Human Activity Recognition Using Graph Structures and Deep Neural Networks by Abed Al Raoof K. Bsoul

“…To address this, we applied the Firefly Optimization Algorithm to fine-tune the hyperparameters of both the graph-based model and a CNN baseline for comparison. …”
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Application of Three Neural Network Models in the Prediction ofStratospheric Wind Field by YUAN Junjie, LUO Rubin, LIAO Jun, YANG Zechuan, WANG Ning, LI Jun

“…The prediction accuracy of the BP neural network optimized by particle swarm optimization is slightly better than that of the BP neural network optimized by genetic algorithm.…”
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Advancing Pile-Bearing Capacity Prediction with Meta-Heuristic Enhanced Specific ANFIS strategys by Zhongmiao Dang

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Advances in Digital Signature Algorithms: Performance, Security and Future Prospects by Lyu Shuhan

“…The results show that while optimizations improve computational efficiency, challenges persist, especially with potential quantum threats that could undermine these algorithms' security. …”
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Advanced Design of Naval Ship Propulsion Systems Utilizing Battery-Diesel Generator Hybrid Electric Propulsion Systems by Youngnam Park, Heemoon Kim

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Improving Genetic Algorithm with Fine-Tuned Crossover and Scaled Architecture by Ajay Shrestha, Ausif Mahmood

“…Genetic Algorithm (GA) is a metaheuristic used in solving combinatorial optimization problems. …”
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An Evolutionary Algorithm for Solving Academic Courses Timetable Scheduling Problem by Israa Abdulameer Abduljabbar, Sura Mahmood Abdullah

“… Scheduling Timetables for courses in the big departments in the universities is a very hard problem and is often be solved by many previous works although results are partially optimal. This work implements the principle of an evolutionary algorithm by using genetic theories to solve the timetabling problem to get a random and full optimal timetable with the ability to generate a multi-solution timetable for each stage in the collage. …”
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Firefly algorithm with multiple learning ability based on gender difference by Wenning Zhang, Chongyang Jiao, Qinglei Zhou

“…Abstract The Firefly Algorithm (FA), while effective for complex optimization, suffers from inherent limitations such as search oscillation and low convergence precision. …”
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The Path Planning of Mobile Robots Based on an Improved Genetic Algorithm by Zheng Zhang, Haobo Yang, Xusheng Bai, Shuo Zhang, Chaobin Xu

“…Bezier curve optimization of the optimal path was conducted. Experimental results show that the improved genetic algorithm demonstrates significant advantages in terms of path length, smoothness, iteration speed, and computational efficiency.…”
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An Efficient Illumination Estimation Algorithm for Low-Light Image Enhancement by Tirui Wu, Martin Glavin, Edward Jones

“…The key step of this algorithm is illumination map refinement, which is achieved by solving an optimization problem. …”
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Application of Artificial Intelligence Computer Intelligent Heuristic Search Algorithm by Fanghai Gong

“…After 114 iterations of the heuristic search algorithm, the optimal value is 6.83353635e-001, while the average optimal value is 6.83551939e-001. …”
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Retinal Vessel Segmentation Using Math-Inspired Metaheuristic Algorithms by Mehmet Bahadır Çetinkaya, Sevim Adige

“…Math-inspired metaheuristic algorithms can be considered to be one of the most robust groups of algorithms, while also generally presenting non-complex structures. …”
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An Interleaved Artificial Bee Colony algorithm for dynamic optimisation problems by Salwani Abdullah, Shams K. Nseef, Ayad Turky

“…This requires an optimisation algorithm that should be able to monitor the movement of the optimal point and the changes in the landscape solutions. …”
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Improved SOM algorithm for damage characterization based on visual sensing by Hongtao Zhu, Shuyun Guo

“…Additionally, employing stochastic gradient descent as an optimization algorithm enhances the model training efficiency. …”
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Adaptive dynamic ϵ-simulated annealing algorithm for tumor immunotherapy by Xiaoyan Sun, Xiaoyan Sun, Ying Jiang

“…When applied to the ITIT model, the algorithm successfully identified optimal drug dosing schedules that significantly reduced simulated tumor burden—from ~1500 to below 500 cells—while maintaining treatment within physiologically acceptable limits.DiscussionUnlike traditional metaheuristics such as PSO or GA, which are less suited for constraint-rich, dynamic ODE-based systems, ADϵSA offers structural advantages in trajectory feasibility and adaptive convergence. …”
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Visual Multiple-object Tracking Algorithm Based on Motion Consistency by YANG Hailang, LYU Yu, JIANG Guotao, PI Zhichao, LUO Shuo, CHEN Meilin

“…The algorithm aims to improve the stability in tracking multiple objects with similar appearance features and motion patterns, while maintaining stability in normal cases. …”
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A Genetic Algorithm for Site-Specific Management Zone Delineation by Francisco Huguet, Lluís M. Plà-Aragonés, Víctor M. Albornoz, Mauricio Pohl

“…A SSMZ is a subregion of a field that is homogeneous with respect to a soil or crop property, enabling farmers to apply customized management strategies for optimizing resource use. The algorithm generates optimized field partitions using rectangular zones, applicable to both regular and irregularly shaped fields. …”
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Study on the gas outflow pattern and outflow prediction model of the return mining face under complex geological conditions by Yi Sun, Lulin Zheng, Hong Lan, Zhaoxing Yu, Jin Wang, Bo Li, Feng Yang, Fangbo Wen

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A solution to the Single-School school bus routing problem considering accessibility and economy by Zizhan Jiang, Jiying Wang, Siyuan Huang, Hua Daniel Xu

“…In the third stage, Dijkstra’s algorithm is combined with GIS to optimize the bus routes, with a focus on accessibility and economy.Experimental results demonstrate that the THGO method can efficiently find the global optimal solution while satisfying constraints such as time windows, bus capacity, and road directionality. …”
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An Efficient Resource Allocation Algorithm for Task Offloading in the Internet of Vehicles by Ahmad Salehi, Sadoon Azizi

“…Simulation results demonstrate that the proposed algorithm reduces memory costs and penalties from rejected tasks, while improving overall system profit. …”
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