Validation and Optimization of Suspension Design for Testing Platform Vehicle by Luhang Li, Lin Xu, Hao Cui, Mohamed A. A. Abdelkareem, Zihao Liu, Jingyu Chen

“…The nondominated sorting genetic algorithm (NSGA-II) is used to optimize the damping, stiffness, and installation position of the suspension system. …”
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Developing a Machine Learning Model for Predicting 30-Day Major Adverse Cardiac and Cerebrovascular Events in Patients Undergoing Noncardiac Surgery: Retrospective Study by Ju-Seung Kwun, Houng-Beom Ahn, Si-Hyuck Kang, Sooyoung Yoo, Seok Kim, Wongeun Song, Junho Hyun, Ji Seon Oh, Gakyoung Baek, Jung-Won Suh

“…ObjectiveThis study aimed to use the Observational Medical Outcomes Partnership Common Data Model to develop a predictive model by applying machine learning algorithms that can effectively predict major adverse cardiac and cerebrovascular events (MACCE) in patients undergoing noncardiac surgery. …”
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Task-dependent Optimal Weight Combinations for Static Embeddings by Nathaniel Robinson, Nathaniel Carlson, David Mortensen, Elizabeth Vargas, Thomas Fackrell, Nancy Fulda

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Dynamic Emergency Vehicle Path Planning and Traffic Evacuation Based on Salp Swarm Algorithm by X. H. Duan, J. X. Wu, Y. L. Xiong

“…In view of the rescue delay due to traffic congestion in the urban road network, this paper implemented real-time traffic control with congestion index constraints in emergency vehicle dispatching and proposed a two-stage optimization model and algorithm. In the first stage, salp swarm algorithm (SSA) was combined with Dijkstra algorithm, and a novel hybrid algorithm with new updating rules was designed to get the multiple alternative paths. …”
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Hybrid Estimation of Distribution Algorithm for Solving Three-Stage Multiobjective Integrated Scheduling Problem by Chao Deng, Rong Hu, Bin Qian, Huai P. Jin

“…Aiming at reducing the total energy consumption of three stages processing-transportation-assembly in the assembly manufacturing industry, a three-stage multiobjective integrated scheduling problem with job batch transportation considering the energy consumption (3sMISP_JBTEC) is proposed, and a comprehensive energy consumption model of multistage of 3sMISP_JBTEC with an improved turn off/on strategy in the processing stage and considering speed in the transportation stage is formulated. …”
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Hybrid AE and Bi-LSTM-Aided Sparse Multipath Channel Estimation in OFDM Systems by Vijayakumar Kondepogu, Budhaditya Bhattacharyya

“…Further, an efficient Grasshopper Electric Fish Optimization Algorithm (G-EFOA) is developed to optimize the parameters of AE and Bi-LSTM, resulting in superior solutions. …”
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PDCSA: A parallel discrete crow search algorithm for influence maximization in social networks. by Lihong Han, Kan Yang, Yang Ming, Jianxin Tang

“…In recent years, swarm intelligence-based optimization algorithms have seen increasing application in addressing this problem, with notable improvements in performance. …”
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OPTIMIZATION OF HEMISPHERICAL RESONATOR GYROSCOPE STANDING WAVE PARAMETERS by O. S. Khalyutina

“…With increasing requirements to accuracy of definition NFP improved the sensors of the primary navigation information: gyroscopes and accelerometers. the gyroscopes of a new type, the so-called solid-state wave gyroscopes (SSVG) are currently developed and put into practice. …”
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Optimization of PID Controllers Using Groupers and Moray Eels Optimization with Dual-Stream Multi-Dependency Graph Neural Networks for Enhanced Dynamic Performance by Vaishali H. Kamble, Manisha Dale, R. B. Dhumale, Aziz Nanthaamornphong

“…This study presents a novel control strategy that integrates the Groupers and Moray Eels Optimization (GMEO) algorithm with a Dual-Stream Multi-Dependency Graph Neural Network (DMGNN) to optimize PID controller parameters. …”
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Implementation of Apriori Algorithm in Identifying Purchase Relationships at Bluder Cokro Pakuwon Mall by Angeline Ivana, Indra Maryati

“…This study aims to identify consumer purchasing patterns at the store to enhance promotional strategies and optimize product placement. The research applies the Cross Industry Standard Process for Data Mining (CRISP-DM) methodology, which includes phases such as business understanding, data understanding, data preparation, modeling, evaluation, and deployment. …”
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Dynamic Aerial Small Target Detection Algorithm Based on Compound Zoom Scaling by Jiang Yuan, Zhu Gaofeng, Zhu Fenghua, Xiong Gang

“…Experiments conducted on the VisDrone2019 UAV aerial ima-gery dataset demonstrate that the proposed algorithm improves mAP by 2.1%, reduces FLOPs by 32.5%, and decreases computational complexity, resulting in superior detection performance.…”
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Genetic Artificial Hummingbird Algorithm-Support Vector Machine for Timely Power Theft Detection by Emmanuel Gbafore, Davies Rene Segera, Cosmas Raymond Mutugi Kiruki

