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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Enhancing Neural Network Training Through Neuroevolutionary Models: A Hybrid Approach to Classification Optimization by Hyasseliny A. Hurtado-Mora, Luis A. Herrera-Barajas, Luis J. González-del-Ángel, Roberto Pichardo-Ramírez, Alejandro H. García-Ruiz, Katea E. Lira-García

“…Additionally, a Cellular Processing Algorithm (PCELL) is employed to expand the search space and improve solution quality. …”
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Optimal Coordination of Directional Overcurrent Relays in Microgrids Considering European and North American Curves by León F. Serna-Montoya, Sergio D. Saldarriaga-Zuluaga, Jesús M. López-Lezama, Nicolás Muñoz-Galeano

“…The proposed model is formulated as a mixed-integer nonlinear programming problem and solved using four metaheuristic techniques: the genetic algorithm (GA), Imperialist Competitive Algorithm (ICA), Harmonic Search (HS), and Firefly Algorithm (FA). …”
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Multi-strategy enhanced artificial rabbits optimization for prediction of grades in tourism service communication courses by Xiaodan Qu, Zhuyin Jia

“…The efficiency of MEARO is confirmed by comparing its performance with eight other sophisticated algorithms using the CEC2017 benchmark. …”
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Precision Detection of Infrared Small Target in Ground-to-Air Scene by Xiaona Dong, Huilin Jiang, Yansong Song, Keyan Dong

“…The results of 9 simulation experiments show that the algorithm has the lowest false alarm rate and the highest detection rate compared with the eight baseline algorithms. …”
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A Short-Term Load Forecasting Method Considering Multiple Factors Based on VAR and CEEMDAN-CNN-BILSTM by Bao Wang, Li Wang, Yanru Ma, Dengshan Hou, Wenwu Sun, Shenghu Li

“…Finally, the sine–cosine and Cauchy mutation sparrow search algorithm (SCSSA) is used to optimize the parameters of the combinative model to improve the forecasting accuracy. …”
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Obstacle-Avoidance Planning in C-Space for Continuum Manipulator Based on IRRT-Connect by Yexing Lang, Jiaxin Liu, Quan Xiao, Jianeng Tang, Yuanke Chen, Songyi Dian

“…Compared to the RRT-Connect algorithm, improvements in node expansion strategies and greedy optimization mechanisms effectively minimize redundant nodes and enhance path generation efficiency: the number of iterations is reduced by 68% and convergence speed is improved by 35%. …”
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Optimization of Ship Permanent Magnet Synchronous Motor ADRC Based on Improved QPSO by Hongbo Xu, Jundong Zhang, Jiale Liu, Yang Cao, Ao Ma

“…Second, due to the numerous parameters in ADRC, which are difficult to tune, the QPSO algorithm—known for its strong global search capabilities and fast convergence speed—is utilized for parameter optimization. …”
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deep-Sep: a deep learning-based method for fast and accurate prediction of selenoprotein genes in bacteria by Yao Xiao, Yan Zhang

“…This algorithm uses a Transformer-based neural network architecture to construct an optimal model for detecting Sec-encoding UGA codons and a homology search-based strategy to remove additional false positives. …”
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Enhanced Hybrid Differential Evolution for Earth-Moon Low-Energy Transfer Trajectory Optimization by Yanyun Zhang, Lei Peng, Guangming Dai, Maocai Wang

“…It is known that the optimization of the Earth-Moon low-energy transfer trajectory is extremely sensitive with the initial condition chosen to search. In order to find the proper initial parameter values of Earth-Moon low-energy transfer trajectory faster and obtain more accurate solutions with high stability, in this paper, an efficient hybridized differential evolution (DE) algorithm with a mix reinitialization strategy (DEMR) is presented. …”
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An Ensemble for Automatic Time Series Forecasting With K-Nearest Neighbors by Maria P. Frias, Francisco Martinez

