Optimization Design of Centrifugal Fan Blades Based on Bézier Curve Method by Jiaju Wang, Kunfeng Liang, Tao He, Haijiang He, Dayuan Zheng, Min Li, Dewu Gong, Lihua Jiang

“…In order to improve the aerodynamic performance of the voluteless centrifugal fan, a multi-objective optimization design system was established by combining parametric modeling, experimental design, surrogate models, and optimization algorithms, with the static pressure and static pressure efficiency of the fan as the optimization objectives. …”
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Redefining Trauma Triage for Elderly Adults: Development of Age-Specific Guidelines for Improved Patient Outcomes Based on a Machine-Learning Algorithm by Ji Yeon Lim, Yongho Jee, Seong Gyu Choi, Yoon Hee Choi, Sam S. Torbati, Carl T. Berdahl, Sun Hwa Lee

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D³-YOLOv10: Improved YOLOv10-Based Lightweight Tomato Detection Algorithm Under Facility Scenario by Ao Li, Chunrui Wang, Tongtong Ji, Qiyang Wang, Tianxue Zhang

“…However, under the facility scenario, existing detection algorithms still have challenging problems such as weak feature extraction ability for occlusion conditions and different fruit sizes, low accuracy on edge location, and heavy model parameters. …”
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Cost-Based Optimal Allocation of Shunt Capacitors in Radial Distribution Networks Considering Load Types Using Crow Search Algorithm by Stephen W. Mathenge, Edwell. T. Mharakurwa, Lucas Mogaka

“…The highest TOAC was observed for CZ loads ($303,570.2), while the lowest was for CI loads ($195,386.4), reflecting the economic influence of load model variation. To ensure practical applicability and robustness, a sensitivity analysis of optimization algorithms under varying load models was performed. …”
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Self-Tuning Parameters of the Proposed Fuzzy Immune Integral Controller to Improve the Performance of the Standard P&O-MPPT Strategy by Ramazan Ayaz

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Optimum design of double tuned mass dampers using multiple metaheuristic multi-objective optimization algorithms under seismic excitation by Fateme Zamani, Sayyed Hadi Alavi, Mohammadreza Mashayekhi, Ehsan Noroozinejad Farsangi, Ataallah Sadeghi-Movahhed, Ali Majdi

“…The tuning process is carried out using a combination of Pareto front derived from seven multi-objective metaheuristic optimization algorithms with two objectives. The proposed methodology is applied to a 10-floor case study, using ground acceleration time histories to evaluate its seismic performance. …”
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A Novel Multi-Objective Hybrid Evolutionary-Based Approach for Tuning Machine Learning Models in Short-Term Power Consumption Forecasting by Aleksei Vakhnin, Ivan Ryzhikov, Harri Niska, Mikko Kolehmainen

“…The proposed algorithm simultaneously optimizes both hyperparameters and feature sets across six different ML models, ensuring enhanced accuracy and efficiency. …”
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A Hierarchical Path Planning Framework of Plant Protection UAV Based on the Improved D3QN Algorithm and Remote Sensing Image by Haitao Fu, Zheng Li, Jian Lu, Weijian Zhang, Yuxuan Feng, Li Zhu, He Liu, Jian Li

“…To address these challenges, this study proposes a deep reinforcement learning algorithm, MoE-D3QN, which integrates a Mixture-of-Experts mechanism with a Bi-directional Long Short-Term Memory model. …”
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Multiobjective Optimization of Turbine Coolant Collection/Distribution Plenum Based on the Surrogate Model by Junsheng Chai, Zhenyu Wang, Xuanling Zhao, Chunhua Wang

“…Based on these data sampling, least square support vector machine (LS-SVM) was used for the surrogate model, and a kind of chaotic optimization algorithms was used for searching for the Pareto solution set. …”
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Optimization design of an acoustic cover layer for a cylindrical cavity based on porous materials by Bohan ZHANG, Jili RONG, Xiuyan CHENG

“…In this study, a comprehensive investigation into the parameter fitting and acoustic performance optimization of porous materials is conducted, utilizing advanced physical models, multifluid impedance transfer theory, and particle swarm optimization algorithms. …”
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An Integrated Supply Chain Model for Predicting Demand and Supply and Optimizing Blood Distribution by Pooria Bagher Niakan, Mehdi Keramatpour, Behrouz Afshar-Nadjafi, Alireza Rashidi Komijan

