Applications of Machine Learning Algorithms in Geriatrics by Adrian Stancu, Cosmina-Mihaela Rosca, Emilian Marian Iovanovici

“…The integration of machine learning (ML)-type algorithms in geriatrics represents a direction for optimizing prevention, diagnosis, prediction, monitoring, and treatment. …”
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An Infrared Small Moving Target Detection Method in Complex Scenes Based on Dual-Region Search by Huazhao Cao, Yuxin Hu, Ziming Wang, Jianwei Yang, Guangyao Zhou, Wenzhi Wang, Yuhan Liu

“…The experimental outcomes show that, compared to alternative algorithms, the proposed approach outperforms others in terms of detection accuracy and speed, particularly in diverse real-world complex scenarios.…”
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Comparison of Innovative Strategies for the Coverage Problem: Path Planning, Search Optimization, and Applications in Underwater Robotics by Ahmed Ibrahim, Francisco F. C. Rego, Éric Busvelle

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Fractal Algorithm for Multiple-lens Analyses by F. Abe

“…There is no limit on the number of lenses that can be used with this algorithm. Compared to inverse-ray shooting, this method dramatically improves the computing time. …”
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GP4ESP: a hybrid genetic algorithm and particle swarm optimization algorithm for edge server placement by Fang Han, Hui Fu, Bo Wang, Yaoli Xu, Bin Lv

“…Due to NP-hardness of ESP, some works have designed meta-heuristic algorithms for solving it. While these algorithms either exploited only one kind of meta-heuristic search strategies or separately perform two different meta-heuristic algorithms. …”
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Feature selection algorithm based on XGBoost by Zhanshan LI, Zhaogeng LIU

“…Feature selection in classification has always been an important but difficult problem.This kind of problem requires that feature selection algorithms can not only help classifiers to improve the classification accuracy,but also reduce the redundant features as much as possible.Therefore,in order to solve feature selection in the classification problems better,a new wrapped feature selection algorithm XGBSFS was proposed.The thought process of building trees in XGBoost was used for reference,and the importance of features from three importance metrics was measured to avoid the limitation of single importance metric.Then the improved sequential floating forward selection (ISFFS) was applied to search the feature subset so that it had high quality.Compared with the experimental results of eight datasets in UCI,the proposed algorithm has good performance.…”
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Feature selection algorithm based on XGBoost by Zhanshan LI, Zhaogeng LIU

“…Feature selection in classification has always been an important but difficult problem.This kind of problem requires that feature selection algorithms can not only help classifiers to improve the classification accuracy,but also reduce the redundant features as much as possible.Therefore,in order to solve feature selection in the classification problems better,a new wrapped feature selection algorithm XGBSFS was proposed.The thought process of building trees in XGBoost was used for reference,and the importance of features from three importance metrics was measured to avoid the limitation of single importance metric.Then the improved sequential floating forward selection (ISFFS) was applied to search the feature subset so that it had high quality.Compared with the experimental results of eight datasets in UCI,the proposed algorithm has good performance.…”
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Voice recognition enhancement by genetic algorithm by Mohamed Salah Salhi, Ali Hamdan Alenezi

“…The findings suggest that the GA algorithm provides improved recognition rates and extends the search space to a global optimum, but can sometimes produce unacceptable results due to rapid and premature convergence and the overfitting problem. …”
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GRU-LSTM model based on the SSA for short-term traffic flow prediction by Changxi Ma, Xiaoyu Huang, Yongpeng Zhao, Tao Wang, Bo Du

“…To address this issue, this study proposes a hybrid model, sparrow search algorithm-gated recurrent unit-long short-term memory (SSA-GRU-LSTM), which leverages the SSA to optimize the GRUs and LSTM networks. …”
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Time-Dependent Vehicle Routing Problem with Drones Under Vehicle Restricted Zones and No-Fly Zones by Shuo Wei, Houming Fan, Xiaoxue Ren, Xiaolong Diao

“…Compared to the genetic neighborhood search algorithm and the hybrid genetic algorithm, the improvement rates are 5.1% and 13.0%, respectively. …”
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Research on the prediction of blasting fragmentation in open-pit coal mines based on KPCA-BAS-BP by Shuang Liu, Enxiang Qu, Chun LV, Xueyuan Zhang

