Adaptive optimization decision system for plate-fin heat Exchangers: An integrated approach to enhancing efficiency and performance by Na Sun, Shuai Zhang, Nan Li, Zijian Li, Meng He, Zhengchun Shen, Ke Wang, Xiaoyong Guo, Wen-Quan Tao

“…The GSA module uses the Sobol method to evaluate the impact of design variables on performance. The optimization module employs the Newton-Raphson-based optimizer (NRBO) and the multi-strategy improved grey wolf optimization algorithm (MIGWO). …”
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An Optimized Spline-Based Registration of a 3D CT to a Set of C-Arm Images

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Parametric study and optimization of thermal performance and pressure drop in heat sinks with double-layer porous microchannels by Fahimeh Aliyari, Keivan Fallah, Hossein Zolfaghary Azizi, Farhad Hosseinnejad

“…Accordingly, the optimization process was pursued using the multi-objective genetic algorithm to find the optimal parameters that achieve the best thermal performance along with the lowest pressure drop, ensuring a desirable balance between improved thermal performance and reduced pressure drop. …”
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Research on Vibration Fatigue Damage Locations of Offshore Oil and Gas Pipelines Based on the GA-Improved BP Neural Network by Yaoguo Xie, Chengang Gao, Puzhe Wang, Lei Zhou, Chuanjie Zhang, Xianqiang Qu

“…To study vibration fatigue damage localization of offshore oil and gas pipelines, aiming at the location error caused by uncertainty of the initial parameters in backpropagation (BP) neural network training, an improved BP neural network based on the genetic algorithm (GA) is proposed to locate pipeline damage. …”
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Analysis and Optimization of a Moving Magnet Permanent Magnet Synchronous Planar Motor with Split Halbach Arrays by Ronglu Wang, Lu Zhang, Chenyang Shi, Chunqiu Zhao, Kai Yang

“…Multi-objective optimization using the non-dominated sorting genetic algorithm-II (NSGA-II) fine-tunes auxiliary magnet width and magnetization angles, resulting in a segmented auxiliary permanent magnet structure that achieves a 9.1% improvement in thrust density over conventional designs. …”
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Intelligent Approach to Robust Design Optimization of a Rotor System due to Its Support Stiffness Uncertainty by Bensheng Xu, Chaoping Zang, Genbei Zhang

“…In this paper, an intelligent robust design approach combined with different techniques such as polynomial chaos expansion (PCE), radial basis function (RBF) neural network, and evolutionary algorithms is presented with a focus on the optimization of the dynamic response of a rotor system considering support stiffness uncertainty. …”
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Maize Classification in Arid Regions via Spatiotemporal Feature Optimization and Multi-Source Remote Sensing Integration by Guang Yang, Jun Wang, Zhengyuan Qi

“…The recursive feature elimination random forest (RF-RFE) algorithm was employed for feature selection and model optimization. …”
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YOLOv10n-Based Defect Detection in Power Insulators: Attention Enhancement and Feature Fusion Optimization by Zhihao Wei, Yan Wei

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UAV-assisted MEC offloading strategy with peak AOI boundary optimization: A method based on DDQN by Zhixiong Chen, Jiawei Yang, Zhenyu Zhou

“…We also propose a deep machine learning-based multi-access edge computing offloading algorithm. First, a traffic arrival model is established in which the time interval follows the Beta distribution, and then a business service model is proposed based on the carrier sense multiple access with collision avoidance algorithm. …”
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Federated learning framework for IoT intrusion detection using tab transformer and nature-inspired hyperparameter optimization by Mohamed Abd Elaziz, Mohamed Abd Elaziz, Mohamed Abd Elaziz, Ibrahim A. Fares, Abdelghani Dahou, Mansour Shrahili

“…To address these challenges, this paper introduces a novel trust-centric FL framework based on the tab transformer (TTF) model for IDS. We enhance the Tab model through an optimization process, utilizing a hyperparameter tuning algorithm inspired by the nature-based electric eel foraging optimization (EEFO) algorithm. …”
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Enhancing Network Performance in Mitigating the Impact of Traffic Accidents with Full User Information by Seyyed Nader Shetab Boushehri, Hossain Poorzahedy, Reza Mahmoudi

