Mengxia Li’s scientific contributions

... In recent years, the Laboratory of Complex Systems and Computational Intelligence of Taiyuan University of Science and Technology [20][21][22][23][24][25][26][27][28][29] has done a lot of research on data storage and modeling methods and has obtained a series of research results, among which the new modeling technology mentioned provides reference data for better solving the problem of damage inducement inversion model in this paper. In the follow-up research, we will further optimize the modeling method and deepen the related research of this paper. ...

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Symmetry Study on Damage Inversion of Wharf Pile Foundation in Three Gorges Reservoir Area Under Ship Impact

... The algorithm has the characteristics of simple theory, easy implementation, and good solving performance, and is suitable for solving large-scale complex optimization problems, including ELD problems [32]. Therefore, many scholars have conducted in-depth research and applied it to different fields [33]. For example, Song, H.M. et al. [34] proposed an improved POA based on chaotic interference factors and essential mathematical functions and applied it to four engineering design problems. ...

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Research on Economic Load Dispatch Problem of Microgrid Based on an Improved Pelican Optimization Algorithm

... The absence of a proactive standard model for evaluating fault tolerance approaches in the cloud highlights the need for further consideration in developing a proactive fault tolerance approach that can control resource load fluctuations and enhance failure prediction accuracy prior to actual faults or failures occurring. • Heterogeneity in both computational resources and applications enhances both the solution space and optimal solution yield time in cloud workflow scheduling as an NP-hard problem, whereby metaheuristic algorithms have become well known in solving this problem (Mokni et al. 2023;Zhang et al. 2023). Every metaheuristic algorithm has its strengths and Regarded as computeintensive workflows in earthquake science and biology; c is the I/O intensive workflow from astronomy; d, e belong to data-intensive workflows in gravitational physics and biology, respectively limitations, and both affect the cloud workflow scheduling processes. ...

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A fault-tolerant scheduling strategy through proactive and clustering techniques for scientific workflows in cloud computing