Optimization of a cylindrical heatsink with L-shaped fins to minimize thermal resistance variation by installation angle by Gihyun Song, Hak-Ho Nam, Seungmin Heo, Se-Jin Yook

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Experimental study on DEM parameters calibration for organic fertilizer by the particle swarm optimization − backpropagation neural networks by Fandi Zeng, Limin Liu, Yinzeng Liu, Hongbin Bai, Chunxiao Li, Zhihuan Zhao

“…Genetic algorithms (GA) and particle swarm optimization algorithms (PSO) were used to optimize the BP neural network. …”
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Hull form optimization of fully parameterized small ships using characteristic curves and deep neural networks by Jin-Hyeok Kim, Myung-Il Roh, In-Chang Yeo

“…The accuracy of the DNN model was evaluated, resulting in a Mean Absolute Error (MAE) of 2.835%. Subsequently, the DNN model is combined with a genetic algorithm to identify the optimal set of parameters for the hull form, resulting in an optimal hull form. …”
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Experimental investigation and optimization of epoxy composites reinforced with jute fiber and alumina using the Jaya ANFIS approach by Lakshmi Narayana Somsole, P. Thejasree, K. L. Narasimhamu, Manikandan Natarajan, G. Velmurugan, Dinesh Ramesh Salunke, Vinod P. Sakhare, Pramod Kumar, Regasa Yadeta Sembeta

“…The Jaya algorithm, developed based on Grey-ANFIS, is utilized for process optimization, applying grey theory to establish a multi-performance index that is rigorously assessed through statistical error analysis. …”
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Python-based deep learning for optimizing thermal performance of Prandtl-Eyring hybrid nanofluids in solar systems by Nidhal Ben Khedher, Bouthaina Dammak, Zahoor Shah, Hamza Iqbal, Maryam Jawaid, Hafedh Mahmoud Zayani, Mohamed Medani

“…Using engine oil as a base fluid and Cu–MoS2 nanoparticles at a 2 % volume fraction, the framework utilized the solver that will be used along with solve_bvp to find a solution of the transformed ODEs, and the model will train a DLNN (two hidden layers, with ReLU activation and optimized with Adam) to have the ability to conduct predictive analysis. …”
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Predictive modeling of building energy consumption and thermal comfort for decarbonization in construction and retrofitting by Sameer Algburi, Aymen Mohammed, Ibrahim Abdullah, Talib Munshid Hanoon, Hassan Falah Fakhruldeen, Otabek Mukhitdinov, Feryal Ibrahim Jabbar, Qusay Hassan, Ali Khudhair, David Kato

“…The proposed multi-variable regression model demonstrated strong predictive accuracy, achieving an R² of 0.98, a mean absolute percentage error of 1.59 %, and a Coefficient of Variation of the Root Mean Square Error (CVRMSE) of 1.47 % in forecasting annual cooling demands. …”
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Statistical Analysis of Industrial Processes by T. I. Chepeleva, A. N. Chepelev

“…The cluster analysis has been carried out by the method of K-medium production process with minimization of the total error probability. …”
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AI-Driven Meat Food Drying Time Prediction for Resource Optimization and Production Planning in Smart Manufacturing by Rajnish Rakholia, Andres L. Suarez-Cetrulo, Manokamna Singh, Ricardo Simon Carbajo

“…Conventional approaches for estimating drying times often depend on empirical rules or manual observations, which can be time-consuming, subjective, and susceptible to human error. Therefore, implementing an automation solution by developing a predictive model for drying times in meat manufacturing is essential for optimizing the production lifecycle. …”
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Machine learning enhanced metal 3D printing: high throughput optimization and material transfer extensibility by Yuanjie Zhang, Cheng Lin, Yuan Tian, Jianbao Gao, Bo Song, Hao Zhang, Min Wang, Kechen Song, Binghui Deng, Dezhen Xue, Yonggang Yao, Yusheng Shi, Kun Kelvin Fu

“…However, the intricate interplay between laser and metal powders poses a significant challenge for conventional trial-and-error optimization. Meanwhile, the “optimized” yet fixed parameters largely limit possible extensions to new designs and materials. …”
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Optimization of PV parameters under varied environmental conditions: A hybrid secant–Newton-Raphson method by Brahim El Fahmi, Driss Saadaoui, Imade Choulli, Khalid Assalaou, Ismail Abazine, Mustapha Elyaqouti, El hanafi Arjdal, Mohammed Agdam, Yassine El aidi Idrissi

