Hybrid CNN-Transformer-WOA model with XGBoost-SHAP feature selection for arrhythmia risk prediction in acute myocardial infarction patients by Li Li, Wenjun Ren, Yuying Lei, Lixia Xu, Xiaohui Ning

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Intelligent Operation and Maintenance of Wind Turbines Gearboxes via Digital Twin and Multi-Source Data Fusion by Tiantian Xu, Xuedong Zhang, Wenlei Sun, Binkai Wang

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Robust Photovoltaic Power Forecasting Model Under Complex Meteorological Conditions by Yuxiang Guo, Qiang Han, Tan Li, Huichu Fu, Meng Liang, Siwei Zhang

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Advanced machine learning techniques for predicting compressive strength and ultrasonic pulse velocity of concrete incorporating industrial by-products by Ehsan Mohsennia, Alireza Javid, Vahab Toufigh

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Improved grey wolf optimization algorithm based service function chain mapping algorithm by Yue ZHANG, Junnan ZHANG, Xiaochun WU, Chen HONG, Jingjing ZHOU

“…With the rise of new Internet applications such as the industrial Internet, the Internet of vehicles, and the metaverse, the network’s requirements for low latency, reliability, security, and certainty are facing severe challenges.In the process of virtual network deployment, when using network function virtualization technology, there were problems such as low service function chain mapping efficiency and high deployment resource overhead.The node activation cost and instantiation cost was jointly considered, an integer linear programming model with the optimization goal of minimizing the average deployment network cost was established, and an improved grey wolf optimization service function chain mapping (IMGWO-SFCM) algorithm was proposed.Three strategies: mapping scheme search based on acyclic KSP algorithm, mapping scheme coding and improvement based on reverse learning and nonlinear convergence were added to the standard grey wolf optimization algorithm to form this algorithm.The global search and local search capabilities were well balanced and the service function chain mapping scheme was quickly determined by IMGWO-SFCM.Compared with the comparison algorithm, IMGWO-SFCM reduces the average deployment network cost by 11.86% while ensuring a higher service function chain request acceptance rate.…”
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Chain hybrid feature selection algorithm based on improved Grey Wolf Optimization algorithm. by Xiaotong Bai, Yuefeng Zheng, Yang Lu, Yongtao Shi

“…In particular, the wrapper algorithm is an improved Grey Wolf Optimization (IGWO) algorithm based on random disturbance factors, while the parameters are adjusted to vary randomly to make the population variations rich in diversity. …”
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Forecasting the daily evaporation by coupling the ensemble deep learning models with meta-heuristic algorithms and data pre-processing in dryland by Tonglin Fu, Dong Wang, Jing Jin

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EEG channels selection for stroke patients rehabilitation using equilibrium optimizer by Al-Betar Mohammed Azmi, Alyasseri Zaid Abdi Alkareem, Makhadmeh Sharif Naser

“…This article addresses this problem by presenting an innovative optimization-based approach to the channel selection problem, employing a novel binary equilibrium optimizer (EO) as an optimization technique to identify the most relevant EEG channels. …”
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Bone scintigraphy based on deep learning model and modified growth optimizer by Omnia Magdy, Mohamed Abd Elaziz, Abdelghani Dahou, Ahmed A. Ewees, Ahmed Elgarayhi, Mohammed Sallah

“…In addition, the second phase is named feature selection, and it is dependent on the Arithmetic Optimization Algorithm (AOA) being used to improve the Growth Optimizer (GO). …”
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Dynamic Reactive Power Optimization Strategy for AC/DC Hybrid Power Grid Considering Different Wind Power Penetration Levels by Nan Feng, Yuyao Feng, Yun Su, Yajun Zhang, Tao Niu

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Drone-assisted adaptive object detection and privacy-preserving surveillance in smart cities using whale-optimized deep reinforcement learning techniques by Ahmed Abu-Khadrah, Ahmad Al-Qerem, Mohammad R. Hassan, Ali Mohd Ali, Muath Jarrah

