FCC algorithm for power loss diminution by Kanagasabai L.

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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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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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Non-Vertical Well Trajectory Design Based on Multi-Objective Optimization by Xiaowei Li, Yu Li, Yang Wu, Zhaokai Hou, Haipeng Gu

“…The optimization and control of the wellbore trajectory is one of the important technologies to improve drilling efficiency, reduce drilling cost, and ensure drilling safety in the process of modern oil and gas exploration and development. …”
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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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Stability Analysis and Construction Parameter Optimization of Tunnels in the Fractured Zone of Faults by Banma Huang, Haibo Chen, Chenglong Duan, Wenhu Li

“…In order to improve the construction method of highway tunnel fault, improve the excavation level, improve the construction efficiency, reduce the project cost, and shorten the construction period, so as to find a specific road, this paper puts forward the research method of tunnel stability analysis and construction parameter optimization in the fault fracture zone. …”
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A Review of Smart Camera Sensor Placement in Construction by Wei Tian, Hao Li, Hao Zhu, Yongwei Wang, Xianda Liu, Rongzheng Yang, Yujun Xie, Meng Zhang, Jun Zhu, Xiangyu Wang

“…Simultaneously, Building Information Modeling is employed to consider the progress of construction and visualize optimized layouts, improving the effect of CSP. …”
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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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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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Investigating the Performance of Open-Vocabulary Classification Algorithms for Pathway and Surface Material Detection in Urban Environments by Kauê de Moraes Vestena, Silvana Phillipi Camboim, Maria Antonia Brovelli, Daniel Rodrigues dos Santos

“…Our approach uses large language models (LLMs) to improve the accuracy of classifying different pavement types. …”
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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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Optimizing Photovoltaic Panel Performance: A Comparative Study of Meta-Heuristic Algorithms by M. Sundar Rajan

“…This paper addresses the parameter estimation of four distinct PV panel models—PV-RTC, PV-PWP 201, PV-STM6 40/36, and PV-STP6 120/36—using a range of meta-heuristic optimization algorithms. …”
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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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Optimizing Imbalanced Data Classification: Under Sampling Algorithm Strategy with Classification Combination by Nauval Dwi Primadya, Adhitya Nugraha, Sahrul Yudha Fahrezi, Ardytha Luthfiarta

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An automated software algorithm for optimizing microwave ablation parameters for treatment of liver tumors by Sabrina Q. R. Liew, Nathaniel Rex, Celina Hsieh, Hyeonseon Kim, Scott A. Collins, Grayson L. Baird, DaeHee Kim, Aaron W. P. Maxwell

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Application of Improved Fault Detection and Robust Adaptive Algorithm in GNSS/INS Integrated Navigation by Qinghai Wang, Jianghua Liu, Jinguang Jiang, Xianrui Pang, Zhimin Ge

“…In vehicle GNSS/INS integrated navigation, robust and adaptive algorithms have become one of the key technologies for achieving a comprehensive PNT due to their ability to control the gross errors of the observation model and dynamic model. …”
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