved Interpolation Algorithm for Surface Meteorological Observations via Fuzzy Adaptive Optimisation Fusion by Xiaoya Jiang, Xiong Xiong, Wenlan Wang, Xiaoling Ye, Xin Chen, Yihu Wang, Fangjian Zhang

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The algorithm of the engineering method of parameter optimization dump working equipment of the motor grader by Ignatov S.D.

“…This paper presents an analysis of existing motor grader blade equipment designs, develops an engineering methodology optimization algorithm, and examines the main stages of its implementation, including modeling, iterative optimization procedures, and experimental validation. …”
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Joint beam hopping and coverage control optimization algorithm for multibeam satellite system by Guoliang XU, Feng TAN, Yongyi RAN, Feng CHEN

“…To improve the performance of multibeam satellite (MBS) systems, a deep reinforcement learning-based algorithm to jointly optimize the beam hopping and coverage control (BHCC) algorithm for MBS was proposed.Firstly, the resource allocation problem in MBS was transformed to a multi-objective optimization problem with the objective maximizing the system throughput and minimizing the packet loss rate of the MBS.Secondly, the MBS environment was characterized as a multi-dimensional matrix, and the objective problem was modelled as a Markov decision process considering stochastic communication requirements.Finally, the objective problem was solved by combining the powerful feature extraction and learning capabilities of deep reinforcement learning.In addition, a single-intelligence polling multiplexing mechanism was proposed to reduce the search space and convergence difficulty and accelerate the training of BHCC.Compared with the genetic algorithm, the simulation results show that BHCC improves the throughput of MBS and reduces the packet loss rate of the system, greedy algorithm, and random algorithm.Besides, BHCC performs better in different communication scenarios compared with a deep reinforcement learning algorithm, which do not consider the adaptive beam coverage.…”
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Swarm Intelligence Algorithms for Optimization Problems a Survey of Recent Advances and Applications by Mande Smita Samrat, M Srinivasulu, Anand Sruthi, K Anuradha, Tiwari Mohit, U Esakkiammal

“…For many years swarm intelligence (SI) algorithms have shown successful performance for complex optimization problems in many fields. …”
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