“…Genetic algorithms (GA) and particle swarm optimization (PSO) are used to solve mathematical models quickly and efficiently, ensuring reliable operation. …”
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Differentiable Deep Learning Surrogate Models Applied to the Optimization of the IFMIF-DONES Facility by Galo Gallardo Romero, Guillermo Rodríguez-Llorente, Lucas Magariños Rodríguez, Rodrigo Morant Navascués, Nikita Khvatkin Petrovsky, Rubén Lorenzo Ortega, Roberto Gómez-Espinosa Martín

“…The substantial speed-up factors enable the application of online reinforcement learning algorithms, and the differentiable nature of the models allows for seamless integration with differentiable programming techniques, facilitating the solving of inverse problems to find the optimal parameters for a given objective. …”
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Application of Machine Learning Models in Optimizing Wastewater Treatment Processes: A Review by Florin-Stefan Zamfir, Madalina Carbureanu, Sanda Florentina Mihalache

“…Thus, this paper identifies gaps in the current research, discusses ML and DL algorithms in the context of optimizing wastewater treatment processes, and identifies future directions for optimizing these processes through data-driven methods. …”
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A Novel DV-Hop Localization Method Based on Hybrid Improved Weighted Hyperbolic Strategy and Proportional Integral Derivative Search Algorithm by Dejing Zhang, Pengfei Li, Benyin Hou

“…Secondly, the localization error is further reduced by employing the improved PSA. In addition, the selection process of the node set is optimized using progressive sample consensus (PROSAC) followed by a 3D hyperbolic algorithm based on coplanarity. …”
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Optimization of Construction Projects Time-Cost-Quality-Environment Trade-off Problem Using Adaptive Selection Slime Mold Algorithm by Pham Vu Hong Son, Luu Ngoc Quynh Khoi

“…To improve the suggested model's superiority and effectiveness, it is compared to the multiple-target swarm algorithm (MOPSO), multi-objective artificial bee colony (MOABC) and non-dominant sort genetic algorithm (NSGA-II). …”
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Logistics Hub and Route Optimization in the Physical Internet Paradigm by Hisatoshi Naganawa, Enna Hirata, Nailah Firdausiyah, Russell G. Thompson

“…<i>Methods:</i> We propose a novel demography-weighted combinatorial optimization model utilizing a genetic algorithm and the Lin–Kernighan heuristic. …”
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Volt/VAr Regulation of the West Mediterranean Regional Electrical Grids Using SVC/STATCOM Devices With Neural Network Algorithms by H. Feza Carlak, Ergin Kayar

“…A load flow and short circuit analysis is performed on the designed transmission system for a number of critical scenarios. The modeled power system is optimized for the size and location of the FACTS devices by applying genetic algorithms (GAs) and particle swarm optimization (PSO) algorithms to the selected busbars of the FACTS devices, a strategy designed to significantly reduce system losses. …”
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Intelligent anti-jamming decision algorithm of bivariate frequency hopping pattern based on ET-PPO by Yibo CHEN, Zhijin ZHAO

“…In order to further improve its anti-interference ability in complex electromagnetic environment, a PPO algorithm based on weighted importance sampling and eligibility traces (ET-PPO) was proposed.On the basis of the traditional frequency hopping pattern, time-varying parameters were introduced, and the bivariate frequency hopping pattern decision problem was modeled as a Markov decision problem through the construction of the state-action-reward triple.Aiming at the high variance problem of the sample update method of an actor network of the PPO algorithm, weighted importance sampling was introduced to reduce the variance, and the action selection strategy of Beta distribution was used to enhance the stability of the learning stage.Aiming at the problem of slow convergence speed of the evaluator network, the eligibility trace method was introduced, which better balanced the convergence speed and the global optimal solution.The algorithm comparison simulation results in different electromagnetic interference environments show that ET-PPO has better adaptability and stability, and has better performance against obstruction interference and sweep frequency interference.…”
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Structural Parameter Identification Using Multi-Objective Modified Directional Bat Algorithm by LIU Li-jun, LIN Ying-hai, SU Yong-hui, LEI Ying

“…This approach improved the accuracy and robustness of structural parameter identification while maintaining computational efficiency.MethodsMOMDBA is an enhanced version of the Directional Bat Algorithm （DBA）， a swarm intelligence optimization technique inspired by the echolocation behavior of bats. …”
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Tomato Yield Estimation Using an Improved Lightweight YOLO11n Network and an Optimized Region Tracking-Counting Method by Aichen Wang, Yuanzhi Xu, Dong Hu, Liyuan Zhang, Ao Li, Qingzhen Zhu, Jizhan Liu

“…The particle swarm optimization (PSO) algorithm was used to optimize the detection region, thus enhancing the counting accuracy. …”
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