A Finite Element–Finite Volume Code Coupling for Optimal Control Problems in Fluid Heat Transfer for Incompressible Navier–Stokes Equations by Samuele Baldini, Giacomo Barbi, Giorgio Bornia, Antonio Cervone, Federico Giangolini, Sandro Manservisi, Lucia Sirotti

“…Specifically, two different CFD codes, OpenFOAM (finite volume-based) and FEMuS (finite element-based), have been used to solve the optimality system, while the data transfer between them is managed by the external library MEDCOUPLING. …”
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Deep reinforcement learning for multi-objective location optimization of onshore wind power stations: a case study of Guangdong Province, China by Yanna Gao, Hong Dong, Liujun Hu, Fanhong Zeng, Yuqun Gao, Zhuonan Huang, Shaohua Wang, Shaohua Wang

“…To solve this model at large scale, a deep reinforcement learning (DRL) algorithm is designed and implemented. The DRL approach is benchmarked against a traditional optimization implementation using the Gurobi solver. …”
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Multiobjective optimization of CO2 injection under geomechanical risk in high water cut oil reservoirs using artificial intelligence approaches by Fankun Meng, Jia Liu, Gang Tong, Hui Zhao, Chengyue Wen, Yuhui Zhou, Vamegh Rasouli, Minou Rabiei

“…Therefore, a hybrid optimization framework was designed that combines artificial intelligence methods (Support Vector Regression with the Gaussian kernel, Gaussian-SVR or Long Short-Term Memory, LSTM) and multi-objective optimization algorithms (multiple objective particle swarm optimization, MOPSO or Non-dominated Sorting Genetic Algorithm II, NSGA-II) to find the optimal CO2 injection and production strategies under different water cut. …”
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Radar-equivalent snowpack: reducing the number of snow layers while retaining their microwave properties and bulk snow mass by J. Meloche, N. R. Leroux, B. Montpetit, V. Vionnet, C. Derksen

“…Using this methodology in SWE retrieval applications, this method can be used to simplify snowpacks and reduce the number of variables to optimize while maintaining similar scattering behavior without compromising the modeled snowpack properties. …”
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Optimization of microwave-assisted polyphenol extraction and antioxidant activity from papaya peel using response surface methodology and artificial neural network by Md. Waziur Rahman Chy, Tanvir Ahmed, Junaid Iftekhar, Md. Zohurul Islam, Md. Rahmatuzzaman Rana

“…These models were combined with the desirability function (DF) and/or genetic algorithm (GA) optimization approaches. Maximizing TPC and DPPH activity while maintaining MWP, I-time, EtOH%, and S/S within their respective ranges using hybrid optimization approaches (RSM-DF: TPC = 1058 mgGAE/100 g, and DPPH = 83 %, RSM-GA: TPC = 1064 mgGAE/100 g and DPPH = 79 %, and ANN-GA: TPC = 1086 mgGAE/100 g, and DPPH = 83 %,) yielded consistent optimal results. …”
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Optimization and modeling of sulfur removal from liquid fuel using carbon-based adsorbents through synergistic application of RSM and machine learning by Karim Maghfour Sarkarabad, Mohsen Shayanmehr, Ahad Ghaemi

“…We employed radial basis function (RBF) and multilayer perceptron (MLP) algorithms for ANN modeling. The optimal MLP configuration, utilizing the Levenberg–Marquardt (Trainlm) algorithm, consisted of three hidden layers with 20, 17, and 9 neurons, respectively, while the optimal RBF network contained 43 neurons. …”
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Bilevel Optimization Framework for Multiregional Integrated Energy Systems Considering 6G Network Slicing and Battery Energy Storage Capacity Sharing by Kun Cui, Ming Chi, Yong Zhao, Zhi-Wei Liu

“…The proposed line search-based global Levenberg–Marquardt algorithm addresses the limitations of existing algorithms with necessary and innovative improvements to tackle the challenge of global convergence in nonsmooth optimization problems. …”
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Fluid flow characteristics estimation of a new integrated bifluid/airbased photovoltaic thermal system utilizing a hybrid optimization method by Ghassan A. Bilal, Abdullateef A. Jadallah, Omayma M. Abdulmajeed, Müslüm Arıcı

“…This paper aims to utilize soft computing techniques in predicting the outlet fluids’ temperatures for monitoring based on the experience of outdoor experiments. The optimization was conducted using the Particle Swarm Optimization method to decide the rules of the Fuzzy Logic Controller. …”
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A novel hybrid fruit fly and simulated annealing optimized faster R-CNN for detection and classification of tomato plant leaf diseases by E. Gangadevi, Ben Othman Soufiane, Balamurugan Balusamy, Firoz Khan, Masresha Getahun

“…By hybridizing the fruit fly optimization algorithm and simulated annealing, the Faster R-CNN’s hyper-parameter issues are addressed, and the convergence rate is improved. …”
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Optimized frequency stabilization in hybrid renewable power grids with integrated energy storage systems using a modified fuzzy-TID controller by Mohamed Khamies, Ahmed H. A. Elkasem, Salah Kamel, Mohamed Hashem

“…The parameters of the strategies are optimized using a recent metaheuristic algorithm known as the Sea Horse Optimizer (SHO) under different operating conditions. …”
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A Hybrid GRA-TOPSIS-RFR Optimization Approach for Minimizing Burrs in Micro-Milling of Ti-6Al-4V Alloys by Rongkai Tan, Abhilash Puthanveettil Madathil, Qi Liu, Jian Cheng, Fengtao Lin

