Short-Term Power Load Forecasting Using an Improved Model Integrating GCN and Transformer by Man Wu, Wanyi Feng, Xinya Li, Yunan Liu, Chuxin Cao

“…Improving the accuracy of power load forecasting is an important link in the optimization of power systems. …”
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Mapping and interpretability of aftershock hazards using hybrid machine learning algorithms by Bo Liu, Haijia Wen, Mingrui Di, Junhao Huang, Mingyong Liao, Jingyuan Yu, Yutao Xiang

“…By employing the stacking algorithm to optimize and combine XGBoost and LightGBM models, the proposed model significantly improves the prediction performance. …”
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A Hybrid Optimization Approach for Improving Sensor Configuration to Enhance Nasogastric Tube (NGT) Localization During Insertion and Withdrawal by M. Souganttika, Shaohui Foong

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Discrete Optimization Model and Algorithm for Driver Planning in Periodic Driver Routing Problem by Lin Huang, Wenya Lv, Qian Sun, Chengle Ma

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The Crossover strategy integrated Secretary Bird Optimization Algorithm and its application in engineering design problems by Xiongfa Mai, Yan Zhong, Ling Li

“…An improved metaheuristic algorithm called the Crossover strategy integrated Secretary Bird Optimization Algorithm (CSBOA) is proposed in this work for solving real optimization problems. …”
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Alzheimer’s Prediction Methods with Harris Hawks Optimization (HHO) and Deep Learning-Based Approach Using an MLP-LSTM Hybrid Network by Raheleh Ghadami, Javad Rahebi

“…<b>Method:</b> This proposal methodology involves sourcing Alzheimer’s disease-related MRI images and extracting features using convolutional neural networks (CNNs) and the Gray Level Co-occurrence Matrix (GLCM). The Harris Hawks Optimization (HHO) algorithm is applied to select the most significant features. …”
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Integrating Artificial Intelligence and Computational Algorithms to Optimize the 15-Minute City Model by Marwa Abouhassan, Samah Elkhateeb, Raneem Anwar

“…Furthermore, it elaborates on how the integration of artificial intelligence (AI) and computational tools can be utilized in optimizing the 15-minute city model. We reveal how AI-driven algorithms, machine learning techniques, and advanced data analytics can enhance urban planning, improve accessibility, and foster social integration. …”
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An optimization model of computer network security based on GABP neural network algorithm by Jiangang Wang, Xiaoyan Wang

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Optimization model for enterprise financial management utilizing genetic algorithms and fuzzy logic by Sujuan Wang, Musadaq Mansoor

“…A multi-objective mathematical model is first developed to establish key optimization goals, including cost reduction, improved capital utilization, and increased economic benefits. …”
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A hybrid renewable energy system for Hassi Messaoud region of Algeria: Modeling and optimal sizing by Yacine Bourek, El Mouatez Billah Messini, Chouaib Ammari, Mohamed Guenoune, Boulerbah Chabira, Bipul Krishna Saha

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Explanation and Optimizing Multi‐Model Blending Algorithm Using Random Variables Theory by Yu Wang, Yong Cao, Yue Shen, Ruixia Zhao, Xiaoqing Zeng, Li Yao, Kan Dai

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Modeling and Optimization of Concrete Mixtures Using Machine Learning Estimators and Genetic Algorithms by Ana I. Oviedo, Jorge M. Londoño, John F. Vargas, Carolina Zuluaga, Ana Gómez

“…ML models are used to predict compressive strength, while genetic algorithms optimize the mixture cost under quality constraints. …”
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Entire aerial-aquatic trajectory modeling and optimization for trans-medium vehicles by Teng Long, Nianhui Ye, Baoshou Zhang, Jingliang Sun, Renhe Shi

“…Simultaneously, several constraints, i.e., the max impact load, trajectory height, etc., are involved in the optimization problem. Rather than directly optimizing by a heuristic algorithm, a multi-surrogate cooperative sampling-based optimization method is proposed to alleviate the computational complexity of the entire trajectory optimization problem. …”
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Reliability Optimization of Structural Deformation with Improved Support Vector Regression Model by Zheng-Zheng Zhu, Yun-Wen Feng, Cheng Lu, Cheng-Wei Fei

“…To improve the reliability optimization of turbine blades, this paper proposes a novel machine learning-based reliability optimization approach, named improved support vector regression (SR) model (ISRM) method, by fusing artificial bee colony (ABC), traditional SR model, and multipopulation genetic algorithm (MPGA). …”
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Enhancing Compressive Strength Prediction in Recycled Aggregate Concrete through Robust Hybrid Machine Learning Approaches by Samuel Keown, Dylan O’Dwyer

“…To address this issue, robust hybrid machine learning (ML) approaches are employed, particularly emphasizing the Least Square Support Vector Regression (LSSVR) model. This investigation explores the integration of LSSVR with two innovative optimizers, namely the Giant Trevally Optimizer (GTO) and the Dingo Optimization Algorithm (DOA). …”
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Leveraging stacking machine learning models and optimization for improved cyberattack detection by Neha Pramanick, Jimson Mathew, Shitharth Selvarajan, Mayank Agarwal

“…Besides, we propose an improved equilibrium optimizer (EO) approach whereby the previous EO is modified. …”
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A cloud-metaheuristic-based framework for stochastic optimization of a hybrid wind/hydrogen based-Fuel cell system in distribution network considering uncertainty by Ali S. Alghamdi

“…An improved Fire Hawks Optimization (IFHO) algorithm is utilized in solving the optimization problem by determining the optimal installation locations and sizes of HRES components. …”
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Improved Model Predictive Control Algorithm for the Path Tracking Control of Ship Autonomous Berthing by Chunyu Song, Xiaomin Guo, Jianghua Sui

“…To address the issues of path tracking accuracy and control stability in autonomous ship berthing, an improved algorithm combining nonlinear model predictive control (NMPC) and convolutional neural networks (CNNs) is proposed in this paper. …”
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Bi-objective Rolling Operation Optimization Based on Surrogate Model Acceleratiy of Community-Level Integrated Energy Systems by Xiaoman HU, Weikun TIAN, Guanyu SONG, Hao YU

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Coevolutionary Algorithm with Bayes Theorem for Constrained Multiobjective Optimization by Shaoyu Zhao, Heming Jia, Yongchao Li, Qian Shi

“…Previous studies have demonstrated that multi-swarm optimization models exhibit robust performance in CMOPs; however, their high computational resource demands can hinder convergence efficiency. …”
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