“…Utilities face serious obstacles from power theft, which calls for creative ways to maintain income and improve operational effectiveness. This study presents a novel hybrid genetic artificial hummingbird algorithm-support vector machine classifier to detect power theft. …”
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Cellular-free RAN slicing resource allocation algorithm based on multi-timescale collaboration by XIA Weiwei, WANG Boye, XIA Yaxing, MIAO Weiwei, WANG Dayang, JING Dongsheng, YAN Feng, SHEN Lianfeng

“…To address the issue of ensuring user quality of service in resource allocation for 6G cell-free radio access network slicing under dynamic service variations, a resource allocation algorithm based on multi-timescale collaborative optimization was proposed. …”
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Power allocation algorithm for cognitive radio energy harvesting networks based on energy cooperation by Zhen-wei XIE, Qi ZHU

“…An algorithm to optimize the power allocation by maximizing the system throughput in cognitive radio energy harvesting networks was proposed.The algorithm formulated the throughput optimization model subject to the causality constraints of the harvested energy within the two secondary users and the interference constraint of the primary user.In addition,by applying the variable-substitution method and problem equivalence transformation,the joint optimization problem of power and cooperative energy was decoupled into two problems:a power allocation problem and a cooperative energy one.The former problem could be solved by iterating the two decoupled problems.As shown in the simulation results,the energy cooperation can significantly improve the system throughput when the harvested energy difference between two nodes is rather large.…”
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A multi objective collaborative reinforcement learning algorithm for flexible job shop scheduling by Jian Li, Shifa Li, Pengbo He, Huankun Li

“…Abstract To improve the scheduling efficiency of flexible job shops, this paper proposes a multi-objective collaborative intelligent agent reinforcement learning algorithm based on weight distribution. …”
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Stiffness Regulation of Cable-Driven Redundant Manipulators Through Combined Optimization of Configuration and Cable Tension by Zhuo Liang, Pengkun Quan, Shichun Di

“…This paper proposes a dual-level stiffness regulation strategy that combines configuration and cable tension optimization. Motion-level and tension-level factors are introduced as control variables into the respective optimization models, enabling effective manipulation of configuration and tension solutions for stiffness regulation. …”
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Network media streaming offloading algorithm based on QoE in mobile edge network by Zaijian WANG, Hao CHENG

“…Aiming at the problems of high-latency, high energy consumption, high bandwidth, and poor quality of experience (QoE) caused by emerging network media streaming business in mobile edge computing, a computing offloading algorithm based on QoE feedback configuration was proposed.Firstly, both preprocessing and priority were comprehensively considered to maximize network resource utilization.Meanwhile, different weights were assigned to the computation tasks for establishing a resource allocation relationship.Secondly, after comprehensively taking into account deadline, computing resource, power and bandwidth constraint, an QoE model was established where the optimization objective was the weighted sum of task delay, energy consumption and precision, and the method of Lagrange multipliers was utilized to solve the established model.Simulation results indicate that, compared with the deep reinforcement learning-based online offloading algorithm, the proposed algorithm can effectively optimize the resource allocation and better improve the QoE.…”
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Finite-Time Control for Satellite Formation Reconfiguration and Maintenance in LEO: A Nonlinear Lyapunov-Based SDDRE Approach by Majid Bakhtiari, Amirhossein Panahyazdan, Ehsan Abbasali

“…This optimization process minimizes energy usage through a hybrid genetic algorithm and simulated annealing (HGASA), resulting in improved performance. …”
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Network media streaming offloading algorithm based on QoE in mobile edge network by Zaijian WANG, Hao CHENG

“…Aiming at the problems of high-latency, high energy consumption, high bandwidth, and poor quality of experience (QoE) caused by emerging network media streaming business in mobile edge computing, a computing offloading algorithm based on QoE feedback configuration was proposed.Firstly, both preprocessing and priority were comprehensively considered to maximize network resource utilization.Meanwhile, different weights were assigned to the computation tasks for establishing a resource allocation relationship.Secondly, after comprehensively taking into account deadline, computing resource, power and bandwidth constraint, an QoE model was established where the optimization objective was the weighted sum of task delay, energy consumption and precision, and the method of Lagrange multipliers was utilized to solve the established model.Simulation results indicate that, compared with the deep reinforcement learning-based online offloading algorithm, the proposed algorithm can effectively optimize the resource allocation and better improve the QoE.…”
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A novel economic load dispatch method of microgrid based on hybrid slime mould and genetic algorithm by Wei Ba, Wei Sun, Chunjiang Zhao, Qi Li

“…For performance evaluation, GSMA is compared with slime mould algorithm (SMA), grey wolf optimizer (GWO), sparrow search algorithm (SSA), Harris Hawks optimization (HHO), whale optimization algorithm (WOA) and particle swarm optimization (PSO) using standard optimization functions. …”
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