“…One advantage of this scheme is that the uncertainty associated with choosing a wrong configuration for the model is reduced. This approach is compared with the classical way of selecting a configuration by doing a grid search among several configurations of hyperparameters and model selection choices and choosing the one that performs best on a validation set. …”
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Legendre Cooperative PSO Strategies for Trajectory Optimization by Lei Liu, Yongji Wang, Fuqiang Xie, Jiashi Gao

“…Then, a practical fast one-dimensional interval search algorithm is designed to optimize the additional control variable. …”
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Adaptive Bayesian optimization for proportional derivative control in double-acting piston pump ventilators by Cong Toai Truong, Trung Dat Phan, Van Tu Duong, Huy Hung Nguyen, Thanh Truong Nguyen, Tan Tien Nguyen

“…Simulation results indicate that the Bayesian optimization algorithm exposes controller parameters nearly identical to those found via the grid search method, with comparable system responses. …”
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Intelligent Fault Severity Detection of Rotating Machines Based on VMD-WVD and Parameter-Optimized DBN by Ning Jia, Yao Cheng, Youyuan Tian, Feiyu Yang

“…An intelligent fault severity detection method based on variational mode decomposition- (VMD-) Wigner-Ville distribution (WVD) and sparrow search algorithm- (SSA-) optimized deep belief network (DBN) is suggested to address the problem that typical fault diagnostic algorithms are inappropriate for extremely comparable vibration signals when the samples are insufficient. …”
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Real-Time Analysis of Athletes’ Physical Condition in Training Based on Video Monitoring Technology of Optical Flow Equation by Cuijuan Wang

“…After that, through the analysis of the existing methods, compared with some algorithms that only process a single frame in the video, this article analyzes the continuous multiple frames in the video and extracts the continuous multiple frames of the sampling points through the Lucas-Kanade optical flow method. …”
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An optimized ensemble model with advanced feature selection for network intrusion detection by Afaq Ahmed, Muhammad Asim, Irshad Ullah, Zainulabidin, Abdelhamied A. Ateya

“…Leveraging advanced feature selection techniques, including Best-First Search, Particle Swarm Optimization (PSO), Evolutionary Search, and Genetic Search (GS), along with contemporary dataset, this research aims to enhance the adaptability and resilience of NIDS against modern cyber threats. …”
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Prediction of Fading for Painted Cultural Relics Using the Optimized Gray Wolf Optimization-Long Short-Term Memory Model by Zhen Liu, An-Ran Zhao, Si-Lu Liu

“…For the purpose of investigating the color fading mechanism of pigments, we propose a color fading time series model using a combined long short-term memory recurrent neural network modified by the gray wolf optimization algorithm (GWOAD-LSTM). First, the general gray wolf algorithm was scaled up to two dimensions and combined with an LSTM model for optimal parameter search. …”
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A Method for Improving the Monitoring Quality and Network Lifetime of Hybrid Self-Powered Wireless Sensor Networks by Peng Wang, Yonghua Xiong

“…Then, an improved bidirectional search A* algorithm is used to plan the obstacle avoidance moving path of mobile nodes, fill the remaining coverage holes, and improve the coverage quality of the network. …”
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Optimization of Allocation and Launch Conditions of Multiple Missiles for Three-Dimensional Collaborative Interception of Ballistic Targets by Burak Yuksek, N. Kemal Ure

“…The main contribution of this work is the development of a novel probabilistic search algorithm for efficiently solving the missile allocation problem. …”
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On the Performance of Linear Decreasing Inertia Weight Particle Swarm Optimization for Global Optimization by Martins Akugbe Arasomwan, Aderemi Oluyinka Adewumi

“…However, linear decreasing inertia weight PSO (LDIW-PSO) algorithm is known to have the shortcoming of premature convergence in solving complex (multipeak) optimization problems due to lack of enough momentum for particles to do exploitation as the algorithm approaches its terminal point. …”
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