“…Additionally, we propose a model for addressing the Accident Improvement Problem and put forth a heuristic algorithm to solve this model. …”
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Meta-Features Extracted from Use of kNN Regressor to Improve Sugarcane Crop Yield Prediction by Luiz Antonio Falaguasta Barbosa, Ivan Rizzo Guilherme, Daniel Carlos Guimarães Pedronette, Bruno Tisseyre

“…However, enhancing prediction models by incorporating new features extracted through regressions executed on the original dataset features can potentially improve predictive outcomes. …”
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RETRACTED: Bi-Level Optimization Dispatch of Integrated-Energy Systems With P2G and Carbon Capture by Zongnan Zhang, Jun Du, Menghan Li, Jing Guo, Zhenyang Xu, Weikang Li

“…Moreover, the upper model is solved by transforming the model into a mixed-integer linear programming problem and calling CPLEX, and the lower model is a multi-objective planning problem, which is solved by improving the small-habitat particle swarm algorithm. …”
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Face mask identification with enhanced cuckoo optimization and deep learning-based faster regional neural network by Binay Kumar Pandey, Digvijay Pandey, Mesfin Esayas Lelisho

“…Additionally, a deep neural network-based, the faster Region-Based Convolutional Neural Networks (R-CNN) algorithm combined with Adaptive Galactic Swarm Optimization (AGSO) is being used to identify appropriate and incorrect face mask wear in images, as well as to monitor social distancing among individuals in crowded areas. …”
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Optimization Strategy for Battery Swapping Station Scheduling Considering Coupling of Power Market and New Energy Source by WANG Yongli, ZHU Mingyang, ZHANG Yunfei, DONG Huanran, JIANG Sichong, LI Dexin, ZHU Jinrong, GUI Jiangyi

“…Taking 96 time slots as the scheduling granularity， a dual-objective model—maximizing economic benefits and optimizing new energy consumption—was established， and an improved Harris Hawk optimization algorithm was introduced to solve the problem. …”
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Optimizing transient gas network control for challenging real-world instances using MIP-based heuristics by Hennings, Felix, Hoppmann-Baum, Kai, Zittel, Janina

“…In this paper, we present the latest improvements of our ongoing work to tackle this problem for real-world, large-scale problem instances: By adjusting our mixed-integer non-linear programming model regarding the gas compression capabilities in the network, we reflect the technical limits of the underlying units more accurately while maintaining a similar overall model size. …”
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Optimization of load-bearing parameters for anisotropic nodes and prefabricated wall panels in prefabricated shear wall structures. by Jun Zhao, Libo Wang, Tengye Ma

“…Therefore, the study improves the quality information model for prefabricated nodes and the dragonfly algorithm by introducing principal component dimensionality reduction methods and multiple strategies through data modeling. …”
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Microstrip Patch Antenna Design Using a Four-Layer Feed Forward Artificial Neural Network Trained by Levenberg-Marquardt Algorithm by Jitu Prakash Dhar, Maodudul Hasan, Eisuke Nishiyama, Ichihiko Toyoda

“…The ANN contains a multi-layered network architecture that learns and generalizes complex patterns through the LM algorithm and weight optimization based on the datasets without any feature extraction like Deep Neural Network (DNN). …”
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Enhancing MANET Security Through Federated Learning and Multiobjective Optimization: A Trust-Aware Routing Framework by Saad M. Hassan, Mohd Murtadha Mohamad, Farkhana Binti Muchtar, Firoz Bin Yusuf Patel Dawoodi

“…MOO, particularly nondominated sorting genetic algorithm III, effectively balances conflicting network objectives, offering a 15% improvement in overall network performance compared with single-objective approaches. …”
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Hybrid machine learning and physics-based model for estimating lettuce (Lactuca sativa) growth and resource consumption in aeroponic systems by Benedetta Fasciolo, Nicolò Grasso, Giulia Bruno, Paolo Chiabert

“…Despite these challenges, the hybrid model offers a promising solution for optimizing controlled environment agriculture, addressing critical challenges in modern agriculture by improving efficiency and sustainability.…”
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