Three-Dimensional Drone Cell Placement: Drone Placement for Optimal Coverage by Aniket Basu, Hooman Oroojeni, Georgios Samakovitis, Mohammad Majid Al-Rifaie

“…Algorithmic diversity has been explored, leading to several modifications and improvements in the implemented models. …”
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Integrative machine learning approach for forecasting lung cancer chemosensitivity: From algorithm to cell line validation by Jinghong Chen, Yonglin Yi, Chunqian Yang, Haoxuan Ying, Jian Zhang, Anqi Lin, Ting Wei, Peng Luo

“…Therefore, predicting individual responses is critical for optimizing treatment outcomes and improving patient prognosis. …”
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Use of Machine Learning Algorithms to Predict Almen (Shot Peening) Intensity Values of Various Steel Materials by Murat İnce, Hatice Varol Özkavak

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LDDFSF-YOLO11: A Lightweight Insulator Defect Detection Method Focusing on Small-Sized Features by Peng Shen, Keyu Mei, Huiqiong Cao, Yongxiang Zhao, Guoqing Zhang

“…And optimize the network structure through channel pruning technology to improve model lightweighting. …”
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Diagnosis of winter precipitation types using the spectral bin model (version 1DSBM-19M): comparison of five methods using ICE-POP 2018 field experiment data by W. Bang, J. T. Carlin, K. Kim, A. V. Ryzhkov, A. V. Ryzhkov, G. Liu, G. Lee

“…We thus explore the effects of the SBM's microphysics scheme on the extent of melting in cases of misdiagnosed RA. An optimized SBM that uses the climatological snow density–diameter relationship for the Pyeongchang region produces an increased amount of melting and achieves improved skill scores compared to the current SBM, which uses a snow density–diameter relationship for the Colorado region.…”
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Research on Optimization of Target Positioning Error Based on Unmanned Aerial Vehicle Platform by Yinglei Li, Qingping Hu, Shiyan Sun, Yuxiang Zhou, Wenjian Ying

“…Subsequently, the Taylor series expansion method is adopted to linearize the approximated coordinate transformation process and simplify the error propagation model. Finally, in order to further improve the positioning accuracy, a target position correction strategy with the improved dung beetle optimization algorithm is introduced. …”
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Selective opposition based constrained barnacle mating optimization: Theory and applications by Marzia Ahmed, Mohd Herwan Sulaiman, Md. Maruf Hassan, Md. Atikur Rahaman, Masuk Abdullah

“…Mathematical models of Barnacle Mating Optimization (BMO) are based on observations of real-world barnacle mating behaviors such as sperm casting and self-fertilization. …”
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Research on Adaptive Planning of Three-Dimensional Trajectory for Uncrewed Aerial Vehicle Inspection Based on Nonlinear Weibull Algorithm by Zhuang Liu, Ning Yang, Jiaxing Fu, Huanqing Cai, Xuebei Wei

“…The results show that under flight environments with varying complexity of obstacle and threat region distribution, compared with the Particle Swarm Optimization algorithm (PSO), Butterfly Optimization Algorithm (BOA), and Reptile Search Algorithm (RSA), NWFRSA can effectively reduce the path cost (by 4.53%–34.47%), contributing to improved.…”
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Research status of gearboxes for high-power nuclear power circulation pumps by WEI Fude, WANG Huanhuan, YANG Shuncheng

“…Many scholars are committed to in-depth research on high-power nuclear power circulating pump gearboxes from the perspectives of dynamics, mechanical design, big data, optimization algorithms, etc., in response to the above-mentioned issues. …”
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A device free high-precision indoor positioning and tracking method based on GMM-WKNN algorithm by Mumen Jiang, Jiangnan Yuan

“…Abstract To address the high deployment complexity and algorithmic intricacies associated with current indoor target localization and tracking methods, this paper presents a Wi-Fi CSI indoor localization and tracking algorithm that integrates a Gaussian Mixture Model (GMM) with Weighted K-Nearest Neighbors (WKNN) and Kalman filtering. …”
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Alpine Meadow Fractional Vegetation Cover Estimation Using UAV-Aided Sentinel-2 Imagery by Kai Du, Yi Shao, Naixin Yao, Hongyan Yu, Shaozhong Ma, Xufeng Mao, Litao Wang, Jianjun Wang

