Soft-sensor modeling of silicon content in hot metal based on sparse robust LS-SVR and multi-objective optimization by GUO Dong-wei, ZHOU Ping

“…Last, the multi-objective evaluation index that synthesizes the modeling residue and the estimated trend was presented to compensate for the deficiency of the single root mean square error (RMSE) index. Based on those, an on-line soft sensor model of hot metal[Si] with the optimal parameters was obtained by using the multi-objective genetic algorithm (NSGA-Ⅱ) with the non-dominated sort and elitist strategy. …”
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A hybrid model based on learning automata and cuckoo search for optimizing test item selection in computerized adaptive testing by Chanjuan Jin, Weiming Pan

“…Compared with the traditional CAT methods, our approach gives better ability estimates and selects test items that are most appropriate for each student. The findings of the study show that the efficiency, accuracy and fairness of the tests have improved through experimentation.…”
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Prediction of dam deformation using adaptive noise CEEMDAN and BiGRU time series modeling by WANG Zixuan, OU Bin, CHEN Dehui, YANG Shiyong, ZHAO Dingzhu, FU Shuyan

“…High-frequency modal components undergo secondary decomposition using variational mode decomposition (VMD) to extract the optimal intrinsic mode function. Finally, an improved symbiotic biological search algorithm combined with a Bidirectional Gated Recurrent Unit (BiGRU) is used to accurately predict dam deformation.…”
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Allocation of Interline Power Flow Controller-Based Congestion Management in Deregulated Power System by Muhammad Safdar Sial, Qinghua Fu, Talles Vianna Brugni

“…Therefore, an objective function is defined, including the stated parameter, minimizing the generation cost, congestion costs, power losses, and improving the voltage profile. Using the upgraded SWSO algorithm, a new approach to the optimal location of IPFC is presented. …”
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Forecasting Megaelectron‐Volt Electrons Inside Earth's Outer Radiation Belt: PreMevE 2.0 Based on Supervised Machine Learning Algorithms by Rafael Pires de Lima, Yue Chen, Youzuo Lin

“…This updated model, called PreMevE 2.0, provides improved forecasts, particularly at outer L‐shells, by adding upstream solar wind speeds to the model's input parameter list that originally includes precipitating electrons observed at low Earth orbits and MeV electron fluxes in situ measured by a geosynchronous satellite. …”
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Assessment of soil classification based on cone penetration test data for Kaifeng area using optimized support vector machine by Hanliang Bian, Zhongxun Sun, Jiahan Bian, Zhaowei Qu, Jianwei Zhang, Xiangchun Xu

“…Notably, the Thermal Exchange Optimization (TEO) algorithm resulted in the most significant improvement, increasing the accuracy of the original SVM model by 10% and exceeding the standard by 4.3%. …”
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Method for EEG signal recognition based on multi-domain feature fusion and optimization of multi-kernel extreme learning machine by Shan Guan, Tingrui Dong, Long-kun Cong

“…Abstract In response to the current issues of one-sided effective feature extraction and low classification accuracy in multi-class motor imagery recognition, this study proposes an Electroencephalogram (EEG) signal recognition method based on multi-domain feature fusion and optimized multi-kernel extreme learning machine. Firstly, the EEG signals are preprocessed using the Improved Comprehensive Ensemble Empirical Mode Decomposition (ICEEMD) algorithm combined with the Pearson correlation coefficient to eliminate noise and interference. …”
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Influence of soil parameters on dynamic compaction: numerical analysis and predictive modeling using GA-optimized BP neural networks by Yu Zhang, Xueshui Chen, Huakang Ge, Zhigang Guo, Xu Li

“…Orthogonal experimental design and single factor analysis were used to quantify the influence of each parameter on the compaction volume. In order to improve the prediction accuracy, this paper introduces genetic algorithm (GA) to optimize the BP neural network model, constructs a multi-factor dynamic compaction prediction model, and compares it with the traditional BP model. …”
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Achieving local differential location privacy protection in 3D space via Hilbert encoding and optimized random response by Yan Yan, Pengbin Yan, Adnan Mahmood, Yang Zhang, Quan Z. Sheng

“…Experiments on the real spatial location datasets show that the suggested method can reduce spatial location service quality loss, maintain the availability of perturbed spatial location and improve the operation efficiency of the spatial location perturbation algorithm.…”
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Recurrent academic path recommendation model for engineering students using MBTI indicators and optimization enabled recurrent neural network by Anupama V, Sudheep Elayidom M