“…The kernel principal component analysis (KPCA) is adopted to reduce the dimensionality of the input variables. The beetle antennae search algorithm (BAS) is selected to optimize the parameters of the initial weights and thresholds of the back propagation (BP) neural network. …”
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A Hybrid Strategy-Improved SSA-CNN-LSTM Model for Metro Passenger Flow Forecasting by Jing Liu, Qingling He, Zhikun Yue, Yulong Pei

“…Finally, we enhance the individual sparrow position update process by integrating a cosine strategy with an inertia weight adjustment, which improves the algorithm’s global search ability, effectively balancing global search and local exploitation, and reducing the risk of local optima and insufficient convergence precision. …”
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Energy-efficiency maximization scheme for data collection in wireless power communication networks by Haijiang GE, Zhanwei YU, Kaikai CHI

“…WPCN composed of multiple RF energy sources and sinks was studied.The energy efficiency of data collection were maximized by jointly optimizing the transmission power of energy sources,the time allocation of wireless energy transfer and the time allocation of nodes’ data transmission.Specifically,the energy efficiency maximization problem was modeled firstly.Then,the optimal value of transmitted power was obtained,and the monotonicity of energy-efficiency function and the convexity of throughput function were further deduced.Finally,based on these properties,an efficient algorithm which combines golden-section search and bisection search was designed to get the optimal solution quickly.The simulation results show that the proposed optimal algorithm can significantly improve the energy efficiency compared with the baseline scheme.…”
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An Adaptive Large Neighborhood Search for the Larger-Scale Instances of Green Vehicle Routing Problem with Time Windows by Zixuan Yu, Ping Zhang, Yang Yu, Wei Sun, Min Huang

“…In this paper, an adaptive large neighborhood search (ALNS) algorithm is proposed to solve large-scale instances of GVRP. …”
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An Analysis on the Applicability of Meta-Heuristic Searching Techniques for Automated Test Data Generation in Automatic Programming Assessment by Musa et al.

“…Several recent MHST are included in the comparative evaluation combining both the local and global search algorithms ranging from the year of 2000 until 2018. …”
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A simulated annealing with graph-based search for the social-distancing problem in enclosed areas during pandemics. by Bayram Dundar

“…A greedy random-based algorithm is presented to determine efficiently an initial feasible solution. …”
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An Interpretable Dynamic Feature Search Methodology for Accelerating Computational Process of Control Rod Descent in Nuclear Reactors by Qingyu Huang, Cong Xiao, Wei Zeng, Le Xu, Jia Liu, Zhixin Pang, Yuanfeng Lin, Mengwei Zhao, Xiaobo Liu

“…In light of this challenge, we present a novel and interpretative algorithm rooted in dynamic similarity feature search. …”
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Optimization and comparative analysis of hybrid renewable energy systems for sustainable and clean energy production in rural Cameroon considering the loss of power supply probabil... by Yemeli Wenceslas Koholé, Clint Ameri Wankouo Ngouleu, Fodoup Cyrille Vincelas Fohagui, Ghislain Tchuen

“…Three meta-heuristic algorithms namely, the water evaporation optimization, Cuckoo Search Algorithm (CSA), and teaching–learning-based optimization are applied, and the results are compared in terms of NPC, excess energy fraction, electricity demand fulfillment, and CO2 emission reduction. …”
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Driving range estimation for electric bus based on atomic orbital search and back propagation neural network by Hanchen Ke, Jun Bi, Yongxing Wang, Yu Zhang

“…Simulation and experimental analysis show that the algorithm introduced in this paper has higher prediction accuracy and efficiency compared to the traditional machine learning algorithms, that compared with BPNN, AOSBP reduced MAE, RMSE and MAPE by 85.6%, 50.9% and 64.6%, respectively, which effectively relieves range anxiety, and ensures the normal operation of the electric bus fleet.…”
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Individual tree segmentation in occluded complex forest stands through ellipsoid directional searching and point compensation by Qingjun Zhang, Shangshu Cai, Xinlian Liang

“…Secondly, the neighbor points are extracted within an ellipsoid neighborhood to mitigate occlusion effects compared with k-nearest neighbor (KNN). Thirdly, neighbor points are uniformly subsampled by the directional searching algorithm based on the Fibonacci principle in multiple spatial directions to reduce memory consumption. …”
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