Bayesian Uncertainty Quantification of Reflooding Model With PSO–Kriging and PCA Approach by Ziyue Zhang, Dong Li, Nianfeng Wang, Meng Lei

“…To improve the process of best estimate plus uncertainty (BEPU) for nuclear safety assessment and calibration of thermal–hydraulic models for error reduction, inverse uncertainty quantification (IUQ) is proposed in recent years to quantify the uncertainty of model parameters in reactor program. …”
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Embedded Rough-Neck Helmholtz Resonator Low-Frequency Acoustic Attenuator by Xianming Sun, Tao Yu, Lipeng Wang, Yunshu Lu, Changzheng Chen

“…Moreover, by coupling the BP network with the Golden Jackal Optimization (GJO) algorithm, a BP-GJO optimization model is developed to refine the structural parameters. …”
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An Optimization Framework for Waste Treatment Center Site Selection Considering Nighttime Light Remote Sensing Data and Waste Production Fluctuations by Junbao Xia, Yanping Liu, Haozhong Yang, Guodong Zhu

“…Distinct from prior studies, this study suggests that service point waste quantities are not fixed values but rather adhere to a normal distribution within specified ranges and thus provides a more realistic simulation of fluctuations in waste production while enhancing both the robustness and predictive accuracy of the model. In conclusion, by incorporating nighttime light remote sensing data along with advanced machine learning techniques, this study markedly improves forecasting accuracy for waste production while offering effective optimization strategies for site selection and recovery route planning—thereby establishing a robust data foundation aimed at refining urban solid waste management systems.…”
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Migraine triggers, phases, and classification using machine learning models by Anusha Reddy, Ajit Reddy

“…These models are run with the dataset without optimal tuning across the entire dataset for different migraine types; which is further improved with selective sampling and optimal tuning. …”
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Efficiency assessment of micro hydropower for agriculture using modern modeling by Urishev Omadjon, Salomov Uktam, Ergashev Sirojiddin, Kuchkarov Akmaljon, Madaliev Murodil, Abdukarimov Bekzod, Juraev Nurmakhamad

“…Using modern numerical analysis methods, including computational turbulence modeling algorithms, the study evaluates the energy production and optimization of micro-hydropower plant operation under various conditions. …”
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Skip-Connected CNN Exploiting BNN Surrogate for Antenna Modelling by Yubo Tian, Jinlong Sun, Zhiwei Zhu

“…Experimental results of antennas modeling demonstrate that the proposed algorithm improves the prediction accuracy and fitting performance relative to BNN. …”
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Machine Learning with Evolutionary Parameter Tuning for Singing Registers Classification by Tales Boratto, Gabriel de Oliveira Costa, Alexsandro Meireles, Anna Klara Sá Teles Rocha Alves, Camila M. Saporetti, Matteo Bodini, Alexandre Cury, Leonardo Goliatt

“…Thus, the present article proposes a novel approach that leverages the Differential Evolution (DE) algorithm to optimize hyperparameters within three selected ML models, with the aim of classifying singing-voice registers i.e., chest, mixed, and head registers). …”
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Quality Prediction Model Based on Novel Elman Neural Network Ensemble by Lan Xu, Yuting Zhang

“…In this paper, we propose a novel prediction algorithm based on an improved Elman neural network (NN) ensemble for quality prediction, thus achieving the quality control of designed products at the product design stage. …”
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Application of Feedforward Artificial Neural Networks to Predict the Hydraulic State of a Water Distribution Network by Leandro Evangelista, Débora Móller, Bruno Brentan, Gustavo Meirelles

“…Usually, a hydraulic model is used jointly with optimization methods, which require considerable computational effort, hindering real-time interventions. …”
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A Mixed Integer Linear Formulation and a Grouping League Championship Algorithm for a Multiperiod-Multitrip Order Picking System with Product Replenishment to Minimize Total Tardin... by Morteza Farhadi Sartangi, Ali Husseinzadeh Kashan, Hassan Haleh, Abolfazl Kazemi

“…Improvement heuristics are designed as well. The performance of the MILP formulation and metaheuristic algorithms is analyzed for different problem instances whose designs are based on real data gathered from an auto parts warehouse. …”
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Modeling and Control of Permanent Magnet Synchronous Motor Based Electric Vehicle by Rajesh G., K. Sebasthirani

