Enhancing prediction of wildfire occurrence and behavior in Alaska using spatio-temporal clustering and ensemble machine learning by A. Ahajjam, M. Allgaier, R. Chance, E. Chukwuemeka, J. Putkonen, T. Pasch

“…First, NASA’s Fire Information for Resource Management System (FIRMS) dataset spanning +20 years is processed using a spatio-temporal clustering algorithm to create refined wildfire datasets. A sequential Genetic Algorithm (GA) is employed for cost-effective feature selection from 49 geospatial features, including remote sensing and reanalysis data. …”
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Nondestructive Detection of Moisture Content in Palm Oil by Using Portable Vibrational Spectroscopy and Optimal Prediction Algorithms by Ernest Teye, Charles L. Y. Amuah, Tai-Sheng Yeh, Regina Nyorkeh

“…Several preprocessing methods such as standard normal variant (SNV), multiplicative scatter correction (MSC), Savitzky–Golay first derivative (SGD1), Savitzky–Golay second derivative (SGD2) together with partial least square (PLS) regression techniques, full PLS, interval PLS (iPLS), synergy interval PLS (SiPLS), genetic algorithm PLS (GAPLS), and successive projection algorithm PLS (SPA-PLS) were comparatively employed to construct an optimum quantitative prediction model for moisture content in crude palm oil. …”
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Multiobjective Optimization Design for Structural Parameters of TBM Disc Cutter Rings Based on FAHP and SAMPGA by Laikuang Lin, Yimin Xia, Dun Wu

“…According to the characteristics of this model, a self-adaptive multipopulation genetic algorithm (SAMPGA) is utilized to solve the optimization problem, and the Fuzzy analytical hierarchy process (FAHP) is employed to calculate weight coefficients for multiple objectives. …”
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Simulation and Optimization of Acoustic Package of Dash Panel Based on SEA by Jintao Su, Ling Zheng, Jianping Lou

“…On this basis, multiobjective genetic algorithm and proxy model method are used to optimize the insertion loss of the front panel acoustic pack and the weight of the dashboard by introducing multiobjective variable and experimental design method, so as to obtain the best solution to meet the requirements of insertion loss and lightweight acoustic pack of the dashboard. …”
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A data-driven intelligent fault diagnosis framework for permanent magnet in PMSM by Huizhen Wang, Lei Wang, QiYa Wu, Haoying Pei, Lijun Diao

“…Second, fault diagnosis is carried out using the Genetic Algorithm-Support Vector Machine (GA-SVM) to accurately classify demagnetization faults. …”
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A Novel Optimization of Plug-In Electric Vehicles Charging and Discharging Behaviors in Electrical Distribution Grid by Haiming Fu, Yinghua Han, Jinkuan Wang, Qiang Zhao

“…Considering the constraints on the power transportation of branch, in the second phase, we built a mathematical model to maximize the benefit of both power grid and PEV owners. The genetic algorithm was used to optimize the charging and discharging power of PEVs. …”
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Integrated Optimization on Energy Saving and Quality of Service of Urban Rail Transit System by Wenxin Li, Qiyuan Peng, Chao Wen, Shengdong Li, Xu Yan, Xinyue Xu

“…We adopt the nondominated sorting genetic algorithm-II (NSGA-II) to solve the proposed model. …”
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Optimization and Experimental Study of an Intelligent Bamboo-Splitting Machine Charging Manipulator by Tian-Hu Liu, Yong-Lu Wen, Gui-Qi Li, Xiang-Ning Nie

“…The size of the manipulator was optimized here using a genetic algorithm. The capture rate, centering rate, and dynamic characteristics of an intelligent bamboo-splitting machine charging manipulator, in which key factors were considered, were experimentally studied. …”
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Digital-twin driven alignment control method for marine shafting with air spring vibration isolation system by Song Liu, Liang Shi, Wei Xu, ZeChao Hu

“…To obtain the optimal air spring pressures, the genetic algorithm is introduced to solve the optimization problem, fully exploiting its global search capacity. …”
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Virtual Node-Driven Cloud–Edge Collaborative Resource Scheduling for Surveillance with Visual Sensors by Xinyang Gu, Zhansheng Duan, Guangyuan Ye, Zhenjun Chang

