A state evaluation and fault diagnosis strategy for substation relay protection system integrating multiple intelligent algorithms by Jiajun Wang, Shiyi Jing, Yu Yao, Kunlun Wang, Bo Li

“…This study introduces a new diagnostic framework that combines improved particle swarm optimization, K‐means clustering algorithms, support vector machine (SVM), and learning vector quantization neural networks to provide a comprehensive fault diagnosis and prediction model for relay protection systems. …”
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Operational response to contamination in water distribution systems: a multi-objective Bayesian optimization approach by Khalid Alnajim, Ahmed A. Abokifa

“…Simulation results are then propagated into MOBO to generate Pareto-optimal solutions of the objective functions. A sensitivity analysis was conducted to tune the hyperparameters of the MOBO algorithm, including the covariance kernel of the surrogate model. …”
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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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Dynamic economic emission dispatch of combined heat and power system based on multi-objective differential evolution algorithm. by Tao Dong

“…Based on this algorithm, the dynamic economic emission dispatch model of combined heat and power system is constructed to optimize the economic and environmental benefits of the system. …”
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An ensemble of deep representation learning with metaheuristic optimisation algorithm for critical health monitoring using internet of medical things by Mai Alduailij

“…To further optimize model performance, the pelican optimization algorithm (POA) is utilized for hyperparameter tuning to ensure that the optimum hyperparameters are chosen for enhanced accuracy. …”
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Improving energy efficiency and network performance in IaaS cloud with virtual machine placement by Jian-kang DONG, Hong-bo WANG, Yang-yang LI, Shi-duan CHENG

“…The existing virtual machine(VM) placement schemes mostly reduce energy consumption by optimizing utilization of physical server or network element.However,the aggressive consolidation of these resources may lead to network performance degradation.In view of this,a VM placement scheme was proposed to achieve two objectives.One is to minimize the number of activating physical machines and network elements to reduce the energy consumption,and the other is to minimize the maximum link utilization to improve the network performance.This scheme is able to reduce the energy consumption caused by physical servers and network equipment while optimizing the network performance,making a trade off between energy efficiency and network performance.A novel two-stage heuristic algorithm for a solution was designed.Firstly,the hierarchical clustering algorithm based on minimum cut and best fit algorithm was used to optimize energy efficiency,and then,local search algorithm was used to minimize the maximum link utilization.The simulations show that this solution achieves good results.…”
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Inversion of Crop Water Content Using Multispectral Data and Machine Learning Algorithms in the North China Plain by Zhenghao Zhang, Gensheng Dou, Xin Zhao, Yang Gao, Saisai Liu, Anzhen Qin

“…Five machine learning (ML) algorithms (i.e., MLR, RF, PLSR, ElasticNet, and ridge regression) were adopted to estimate the crop water content of winter wheat at the three growth stages. …”
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Study on Subway Station Street Block-Level Land Use Pattern and Plot Ratio Control Based on Machine Learning by Mingyi Kuang, Fei Fu, Fangzhou Tian, Liwei Lin, Can Du, Yuesong Zhang

“…This study takes Panda Avenue Subway Station as a case study to analyze the evolution of land use patterns around subway stations and explore optimization strategies to enhance land development efficiency and spatial utilizationTo fill this research gap, this paper proposes a CNN-AIMatch model based on machine learning algorithm and an enhanced PLUS-Markov prediction model using the increase and decrease of floor area ratio as a control measure, which adopts an increase in plot ratio as a control measure to improve the accuracy of the Kappa coefficient in different plot ratio scenarios and the prediction of 3D urban spatial growth trends. …”
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Multiobjective Collaborative Optimization Method for the Urban Rail Multirouting Train Operation Plan by Lianbo Deng, Qi Peng, Li Cai, Junhao Zeng, Nava Raj Bhatt

“…Finally, the proposed model and algorithm are validated with the real data from the Guangzhou Metro Line 2. …”
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Optimal Sizing of Isolated Microgrid Containing Photovoltaic/Photothermal/Wind/Diesel/Battery by Guo Zhao, Tianhua Cao, Yudan Wang, Huirui Zhou, Chi Zhang, Chenxi Wan

“…The three-objective sizing optimization model was solved by the improved multiobjective grey wolf optimization algorithm. …”
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Enhancing 3D A* path planning of intelligent bridge crane based on energy efficiency criteria by Heng YANG, Yue LI, Min LIU, Qing DONG

“…Subsequently, by comprehensively considering energy, time, and path length, the final evaluation value is formed to determine the optimal path. Finally, considering the spatial arrangement and operation of the bridge crane in a factory building as an example, environment modeling is conducted on the MATLAB platform, the virtual obstacle is built at the same scale, the operation scheme of the bridge crane lifting the weight at different heights is conducted, and the multi-scheme path planning is conducted before and after the improvement of the algorithm. …”
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Structural design and optimization of egg carrier for dynamic egg slit detection platforms. by Ronghua Meng, Yuxiang Tian, Siwei Huang

“…On the basis of stable egg carrying, a carrying motion mathematical model is established, and the genetic algorithm (GA) is chosen to optimize the structural parameters. …”
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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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An Ensemble Formal Approach to Improve Energy Efficiency and Data Aggregation in Smart Agriculture by Shahbaz Ahmad, Nadeem Akhtar, Adeel Ahmed, Saman Iftikhar, Shaikhan Bawazeer, Saima Abdullah

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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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Drilling Parameter Control Based on Online Identification of Drillability and Multi-Objective Optimization by Jianbo Dai, Xilu Yin, Yan Zhang, Lei Si, Dong Wei, Zhongbin Wang, Longmei Zhao

“…A multi-objective optimization model of the optimal drilling parameters is established with the mechanical specific energy and drilling speed prediction model as the objective functions, and the NSGA-II algorithm and TOPSIS algorithm are used for solutions and decision-making. …”
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Low-cost fabrication and comparative evaluation of machine learning algorithms for flexible PDMS-based hexagonal patch antenna by Srivatsan Sarvesan, Mettu Goutham Reddy, S. S. Karthikeyan, Praveen K. Sekhar

“…To accelerate the design process and determine the most effective model for predicting optimal geometrical parameters that yield improved impedance matching at the target frequency, four supervised machine learning algorithms including Random Forest, XGBoost, CatBoost and LightGBM were evaluated and compared. …”
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Machine-Learning-Algorithm-Assisted Portable Miniaturized NIR Spectrometer for Rapid Evaluation of Wheat Flour Processing Applicability by Yuling Wang, Chen Zhang, Xinhua Li, Longzhu Xing, Mengchao Lv, Hongju He, Leiqing Pan, Xingqi Ou

“…By employing an improved whale optimization algorithm (iWOA) coupled with a successive projections algorithm (SPA), we selected the 20 most informative wavelengths (MIWs) from the full range spectra, allowing the iWOA/SPA-SOA-SVR model to predict SV with correlation coefficient and root-mean-square errors in prediction (R_P and RMSE_P) of 0.9605 and 0.2681 mL. …”
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Improvement of Energy Indicators of Asynchronous Motor under the Conditions of Asymmetric Voltage Supply by Boyko A.A., Besarab A.N., Sokolov Y.A., Shapa L.N.

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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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