SMOTE algorithm optimization and application in corporate credit risk prediction with diversification strategy consideration by Han Wei

“…On one hand, this study focuses on optimizing the Synthetic Minority Over-Sampling Technique (SMOTE) algorithm for corporate credit risk prediction, thereby enhancing financial institutions’ risk management capabilities. …”
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Optimization of IMU-based bending strain solving algorithm and full-scale experimental validation by Tong SHI, Xiaoben LIU, Lin ZHANG, Jun WANG, Rui LI, Ting Xie, Qingshan FENG, Qiyu HUANG

“…Moreover, a solving algorithm optimized through an ANNExtraTree deep learning model was introduced. …”
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Research on Optimized Algorithm for Deep Learning Based Recognition of Sediment Particles in Turbulent Flow by WANG Hao, YANG Feiqi, ZHANG Lei, WU Wei, XIE Haonan, ZHAO Lin

“…It further investigates the relationship between turbulent coherent structures and the intensity of particle movement, clarifying the mechanism through which turbulent coherent structures influence sediment transport.MethodsThe optimization algorithm developed in this study aims to maximize the detection of moving particles, providing more accurate data to support understanding sediment transport patterns at the particle scale and their association with turbulent coherent structures. …”
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An energy-efficient routing protocol for wireless body area networks using hybrid artificial bee colony optimization and chicken swarm optimization algorithm by A. Dinesh, J. Rangaraj

“…To begin, this work presents an efficient algorithm named “Artificial Bee Colony Optimization (ABC) and Chicken Swarm Optimization (CSO) algorithm” to create hybrid trees for data aggregation in networks. …”
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Gravitational search algorithm optimization algorithm for grid distributed energy storage resource pool regulation matching load peak–valley and operation constraints by Zhichao Lin, Busheng Luo, Yingmin Wang, Lingfei Xie, Xiangyang Su, Gang Chen, Yuting Huang

“…Consequently, this study investigates the GSA optimization algorithm for regulating distributed energy storage resource pools in the power grid, which can address load peaks and valleys while adhering to operational constraints. …”
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Facial recognition optimization based on adversarial sample generation in the field of artificial intelligence by Jie Yang

“…Firstly, the traditional AdaBoost is improved using particle swarm optimization algorithm and dual threshold classification method. …”
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Optimizing Pile Bearing Capacity Prediction Using Specific Random Forest Models Optimized by Meta-Heuristic Algorithms for Enhanced Geomechanically Applications by Nengyuan Chen

“…To achieve highly accurate predictions of Pile Bearing Capacity (PBC), the study employs a cutting-edge approach featuring Specific Random Forest (RF) prediction models, strategically enhanced with two potent meta-heuristic algorithms: the Snake Optimizer (SO) and the Equilibrium Optimizer (EO). …”
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Optimizing Pharmaceutical Inventory and Investment Strategies During Pandemics: A Dynamic Approach Integrating Environmental Emission Rates and Advanced Optimization Algorithms by Vinita Dwivedi, Mamta Keswani, Uttam Kumar Khedlekar, Lalji Kumar

“…This study presents a strategy for managing pharmaceutical inventory during pandemics, focusing on optimizing investment in COVID-19 medicines while ensuring product preservation. …”
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On the development of a practical Bayesian optimization algorithm for expensive experiments and simulations with changing environmental conditions by Mike Diessner, Kevin J. Wilson, Richard D. Whalley

“…ENVBO finds solutions for the entire domain of the environmental variable that outperform results from optimization algorithms that only focus on a fixed environmental value in all but one case while using a fraction of their evaluation budget. …”
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Memetic Salp Swarm Algorithm for economic load dispatch problems by Mohammed A. Awadallah, Mohammed Azmi Al-Betar, Malik Braik, Raed Abu Zitar, Khaled Assaleh, Mahmud Alkoffash, Qusai Yousef Shambour

“…This hybridization scheme is known as a memetic algorithm, where SSA serves as a natural selection agent (general refinement) in a genotype environment, while A $$\beta$$ HCO serves as a culture selection agent (local refinement) in a phenotype environment. …”
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Integrated Optimization of Pipe Routing and Clamp Layout for Aeroengine Using Improved MOALO by Qiang Liu, Zhi Tang, Huijuan Liu, Jiapeng Yu, Hui Ma, Yonghua Yang