“…The research focuses on the design and optimization of Fractional Order PID (FOPID) controllers, leveraging Genetic Algorithm (GA) and Hybrid Reinforcement Genetic Algorithm-Recursive Backpropagation Learning (GA-RBL) techniques to enhance tuning performance. …”
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Establishment of Hyperspectral Prediction Model of Water Content in Anshan-Type Magnetite by Xiaoxiao XIE, Yang BAI, Jiuling ZHANG, Yuna JIA

“…Using S-G smoothing filtering (S-G), multivariate scattering correction (MSC), standard normal transformation (SNV), second derivative (SD), reciprocal logarithm (LR) and continuum removal (CR) to preprocess the data, the spectral characteristics and their correlation with water content were analyzed. In order to further improve the prediction ability of the model, the competitive adaptive reweighting method (CARS) was used to optimize the characteristic band, and a prediction model was established by combining random forest regression (RFR), least squares support vector regression (LSSVR) and particle swarm optimization least squares support vector regression (PSO-LSSVR). …”
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River floating object detection with transformer model in real time by Chong Zhang, Jie Yue, Jianglong Fu, Shouluan Wu

“…Our experimental findings are compelling: LR-DETR achieves a 5% increase in mean Average Precision (mAP) at an Intersection over Union (IoU) threshold of 0.5, a 25.8% reduction in parameter count, and a 22.8% decrease in GFLOPs, compared to the RT-DETR algorithm. These improvements are particularly pronounced in the real-time detection of river floating objects, showcasing LR-DETR’s potential in specific environmental monitoring scenarios. …”
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Classification of English Translation Teaching Models based on Multiple Intelligence Theory by Xiaoli Li

“…Moreover, this paper adopts Fisher’s discriminant method and Bayesian discriminant method to classify the English translation teaching samples. In order to improve the discrimination accuracy of the extreme learning machine algorithm, this paper applies the particle swarm optimization extreme learning machine algorithm to the research on the classification of English translation teaching samples and proposes an intelligent English classification teaching model based on the actual situation of English translation teaching. …”
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A novel and sturdy MPPT architecture for grid-tied EV charging stations using Ali Baba and forty thieves optimization by Debabrata Mazumdar, Hassan Abdurrahman Shuaibu, Chiranjit Sain, Taha Selim Ustun

“…This approach aims to optimize modelling for all EV fleets. The developed method performs exceptionally well in comparison to other algorithms that have been studied in the literature. …”
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Two-Stage Optimization of Mobile Energy Storage Sizing, Pre-Positioning, and Re-Allocation for Resilient Networked Microgrids with Dynamic Boundaries by Hongtao Lei, Bo Jiang, Yajie Liu, Cheng Zhu, Tao Zhang

“…The proposed framework is modeled mathematically and solved using a customized progressive hedging algorithm. …”
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Revisiting universal extra-dimension model with gravity mediated decays by Kirtiman Ghosh, Katri Huitu, Rameswar Sahu

“…These methods improve sensitivity to fat-brane mUED signatures and offer promising prospects for probing this model in future LHC runs.…”
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Optimizing solar maximum power point tracking with adaptive PSO: A comparative analysis of inertia weight and acceleration coefficient strategies by Denesh Sooriamoorthy, Aaruththiran Manoharan, Siva Kumar Sivanesan, Soon Kian Lun, Alexander Chee Hon Cheong, Sathish Kumar Selva Perumal

“…Metaheuristic algorithms such as Particle Swarm Optimization (PSO) are explored extensively for MPPT applications. …”
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A Model for Bus Crew Scheduling Problem with Multiple Duty Types by Mingming Chen, Huimin Niu

“…., day duty) has also been considered. An optimization model is formulated as a 0-1 integer programming problem to improve the efficiency of crew scheduling at the minimum expense of total idle time of crew for a circle bus line. …”
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A hybrid AI-CFD framework for optimizing heat transfer of a premixed methane-air flame jet on inclined surfaces by Panit Kamma, Kittipos Loksupapaiboon, Juthanee Phromjan, Chakrit Suvanjumrat

“…To reduce the computational expense of these simulations, a hybrid Artificial Neural Network-Genetic Algorithm (ANN-GA) model was developed. The ANN accurately predicted thermal efficiency based on operational parameters, while the GA optimized these inputs to achieve maximum thermal efficiency of 76.9955 %, closely matching the CFD-predicted value of 70.86 % (discrepancy:6.1355 %). …”
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