“…At last, an adaptive recommendation of the engineering department is performed using DRNN, which is trained based on the Magnetic Invasive Weed Optimization (MIWO) algorithm. On the other hand, MBTI personality type categorization is done, wherein the correlation of courses with MBTI outcome is detected using MIWO-based DRNN. …”
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Optimizing multi-objective hybrid energy systems with pumped hydro storage for enhanced stability and efficiency in renewable energy integration by Junxian Li, Jiaxin Yuan, Xuxin Yue

“…This efficient strategy consists of the inherent complexities, which is solved by the NSGA-II algorithm. The multi-objective approach of optimization procedure performs Pareto solution sets that reflects trade-offs between remaining load variations and operational costs. …”
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Enhancing Streamflow Prediction Accuracy: A Comprehensive Analysis of Hybrid Neural Network Models with Runge–Kutta with Aquila Optimizer by Rana Muhammad Adnan, Wang Mo, Ahmed A. Ewees, Salim Heddam, Ozgur Kisi, Mohammad Zounemat-Kermani

“…Abstract This study investigates the efficacy of hybrid artificial neural network (ANN) methods, incorporating metaheuristic algorithms such as particle swarm optimization (PSO), genetic algorithm (GA), gray wolf optimizer (GWO), Aquila optimizer (AO), Runge–Kutta (RUN), and the novel ANN-based Runge–Kutta with Aquila optimizer (LSTM-RUNAO). …”
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Machine Learning Framework for Early Detection of Chronic Kidney Disease Stages Using Optimized Estimated Glomerular Filtration Rate by Samit Kumar Ghosh, Namareq Widatalla, Ahsan H. Khandoker

“…The application of GWO for hyperparameter tuning has resulted in a 37.3% reduction in root mean square error (RMSE), a 37.4% drop in mean absolute percentage error (MAPE), and a 2.06% improvement in <inline-formula> <tex-math notation="LaTeX">$\text {R}^{2}$ </tex-math></inline-formula> to improve the precision of prediction. …”
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Enhanced Disc Herniation Classification Using Grey Wolf Optimization Based on Hybrid Feature Extraction and Deep Learning Methods by Yasemin Sarı, Nesrin Aydın Atasoy

“…Following feature extraction, the GWO algorithm, inspired by the social hierarchy and hunting behavior of grey wolves, is employed to optimize the feature set by selecting the most relevant features. …”
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Toward a linear-ramp QAOA protocol: evidence of a scaling advantage in solving some combinatorial optimization problems by J. A. Montañez-Barrera, Kristel Michielsen

“…Abstract The quantum approximate optimization algorithm (QAOA) is a promising algorithm for solving combinatorial optimization problems (COPs), with performance governed by variational parameters $${\{{\gamma }_{i},{\beta }_{i}\}}_{i = 0}^{p-1}$$ { γ i , β i } i = 0 p − 1 . …”
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Enhancing grid connected wind energy conversion systems through fuzzy logic control optimization with PSO and GA techniques by Abdelhalim Borni, Noureddine Bessous, Layachi Zaghba, Abdelhak Bouchakour, Melkamu Sisay Agmas, Enas Ali, Sherif S. M. Ghoneim, Ayman Hoballah

“…Abstract This paper presents the design and simulation of an optimized fuzzy logic Maximum Power Point Tracking (MPPT) controller for grid-tied wind turbines, utilizing Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). …”
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Adaptive Neuro-Fuzzy Inference System-Genetic Algorithm approach for global maximum power point tracking in PV systems under different shading conditions by Nivine Guler, Zied Ben Hazem, Ali Gunes, Firas Saidi

“…An inherent problem with most conventional global maximum power point tracking (GMPPT) algorithms is that they do not distinguish local and global peaks, and thus energy extraction may not be optimal. …”
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Distribution Generation Network Arrangement by Capacitor Placement and Sizing in Renewable Energy Sources with Uncertainties Based on Self-adaption Kho-Kho Optimizer by Lu Xingxing

“…Using a self-adaptive Kho-Kho optimizer, the research aims to minimize operational costs while improving technical parameters, such as voltage stability and loss reduction. …”
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Dynamic Gesture Recognition and Interaction of Monocular Camera Based on Deep Learning by SUNBo wen, YU Feng

“…Through convolution and fullconnected network structure, as well as optimization of parameter selection and prevention of overfitting, combined with fingertip detection and elimination algorithm, the recognition accuracy is improved. …”
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Medical Dataset Classification: A Machine Learning Paradigm Integrating Particle Swarm Optimization with Extreme Learning Machine Classifier by C. V. Subbulakshmi, S. N. Deepa

“…This paradigm integrates the successful exploration mechanism called self-regulated learning capability of the particle swarm optimization (PSO) algorithm with the extreme learning machine (ELM) classifier. …”
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