“…The results showed that: (1) Machine learning algorithms based on Sentinel-2 and UAV imagery effectively improved the accuracy of FVC estimation in alpine meadows. …”
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An optimized machine learning framework for predicting and interpreting corporate ESG greenwashing behavior. by Fanlong Zeng, Jintao Wang, Chaoyan Zeng

“…The framework integrates an Improved Hunter-Prey Optimization (IHPO) algorithm, an eXtreme Gradient Boosting (XGBoost) model, and SHapley Additive exPlanations (SHAP) theory to predict and interpret corporate ESG greenwashing behavior. …”
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A Matching Game for LLM Layer Deployment in Heterogeneous Edge Networks by Benedetta Picano, Dinh Thai Hoang, Diep N. Nguyen

“…Executing the inference of foundation models in a distributed manner presents significant challenges, particularly in optimizing both computing and communication resources. …”
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Optimization strategies for public health education based on ISSA and information system technology by Zhanyu Ye, Yifei Li, Yan Zhang

“…IntroductionAgainst the backdrop of rapid development of information technology, public health education is facing challenges such as uneven resource allocation and lagging content.MethodsTo propose an optimization strategy that can effectively improve the level of public health education, this study improves the sparrow search algorithm by introducing the theory of best point sets to optimize the allocation of public health education resources. …”
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Development of Flash Flood Forecasting System for Small and Medium‐Sized Rivers by Koji Ikeuchi, Daiki Kakinuma, Yosuke Nakamura, Shingo Numata, Takafumi Mochizuki, Keijiro Kubota, Masaki Yasukawa, Toshihiro Nemoto, Toshio Koike

“…This forecasting approach uses the rainfall–runoff–inundation (RRI) model and the H–Q equation. The parameters in the RRI model were optimized using the Shuffled Complex Evolution algorithm developed at the University of Arizona (SCE‐UA) to reduce the required time and effort. …”
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Wavelet Transform-Based 3D Landscape Design and Optimization for Digital Cities by Yang Chen, Xiaolin Wang, Chang Zhang

“…Combining this method to design and optimize 3D landscapes in digital cities can improve the efficiency of landscape design.…”
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An open dataset and machine learning algorithms for Niacin Skin-Flushing Response based screening of psychiatric disorders by Xuening Lyu, Rimsa Goperma, Dandan Wang, Chunling Wan, Liang Zhao

“…The core of our methodology involves a novel algorithm featuring an Efficient-Unet based Deep Learning model for the precise segmentation of NSR areas. …”
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Efficient Task Scheduling in Cloud Computing: A Multiobjective Strategy Using Horse Herd–Squirrel Search Algorithm by V. Parthasaradi, A. Karunamurthy, C. H. Hussaian Basha, S. Senthilkumar

“…The novel algorithm used here merges two familiar algorithms as squirrel search algorithm (SSA) and the horse herd optimization algorithm (HOA) leading to a new hybrid metaheuristic algorithm called the horse herd–squirrel search algorithm (HO–SSA). …”
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Optimizing XGBoost Hyperparameters for Credit Scoring Classification Using Weighted Cognitive Avoidance Particle Swarm by Atul Vikas Lakra, Sudarson Jena, Kaushik Mishra

“…The proposed WCAPSO-XGB model tunes the hyperparameters of XGBoost and classifies the credit scoring, and the experimental results are compared with various classifier such as Random Forest (RF), K-neighbors (KNN), Gaussian Naive Bayes (NB), AdaBoost, Gradient Boosting, Logistic Regression (LR), Neural Network (NN), Decision Tree (DT) and Linear Discriminant Analysis (LDA), and hyperparameter optimization methods, such as Grid Search (GS), Random Search (RS), Bays Optimization, Optuna Optimization, Hybrid Snake Optimizer Algorithm (HSOA), Exploratory Cuckoo Search, island Cuckoo Search (iCSPM and iCSPM2), and Improved SSA (ISSA) with HDPM, on four different datasets with a varying number of instances from small to large. …”
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Machine Learning-Driven Prediction of Vitamin D Deficiency Severity with Hybrid Optimization by Usharani Bhimavarapu, Gopi Battineni, Nalini Chintalapudi

“…To enhance the capacity of the classification system to predict multiple classes, preprocessing procedures such as data reduction, cleaning, and transformation were used on the raw vitamin D dataset. The improved whale optimization (IWOA) algorithm was used for feature selection, which optimized weight functions to improve prediction accuracy. …”
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