“…However, its practical applications are hindered by significant challenges, particularly the unavoidable generation of burrs, which complicate subsequent finishing processes and adversely affect overall part quality. To optimize the burr formation in the micro-milling of Ti-6Al-4V alloys, this study proposes a novel hybrid-ranking optimization algorithm that integrates Grey Relational Analysis (GRA) with the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). …”
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A Hybrid Deep Learning and Improved SVM Framework for Real-Time Railroad Construction Personnel Detection with Multi-Scale Feature Optimization by Jianqiu Chen, Huan Xiong, Shixuan Zhou, Xiang Wang, Benxiao Lou, Longtang Ning, Qingwei Hu, Yang Tang, Guobin Gu

“…Finally, an SVM classification algorithm is employed for personnel detection. To process small sample categories, data enhancement techniques (e.g., random flip and rotation) and K-fold cross-validation are applied to optimize the model parameters. …”
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Optimized Two-Stage Anomaly Detection and Recovery in Smart Grid Data Using Enhanced DeBERTa-v3 Verification System by Xiao Liao, Wei Cui, Min Zhang, Aiwu Zhang, Pan Hu

“…The first stage employs an optimized increment-based detection algorithm achieving 95.0% for recall and 54.8% for precision through multidimensional analysis. …”
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Quantum-Enhanced Predictive Degradation Pathway Optimization for PV Storage Systems: A Hybrid Quantum–Classical Approach for Maximizing Longevity and Efficiency by Dawei Wang, Shuang Zeng, Liyong Wang, Baoqun Zhang, Cheng Gong, Zhengguo Piao, Fuming Zheng

“…To address these challenges, this paper proposes a quantum-enhanced degradation pathway optimization framework that dynamically adjusts operational strategies to extend the lifespan of PV storage systems while maintaining high efficiency. …”
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Uncertainty management in multiobjective electric vehicle integrated optimal power flow based hydrothermal scheduling of renewable power system for environmental sustainability by Susanta Dutta, Siddhartha Ghosh, Tushnik Sarkar, Provas Kumar Roy, Chandan Paul, Ruba Abu Khurma, Mohd Asif Shah, Saurav Mallik

“…Secondly, renewable energy sources such as wind-solar-EV are integrated with the aforesaid systems for lowering fuel cost, emission, active power loss (APL), aggregated voltage deviation (AVD), voltage stability index (VSI) and also cost, emision, APL, AVD, VSI are reduced simultaneously considering different cases for multi-objective functions.Proposed sine-cosine algorithm (SCA) embedded with quasi-oppositional based learning (QOBL), known as QOSCA is used to balance the exploration and exploitation ability in order to overcome shortcomings and provide global optimal solutions. …”
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Max–Min Secrecy Rate and Secrecy Energy Efficiency Optimization for RIS-Aided VLC Systems: RSMA Versus NOMA by Omar Maraqa, Sylvester Aboagye, Majid H. Khoshafa, Telex M. N. Ngatched

“…This paper presents a comprehensive study on the joint optimization of VLC access point (AP) power allocation, RIS association, and RIS elements orientation angles for secure VLC systems, while considering rate-splitting multiple access (RSMA) and power-domain non-orthogonal multiple access (NOMA) schemes. …”
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Synergizing neural networks with multi-objective thermal exchange optimization and PROMETHEE decision-making to improve PCM-based photovoltaic thermal systems by Yongxin Li, Ali Basem, As'ad Alizadeh, Pradeep Kumar Singh, Saurav Dixit, Hanaa Kadhim Abdulaali, Rifaqat Ali, Pancham Cajla, Husam Rajab, Kaouther Ghachem

“…This study addresses the integration of machine learning (ML) and artificial intelligence (AI) for optimizing photovoltaic-thermal (PVT) systems. While ML modeling has become prevalent in this field, a significant gap remains in combining ML with AI-based optimization and decision-making methods to enhance PVT performance. …”
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Coordinated Operation of the Constituent Components of a Community Energy System to Maximize Benefits While considering the Network Constraints by A. H. Wijethunge, J. V. Wijayakulasooriya, J. B. Ekanayake, A. Polpitiya

“…The simulations show that the use of dynamic line rating and optimum appliance schedule provide higher profit to the community. The algorithm managed to run the optimization with 12,500 controllable entities within an average execution time of 2000s.…”
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Multi-Objective Optimization Research Based on NSGA-II and Experimental Study of Triplex-Tube Phase Change Thermal Energy Storage System by Yi Zhang, Haoran Yu, Yingzhen Hou, Neng Zhu

“…A multi-objective optimization method based on the elitist non-dominated sorting genetic algorithm (NSGA-II) was utilized to optimize the geometric dimensions (inner tube radius <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>r</mi><mn>1</mn></msub></semantics></math></inline-formula>, casing tube radius <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>r</mi><mn>2</mn></msub></semantics></math></inline-formula>, and outer tube radius <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>r</mi><mn>3</mn></msub></semantics></math></inline-formula>), focusing on heat transfer efficiency (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>ε</mi></semantics></math></inline-formula>), heat storage rate (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>P</mi><mi>t</mi></msub></semantics></math></inline-formula>), and mass (<i>M</i>). …”
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Machine learning-driven development of a stratified CES-D screening system: optimizing depression assessment through adaptive item selection by Ruo-Fei Xu, Zhen-Jing Liu, Shunan Ouyang, Qin Dong, Wen-Jing Yan, Dong-Wu Xu

“…Conclusions This study contributes to the refinement of CES-D by developing a machine learning-derived stratified screening version, offering an efficient and reliable approach that optimizes assessment burden while maintaining excellent psychometric properties. …”
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