“…This article proposes a novel object detection technique (ODT) that assimilates whale optimization algorithms and deep reinforcement learning. …”
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Extraction of the Optimal Parameters of Single-Diode Photovoltaic Cells Using the Earthworm Optimization Algorithm by Fatima Wardi, Mohamed Louzazni, Mohamed Hanine

“…Furthermore, the outcomes obtained via the EOA are contrasted with those derived from other algorithms, namely gray wolf optimizer (GWO), whale optimization algorithm (WOA), sine cosine algorithm (SCA), moth–flame optimization (MFO), ant lion optimizer (ALO), and multiverse optimizer (MVO). …”
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Optimization of Electrical Discharge Machining Process by Metaheuristic Algorithms by Nurezayana Zainal, Mohanavali Sithambranathan, Umar Farooq Khattak, Azlan Mohd Zain, Salama A. Mostafa, Ashanira Mat Deris

“…Several attempts have been carried out to solve the optimization problem involved in the EDM process. This paper emphasizes optimizing the EDM process using three metaheuristic algorithms: Glowworm Swarm Optimization (GSO), Grey Wolf Optimizer (GWO), and Whale Optimization Algorithm (WOA). …”
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Research of the Parameter Comprehensive Optimization of Excavator Working Device based on the Hybrid Optimization Algorithm by Zhang Xian, Liu Baixi, Qu Tao

“…The parameter of working device in the anti shovel hydraulic excavator are integrated optimized by using the hybrid algorithm of simulated annealing and penalty function. …”
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Study on the probabilistic characteristics of forces in the support structure of heliostat array based on the DBO-BP algorithm by Haiyin Luo, Qiwei Xiong, Xuewen Zhang, Shi Zuo

“…Dung beetle optimization (DBO) algorithm is a metaheuristic algorithm mimicking dung beetle ball-rolling behavior, while Back propagation (BP) neural network is a feedforward artificial neural network trained via error backpropagation to adjust parameters. …”
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An evolutionary-based optimization algorithm for truss sizing design by Pham Hoang Anh

“…Three truss sizing benchmark problems with discrete variables are used to examine the performance of the proposed algorithm. Objective functions of the optimization problems are minimum weights of the whole truss structures and constraints are stress in members and displacement at nodes. …”
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Multiplier leadership optimization algorithm (MLOA): unconstrained global optimization approach for melanoma classification by Sukanta Ghosh, Amar Singh, Shakti Kumar

“…Abstract This paper proposes the multiplier leadership optimization algorithm, which draws inspiration from multiplier leadership principles to search for and optimize solutions to complex problems effectively. …”
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Optimization of Jaw Crusher Based on Improved Genetic Algorithm by SUN Yu-fei, ZHENG Xiao-wen, CHEN Hao, LIU Xiao-Shan

“…Aiming at the deficiency of ANSYS′s own optimization algorithm, the improved genetic algorithm is applied to the structural optimization design of ANSYS.Taking the whole structure optimization of jaw crusher as an example, the optimization platform of jaw crusher based on SolidWorks and ANSYS is established.The traditional optimization algorithm of ANSYS and the improved genetic algorithm with embedded ANSYS finite element analysis are used to optimize the design.The results show that compared with the optimization algorithm of ANSYS, the improved genetic algorithm has obvious advantages in the overall structure design of jaw crusher. …”
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Optimal Placement of Phasor Measurement Unit in Electrical Grid Using Dingo Optimization Algorithm by ARIYO Funso Kehinde, AYANLADE Samson Oladayo, JIMOH Abdulrasaq, ADEBAYO Moses Taiwo

“…The study utilizes the Dingo Optimization Algorithm, a metaheuristic inspired by nature, to identify the best PMU placement. …”
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A new human-based offensive defensive optimization algorithm for solving optimization problems by Ning Fang, Cheng Xu, Xuxiong Gong, Zhouhua Wu

“…Abstract A novel human-inspired metaheuristic algorithm, termed Offensive Defensive Optimization, has been introduced to address single-objective optimization problems. …”
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