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Optimizing Scan Range in Computed Tomography of Kidneys, Ureters, and Bladder: A Retrospective Study on Reducing Overscanning by Ali Bin Owien, Khaled Alenazi, Ahmad Abanomy, Mansour Almanaa, Mohammad Alarifi, Haitham Alahmad

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Fluvial bedload transport modelling: advanced ensemble tree-based models or optimized deep learning algorithms? by Khabat Khosravi, Aitazaz A. Farooque, Sayed M. Bateni, Changhyun Jun, Dorsa Mohammadi, Zahra Kalantari, James R. Cooper

“…Using 926 datasets for 20 rivers, the performance of three groups of models was tested: (1) standalone tree-based models Alternating Model Tree (AMT) and Dual Perturb and Combine Tree (DPCT); (2) ensemble tree-based models Iterative Absolute Error Regression (IAER), ensembled with AMT and DPCT; and (3) optimized deep learning models Long Short-Term Memory (LSTM) and Recurrent Neural Network (RNN) ensembled with Grey Wolf Optimizer. …”
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Bioreactor Design Optimization Using CFD for Cost-Effective ACPase Production in <i>Bacillus subtilis</i> by Xiao Yu, Kaixu Chen, Chunming Zhou, Qiqi Wang, Jianlin Chu, Zhong Yao, Yang Liu, Yang Sun

“…First, the gas distributor structure of the 5 L bioreactor was optimized using CFD simulation results. Optimal mass transfer conditions were identified through comprehensive analysis of <i>K_La</i> in different reactor regions (aeration ratio: 1.142 VVm, <i>K_La</i> = 264.2 h⁻¹). …”
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Performance Portrait Method: Robust Design of Predictive Integral Controller by Mikulas Huba, Pavol Bistak, Jarmila Skrinarova, Damir Vrancic

“…The wide applicability of PPM ranges from verification of analytically calculated optimal settings achieved by various approaches to controller design, to the analysis as well as optimal and robust setting of controllers for processes where other known control design methods fail. …”
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The Role of Forcing and Parameterization in Improving Snow Simulation in the Upper Colorado River Basin Using the National Water Model by Yanjun Gan, Yu Zhang, Cezar Kongoli, Ming Pan

“…Adjusting AORC precipitation with SNOTEL observations reduced SWE root‐mean‐square error (RMSE) by 66%, adjusting temperature trimmed it by 10%, and adjusting both decreased it by 69%. …”
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Performance Evaluation of Metaheuristics for LQR Controller Optimization: A Two-Wheel Balancing Robot Case Study by Jose Ricardo Rivera-Ruiz, Ricardo Rojas-Galvan, Jose R. Garcia-Martinez, Edson Eduardo Cruz Miguel, Omar A. Barra-Vazquez, Maria Ines Cruz Orduna, Jesus Enrique Escalante-Martinez, Juvenal Rodriguez-Resendiz

“…Experimental results demonstrate that the controller optimized by differential evolution achieves the lowest root mean square error (0.4910 degrees), outperforming ABC (0.5187 degrees) and GHS (0.5195 degrees). …”
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Predictive Analysis of Maritime Congestion Using Dynamic Big Data and Multiscale Feature Analysis by Yalin Wu

“…First, the dynamic analysis of vessel trajectories aims to extract valuable information from ships’ data as they navigate the oceans, enabling proactive traffic management and optimized routing. …”
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Behavioral Modeling of SiC MOSFET Static and Dynamic Characteristics Based on Particle Swarm Optimization Algorithm by Zhibo Zhu, Yang Zhao, Wei Yan

“…A pulse testing experimental circuit is constructed to validate the accuracy of the dynamic model, compared with the sample model and experimental results, the errors of the behavioral model are less than 3%. This study provides valuable insights for MOSFET modeling and optimization, contributing to the dynamic analysis and reliability research of electronic circuits.…”
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Application of response surface methodology to optimize the drying condition of black tea using superheated steam dryer by Rumaisa Nordin, Norazatul H. M. Rozall, Tajul A. Yang

“…Drying conditions of black tea using superheated steam (SHS) were optimized based on a central composite design (CCD) of response surface methodology (RSM). …”
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Quantum Long Short-Term Memory-Assisted Optimization for Efficient Vehicle Platooning in Connected and Autonomous Systems by Mahzabeen Emu, Taufiq Rahman, Salimur Choudhury, Kai Salomaa

“…Vehicle platooning, especially when dedicated to carrying goods, represents a forward-looking approach to optimizing logistics and freight transportation using autonomous vehicles. …”
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