“…Additionally, we propose three alternative virtual node-driven scheduling algorithms, the extension of a random algorithm, a genetic algorithm, and a heuristic algorithm, respectively. …”
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Numerical Investigation of Performance Improvement and Erosion Characteristics of Vortex Pump Using Particle Model by Daoxing Ye, Hao Li, Qiuyan Ma, Qibiao Han, Xiulu Sun

“…The relationship between geometric factors of vortex pump and efficiency and erosion rate of blade was established using the kriging approximation model. The genetic algorithm solved the multiobjective optimization and obtained the Pareto front solution using NSGA-II. …”
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An integrated modelling framework for optimization of the placement of grey-green-blue infrastructure to mitigate and adapt flood risk: An application to the Upper Ting River Water... by Jun Wu, Jiangang Xu, Muqiu Lu, Haolin Ming

“…Areas most suitable for GGBI construction are located along the Ting River, showing clear continuity and concentration in the central city and Xinqiao Town.（3）The optimized placement of GGBI, based on the SWMM model and non-dominated sorting genetic algorithm (NSGA-III), effectively reduces flood damage. …”
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Analysis of thermal characteristics of machine tool spindle based on lion swarm optimization algorithm by ZHANG ZhuangZhuang, WANG HongJun, WANG ZengXin

“…Compared with other optimization algorithms such as genetic algorithm, the LSO algorithm has faster convergence speed, higher accuracy, and better global optimal solution. …”
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Location Optimization for Community Smart Parcel Lockers Based on Bilevel Programming by Xia Yang, Chenyang Wang, Xiaozheng He, Hedi Zhang, Guangming Xu

“…Then, a solution algorithm based on the genetic algorithm is proposed. Finally, some numerical experiments are carried out based on a medium-scale residential community in Jiading District, Shanghai. …”
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Point and Interval Predictions for Tanjiahe Landslide Displacement in the Three Gorges Reservoir Area, China by Yankun Wang, Huiming Tang, Tao Wen, Junwei Ma, Zongxing Zou, Chengren Xiong

“…Second, a new LSSVM model optimized by a genetic algorithm (GA) was implemented to estimate the noise variance. …”
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Optimal Operation of Droop Control in Microgrids Using Different Techniques Optimization: Review by Ruqaya Majeed Kareem

“…These techniques include Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Grey Wolf Optimization (GWO), Grasshopper Optimization Algorithm (GOA), and Salp Swarm Algorithm (SSA)…”
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Enhanced Seismic Structural Reliability on Reinforced Concrete Buildings by Using Buckling Restrained Braces by Victor Baca, Juan Bojórquez, Edén Bojórquez, Herian Leyva, Alfredo Reyes-Salazar, Sonia E. Ruiz, Antonio Formisano, Leonardo Palemón, Robespierre Chávez, Manuel Barraza

“…For this aim, three traditional RC framed structures with 3, 6, and 9 story levels are designed by using the well-known technique nondominated sorting genetic algorithm (NSGA-II) in order to reduce the cost and maximize the seismic performance. …”
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Transactive energy management for efficient scheduling and storage utilization in a grid-connected renewable energy-based microgrid by Peter Anuoluwapo Gbadega, Olufunke Abolaji Balogun

“…Comparative analysis reveals that SMA consistently outperforms conventional methods such as Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) in terms of convergence speed and computational efficiency, making it particularly suitable for real-time energy management. …”
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A Novel on Energy Management Strategy with Maximum Exploitation of Renewables and EV Storage in Distribution Networks by K. Ramakrishna Reddy, C. H. Hussaian Basha, V. Prashanth, C. Dhanamjayulu, Sujata Shivashimpiger, R. Likhitha

“…A multiobjective genetic algorithm (MOGA) is employed to solve a formulated multiobjective optimization problem for load flattening and voltage regulation, with optimal power transaction (OPT) serving as the decision variable. …”
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A Real-Time Timetable Rescheduling Method for Metro System Energy Optimization under Dwell-Time Disturbances by Guang Yang, Junjie Wang, Feng Zhang, Shiwen Zhang, Cheng Gong

“…The real-time feature and self-adaptability of the method are attributed to the combinational use of Genetic Algorithm (GA) and Deep Neural Network (DNN). The decision system for proposing solutions, which contains multiple DNN cells with same structures, is trained by GA results. …”
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