A Linear Fitting Algorithm Based on Modified Random Sample Consensus by Yujin Min, Yun Tang, Hao Chen, Faquan Zhang

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Integrated transportation system planning with gravitational search algorithm approach based on fuzzy mutant controller by Alireza Hosseinzadeh Kashani, Seyed Ahmad Shayannia, Mohammad Mehdi Movahedi, Soheila Sardar

“…In these relations, <strong>3r </strong>is a uniform random variable in the interval [1,0], which is used to create the random property of the speed of the particle population optimization algorithm and the acceleration of the gravitational search algorithm in the gravitational particle population algorithm, and <strong>3C </strong>and <strong>4C</strong> are two constants to determine the degree of the speed of the particle population optimizer algorithm and the acceleration of the gravitational search algorithm in the gravitational particle population algorithm the values of which are considered 3C and 4C. …”
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TS-SSA: An improved two-stage sparrow search algorithm for large-scale many-objective optimization problems. by Xiaozhi Du, Kai Chen, Hongyuan Du, Zongbin Qiao

“…In the first stage of TS-SSA, this paper proposes a many-objective sparrow search algorithm (MaOSSA) to mainly manages the convergence through the adaptive population dividing strategy and the random bootstrap search strategy. …”
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A stacked ensemble machine learning model for the prediction of pentavalent 3 vaccination dropout in East Africa by Meron Asmamaw Alemayehu, Shimels Derso Kebede, Agmasie Damtew Walle, Daniel Niguse Mamo, Ermias Bekele Enyew, Jibril Bashir Adem

“…The objective is to identify predictors of dropout and enhance intervention strategies.MethodsThe study utilized seven base machine learning algorithms to create a stacked ensemble model with three meta-learners: Random Forest (RF), Generalized Linear Model (GLM), and Extreme Gradient Boosting (XGBoost). …”
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Securing IoT Communications via Anomaly Traffic Detection: Synergy of Genetic Algorithm and Ensemble Method by Behnam Seyedi, Octavian Postolache

“…The second phase focuses on optimal feature selection using a Genetic Algorithm enhanced with eagle-inspired search strategies. …”
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Enhanced Automatic Generation Control in Multiarea Power Systems: Crow Search Optimized Cascade FOPI‐TIDDN Controller With Integrated Renewable Solar Thermal Models and HVDC Lines... by Naladi Ram Babu, Pamarthi Sunitha, Ganesh Pardhu B. S. S., Sanjeev Kumar Bhagat, Adireddy Ramesh, Arindita Saha, Wulfran Fendzi Mbasso, Pradeep Jangir, Ahmed Hossam‐Eldin

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Research on vehicle scheduling for forest fires in the northern Greater Khingan Mountains by Jie Zhang, Junnan He, Shihao Ren, Pei Zhou, Jun Guo, Mingyue Song

“…Improvement of ordinary genetic algorithm, design of double population strategy selection operation, the introduction of chaotic search initialization population, to improve the algorithm’s solution efficiency and accuracy, through the northern pristine forest area of Daxing’anling real forest fire cases and generation of large-scale random fire point simulation experimental test to verify the effectiveness of the algorithm, to ensure that the effectiveness and reasonableness of the solution to the problem of forest fire emergency rescue vehicle scheduling program. …”
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Photovoltaic Hosting Capacity Assessment of Distribution Networks Considering Source–Load Uncertainty by Chao Chen, Weifeng Peng, Cheng Xie, Shufeng Dong, Yibo Hua

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Using Anomaly Detection to Search for Technosignatures in Breakthrough Listen Observations by Snir Pardo, Dovi Poznanski, Steve Croft, Andrew P. V. Siemion, Matthew Lebofsky

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An RFCSO-based grid stability enhancement by integrating solar photovoltaic systems with multilevel unified power flow controllers by Swetha Monica Indukuri, Alok Kumar Singh, D. Vijaya Kumar

“…Furthermore, the ML-UPFC, controlled by a random forest cuckoo search optimization algorithm, enhances the fault ride-through capabilities and power regulation. …”
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Optimization Methods for Customized Bus Routes in Random Environments by Fangyuan Gong, Chuanjun Jia, Xu Wu

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Multiple objectives escaping bird search optimization and its application in stock market prediction based on transformer model by Dedai Wei, Zimo Wang, Minyu Qiu, Juntao Yu, Jiaquan Yu, Yurun Jin, Xinye Sha, Kaichen Ouyang

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Comparative analysis of machine learning algorithms for predicting depression among individuals with diabetes by Hind Bourkhime, Noura Qarmiche, Soumaya Benmaamar, Nada Lazar, Mohammed Omari, Mohamed Berraho, Nabil Tachfouti, Samira El Fakir, Hanan El Ouahabi, Nada Otmani

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Universal Simulation Model of Battery Degradation with Optimization of Parameters by Genetic Algorithm by K. V. Dobrego, I. A. Koznacheev

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Precise wind allocation scheme decision based on attraction-repulsion algorithm by NI Jingfeng, CHEN Dunwei, LIU Yujiao

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Routing algorithm for heterogeneous computing force requests based on computing first network by ZHANG Gang, LI Xi

“…An optimized genetic algorithm to address this issue was proposed. This algorithm was designed from both local and global perspectives: to ensure fast convergence to the target solution locally, a single parameter satisfying the randomness strategy was used to initialize the population, making it widely dispersed in the solution space; adopting a multi-parameter solution (or path) balanced selection strategy for selection operations, making the selected population rich and diverse; adopting a two-layer crossover strategy for crossover operations, with the aim of expanding the breadth of global search; adopting a multi parameter random single point mutation strategy for mutation operations, with the aim of deepening local search capabilities. …”
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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

“…MOMDBA addressed these limitations through three key improvements： 1） Individual Historical Best Position Tracking： This feature allowed the algorithm to retain and utilize the best individual solutions encountered during the search process， improving its ability to explore the solution space effectively. 2） Hybrid Global-Local Search Strategy： By combining global exploration with local exploitation， MOMDBA enhanced its ability to converge towards optimal solutions while avoiding local optima. 3） Elimination Mechanism： To maintain population diversity and prevent stagnation， low-performing individuals were periodically replaced with new solutions. …”
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Robust parameter inversion of coal mining subsidence based on the combination of RANSAC and DE algorithms by Yuanfei Chen, Lei Wang

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GAGAN: Enhancing Image Generation Through Hybrid Optimization of Genetic Algorithms and Deep Convolutional Generative Adversarial Networks by Despoina Konstantopoulou, Paraskevi Zacharia, Michail Papoutsidakis, Helen C. Leligou, Charalampos Patrikakis

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Exploring genomic feature selection: A comparative analysis of GWAS and machine learning algorithms in a large‐scale soybean dataset by Hawlader A. Al‐Mamun, Monica F. Danilevicz, Jacob I. Marsh, Cedric Gondro, David Edwards

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