“…To this end, the MOALO (multiobjective ant lion optimizer) algorithm is modified by introducing the levy flight strategy to improve the global search performance and convergence speed, and it is further used as a basic computation tool. …”
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Gutek: Intelligent Revision Algorithms by Lukasz Galka

“…This paper introduces Gutek, a novel open-source framework designed to optimize the learning process through intelligent revision algorithms. …”
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Dynamic Optimization of Xylitol Production Using Legendre-Based Control Parameterization by Eugenia Gutiérrez, Marianela Noriega, Cecilia Fernández, Nadia Pantano, Leandro Rodriguez, Gustavo Scaglia

“…The proposed technique employs Legendre polynomials to parameterize two control actions (the feeding rates of glucose and xylose), and it uses a hybrid optimization algorithm combining Monte Carlo sampling with genetic algorithms for coefficient selection. …”
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Fault Diagnosis System of Induction Motors Based on Neural Network and Genetic Algorithm Using Stator Current Signals by Tian Han, Bo-Suk Yang, Won-Ho Choi, Jae-Sik Kim

“…GA is used to select the most significant features from the whole feature database and optimize the ANN structure parameter. …”
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Black Hole Algorithm for Software Requirements Prioritization by Norah Ibrahim Alfassam, M. Abdullah-Al-Wadud, Mubarak Rashed Alrashoud

“…Furthermore, the proposed BHA-based solution was evaluated on three real-world datasets (RALIC, Word, and ReleasePlanner), and its performance was compared with that of multiple state-of-the-art algorithms, including Ant Colony Optimization (ACO), Genetic Algorithm (GA), Grey Wolf Optimizer (GWO), Particle Swarm Optimization (PSO), Fitness Dependent Optimizer (FDO), Goose Algorithm (GAO), and Lagrange Elementary Optimization (LEO). …”
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A comprehensive review of artificial intelligence approaches for smart grid integration and optimization by Malik Ali Judge, Vincenzo Franzitta, Domenico Curto, Andrea Guercio, Giansalvo Cirrincione, Hasan Ali Khattak

“…An efficient Energy Management System (EMS) is essential to deal with uncertainties associated with renewable energy production and load demand while optimizing the operation of distributed energy generation sources. …”
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An Optimization Method for Multi-Robot Automatic Welding Control Based on Particle Swarm Genetic Algorithm by Lu Chen, Jie Tan, Tianci Wu, Zengxin Tan, Guobo Yuan, Yuhao Yang, Chiang Liu, Haoyu Zhou, Weisi Xie, Yue Xiu, Gun Li

“…Then, the PSO (particle swarm optimization) algorithm, which integrates penalty functions into the fitness evaluation, is used to determine the optimal welding path by simulating collective behavior within a group. …”
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Enhanced skill optimization algorithm: Solution to the stochastic reactive power dispatch framework with optimal inclusion of renewable resources using large‐scale network by Noor Habib Khan, Yong Wang, Raheela Jamal, Sheeraz Iqbal, Mohamed Ebeed, Yazeed Yasin Ghadi, Z. M. S. Elbarbary

“…The normal, lognormal, and Weibull distributions are utilized to model system uncertainties, while Monte‐Carlo simulation and reduction‐based approaches are utilized to generate the novel set of optimal scenarios. …”
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A Markov decision optimization of medical service resources for two-class patient queues in emergency departments via particle swarm optimization algorithm by Chia-Hung Wang, Rong Tian, Kun Hu, Yu-Tin Chen, Tien-Hsiung Ku

“…The particle swarm optimization algorithm was applied to determine the optimal number of servers, service rate, and number of beds. …”
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Energy efficient optimal sink position selection algorithm for multi-sink wireless sensor networks by TANG Wei, GUO Wei

“…In combination with the energy efficient routing algorithm,the optimal sink position selection problem was studied,which aimed to minimize the overall network energy consumption.When the candidate set of sink positions is finite,the problem is shown to be an integer linear programming problem,when the candidate set is the whole space,the problem is shown to be a nonlinear programming problem.Due to the NP-completeness of the problems,several heuristic algorithms were designed accordingly.The proposed algorithms were examined by extensive simulation experiments,the results show that the performances of presented algorithms are close to the optimality.…”
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