Physics-informed modeling and process optimization of friction stir welding of AA7075-T6 with a zinc interlayer by Dejene Alemayehu Ifa, Dame Alemayehu Efa, Naol Dessalegn Dejene, Sololo Kebede Nemomsa

“…This study is the first to combine a zinc interlayer with machine learning (ML) based optimization in the FSW of AA7075-T6. Artificial Neural Networks (ANN), Support Vector Regression (SVR), Random Forest Regression (RFR), a Genetic Algorithm (GA) for optimization, and Response Surface Methodology (RSM) for statistical modeling were used to analyze a dataset of 60 observations. …”
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A Minimized Data Collection Optimization Method for Distribution Networks Considering Multiple-Time and Compressed Candidate Sets by Zhaoxiang YUAN, Zhihong XIAO, Jing WANG, Yanling YU, Yan HUANG, Xingle GAO

“…The minimized data collection technology for distribution networks can optimize the measurement configuration with the minimum economic cost, which plays an important role in improving the system observability. …”
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Tensor Network Methods for Hyperparameter Optimization and Compression of Convolutional Neural Networks by A. Naumov, A. Melnikov, M. Perelshtein, Ar. Melnikov, V. Abronin, F. Oksanichenko

“…However, challenges such as hyperparameter optimization (HPO) and model compression remain critical for improving performance and deploying models on resource-constrained devices. …”
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Research on real time measurement model and measurement system for gas concentration in extraction drilling by Dayang Yu, Junhao Zhu, Xing Li, An He, Huaiqian Liu, Changjiang Chen, Yong Liu

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Prediction of CO2 emission for the central European countries through five metaheuristic optimization techniques helping multilayer perceptron by Hossein Moayedi, Azfarizal Mukhtar, Serhan Alshammari, Mohamed Boujelbene, Isam Elbadawi, Quynh T Thi, Mojtaba Mirzaei

“…A series of parametric studies are performed to improve the effectiveness of the employed models. …”
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A comparative study of different kinematic wake models within metaheuristics for efficient wind farm layout optimization by Antonio J. Romero-Barrera, David Casillas-Pérez, Laura Cornejo-Bueno, Jorge Pérez-Aracil, Alvaro Paricio-Garcia, Miguel A. Lopez-Carmona, Juan Blanco-Sancho, Sujan Ghimire, Ravinesh C. Deo, Antonio J. Caamaño, Sancho Salcedo-Sanz

“…We analyze the performance of seven analytical wake models—Jensen, Park2, Frandsen, Larsen, Bastankhah, Ishihara, and Zhang—to estimate the downstream wind speed deficits included in the objective function of metaheuristics (Genetic Algorithm, Particle Swarm Optimization, and Coral Reefs Optimization with Substrate Layers), for an optimal WFLO solution. …”
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Charge and discharge scheduling method for large-scale electric vehicles in V2G mode via MLGCSO by Songling Pang, Kaidi Fan, Meiyi Huo

“…Compared with traditional methods, the diversity and convergence of particle swarm learning are enhanced, and the optimization performance is improved. Simulation results indicate that when compared with three state-of-the-art optimizers, the optimization accuracy of the proposed algorithm is increased by at least 34% and the total cost is reduced by 3.14% and 1.62% respectively, demonstrating that the MLGCSO exhibits high optimization performance and remarkable optimization effects.…”
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The analysis of strategic management decisions and corporate competitiveness based on artificial intelligence by Yang Pu, Hao Li, Wenjia Hou, Xingchen Pan

“…To address this issue, this work proposes a hybrid optimization model combining transformer models and reinforcement learning algorithms, designed to optimize corporate strategic decision-making processes and improve competitiveness. …”
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Hybrid procurement model for the construction of library literature and information resource procurement by Chuanyu Zhang, Changsheng Wang

“…The results show that using genetic algorithm to optimize support vector machine can effectively improve the prediction speed and prediction efficiency of the model. …”
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Hybrid extreme learning machine for real-time rate of penetration prediction by Abdelhamid Kenioua, Omar Djebili, Ammar Touati Brahim

“…Abstract This study presents a comparative analysis of hybrid Extreme Learning Machine (ELM) models optimized with metaheuristic algorithms Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Whale Optimization Algorithm (WOA), and Grey Wolf Optimizer (GWO) for real-time Rate of Penetration (ROP) prediction in drilling operations. …”
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A Comprehensive Analysis of the Triple-Hybrid Metamodel of MLP-PSO-ARIMA for Forecasting the FDSD Index: A Case Study of Khuzestan Province by Mohammad Ansari Ghojghar

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Interacting Large Language Model Agents. Bayesian Social Learning Based Interpretable Models by Adit Jain, Vikram Krishnamurthy

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Optimizing Berth Allocation for Maritime Autonomous Surface Ships (MASSs) in the Context of Mixed Operation Scenarios by Lixin Shen, Xueting Shu, Chengcheng Li, Tomaž Kramberger, Xiaoguang Li, Lixin Jiang

“…A large-scale simulation of the mixed-type berth allocation model is carried out using an improved simulated annealing algorithm. …”
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Recurrent Neural Network Optimized by Grasshopper for Accurate Audio Data-Based Diagnosis of Parkinson's Disease by Saif Wali Ali Alsudani, Ghassan Khudair Saud

“… Proposed here is a speech-based diagnostic framework for detecting Parkinson's disease that utilizes a Long Short-Term Memory neural network and the Grasshopper Optimization Algorithm. The framework aims to improve the detection of PD while ensuring accurate and efficient classification of speech-based signals. …”
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Examining Nasdaq Market Data and Presenting an Optimized Model by Extreme Gradient Boosting Regression and Artificial Bee Colony by Ali Ahmadpour

“…These optimization techniques aim to enhance the model's predictive performance by improving parameter tuning and model generalization. …”
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Integration of multi agent reinforcement learning with golden jackal optimization for predicting average localization error in wireless sensor networks by K. Lakshmi Prabha, Hanan Abdullah Mengash, Hamed Alqahtani, Randa Allafi

“…The GJO algorithm fine-tunes the hyperparameters of MARL to improve generalization across different WSN configurations. …”
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Optimization of engine parameters and emission profiles through bio-additives: Insights from ANFIS Modeling of Diesel Combustion by Abbas Rohani, Javad Zareei, Kourosh Ghadamkheir, Seyed Alireza Farkhondeh

“…Various machine learning configurations and training algorithms were employed to optimize the model's performance. …”
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Parametric Optimization of Train Brake Pad Using Reverse Engineering with Digital Photogrammetry 3D Modeling Method by P Paryanto, Muhammad Faizin, R Rusnaldy

“…Reverse engineering (RE) is essential in recreating 3D models of existing manufactured parts. It is widely used for repairing damaged components, improving used parts, and designing new items based on older models. …”
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The different member equivalent circulating density prediction model and drilling parameter optimization under narrow density window by Wanchun Zhao, Wanchun Zhao, Zhipeng Yang, Tingting Wang, Yan Zhou, Wei Song, Jingrun Li, Peihong Zhai

“…The model uses nonlinear regression algorithms to predict ECD values for different members. …”
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Research on early warning model of coal spontaneous combustion based on interpretability by Huimin Zhao, Xu Zhou, Jingjing Han, Yixuan Liu, Zhe Liu, Shishuo Wang

“…The grid search algorithm was utilized to optimize the model parameters, ensuring the selection of the most suitable parameter configurations. …”
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