A Fusion Model for Predicting the Vibration Trends of Hydropower Units by Dong Liu, Youchun Pi, Zhengyang Tang, Hongpeng Hua, Xiaopeng Wang

“…The fusion model first employed a waveform matching extension method based on parameter ergodic optimization to extend the original signal. …”
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Improving Soil Heavy Metal Lead Inversion Through Combined Band Selection Methods: A Case Study in Gejiu City, China by Ping He, Xianfeng Cheng, Xingping Wen, Yi Cao, Yu Chen

“…To construct a preliminary Pb content prediction model, the initial selection of spectral bands utilized methods including CARS (Competitive Adaptive Reweighted Sampling), GA (Genetic Algorithm), MI (mutual information), SPA (Successive Projections Algorithm), and WOA (Whale Optimization Algorithm). …”
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Stiffness Optimization for Hybrid Electric Vehicle Powertrain Mounting System in the Context of NSGA II for Vibration Decoupling and Dynamic Reaction Minimization by Zhanpeng Fang, Qihang Li, Lei Yao, Xiaojuan Hu

“…A 6-DOF dynamic model was established to analyze the decoupling rate and frequency distribution in its inherent characteristics, calculate the dynamic reaction of the suspension system, set the decoupling rate and the dynamic reaction of the suspension as optimization objectives, and use the NSGA II (Non-dominated Sorting Genetic Algorithm II) optimization algorithm to optimize the stiffness of the suspension. …”
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Prediction of peripheral lymph node metastasis (LNM) in thyroid cancer using delta radiomics derived from enhanced CT combined with multiple machine learning algorithms by Wenzhi Wang, Feng Jin, Lina Song, Jinfang Yang, Yingjian Ye, Junjie Liu, Lei Xu, Peng An

“…Abstract Objectives This study aimed to develop a model for predicting peripheral lymph node metastasis (LNM) in thyroid cancer patients by combining enhanced CT radiomic features with machine learning algorithms. …”
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PROCESS MANAGEMENT SYSTEMS IN THE BUSINESS-ORIENTED MODEL OF ENTERPRISE DEVELOPMENT by Valentyna A. Pavlova

“…To ensure business effectiveness, an appropriate algorithm for the implementation of actions and procedures is selected based on the structuring of business processes. …”
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Optimizing Electric Cold-Chain Vehicle Scheduling for Sustainable Urban Logistics: A Novel Framework Balancing Freshness and Vehicle Charging by Zhenkun Gan, Peiwu Dong, Zhengtang Fu, Yanbing Ju, Yajun Shen

“…Subsequently, we develop a mixed-integer programming model to optimize freshness preservation. Additionally, we design a state-of-the-art algorithm based on an improved genetic algorithm to solve the scheduling model effectively. …”
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Biomimetic Computing for Efficient Spoken Language Identification by Gaurav Kumar, Saurabh Bhardwaj

“…Further, the selection of features is performed by DBO algorithm, which removes redundant features and helps to improve efficiency and accuracy. …”
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A Model Transformation Method Based on Simulink/Stateflow for Validation of UML Statechart Diagrams by Runfang Wu, Ye Du, Meihong Li

“…The experimental implementation converts operational statecharts of turnout control logic into optimized NuSMV models. Not only did the models remain intact, but the state space was also effectively reduced through the optimization of the hierarchical structure. …”
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Two-stage strategic optimal planning of distributed generators and energy storage systems considering demand response program and network reconfiguration by Saleh Ba-swaimi, Renuga Verayiah, Vigna K. Ramachandaramurthy, Ahmad K. ALAhmad, Sanjeevikumar Padmanaban

“…This work presents a stochastic two-stage mixed-integer nonlinear programming (MINLP) optimization model for the long-term planning of a distribution system (DS) to improve renewable energy integration over a ten-year period. …”
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An Optimal Energy Management Strategy With Time-Varying Equivalent Factor Based on Transformer for Multi-Mode Hybrid Electric Mining Trucks by Xinxin Zhao, Jiaqi Li, Menglei Liu, Jinggang Zhang, Nasser Lashgarian Azad

“…This paper introduces an advanced Transformer network model aimed at an adaptive Energy Management Strategy (EMS) to improve the fuel efficiency of Hybrid Electric Mining Trucks (HEMTs). …”
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Construction and scheduling optimization of renewable energy consumption forecasting system for twisted tire porcelain manufacturing industry based on deep learning by Fangrong Liao, Runlin Ran, Jiayi Zhang

“…After the algorithm is trained on GPU many times, the obtained optimal model is tested many times in the above data set, with an accuracy rate of 90.2% and a speed of 66 frames per second. …”
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Agricultural Model for Allocation of Crops Using Pollination Intelligence Method by C. N. Ejieji, A. E. Akinsunmade

“…An improved version of the Flower Pollinated Algorithm called Pollination Intelligence Algorithm using an iterative scheme to override the switch parameter in Flower Pollinated Algorithm is also presented and used in solving the designed model. …”
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Unveiling optimal SDG pathways: an innovative automated recommendation approach integrating graph pruning, intent graph, and attention mechanism by Qiang Wang, Zhihang Yu, Shu Wang, Yunqiang Zhu, Xiaoliang Dai, Zhiqiang Zou, Weiming Huang, Christophe Claramunt

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Six Sigma-Based Mathematical Optimization Framework for Flux-Switching Machines: A Roadmap for Quality, Performance, and Manufacturing Tolerances by Chiweta E. Abunike, Ogbonnaya I. Okoro, Sumeet S. Aphale

“…This study presents a Design for Six Sigma (DFSS) optimization framework that integrates sensitivity analysis, response surface modeling (RSM), and multi-objective genetic algorithms to address these challenges. …”
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Establishment of Hyperspectral Prediction Model of Water Content in Anshan-Type Magnetite by Xiaoxiao XIE, Yang BAI, Jiuling ZHANG, Yuna JIA

“…Using S-G smoothing filtering (S-G), multivariate scattering correction (MSC), standard normal transformation (SNV), second derivative (SD), reciprocal logarithm (LR) and continuum removal (CR) to preprocess the data, the spectral characteristics and their correlation with water content were analyzed. In order to further improve the prediction ability of the model, the competitive adaptive reweighting method (CARS) was used to optimize the characteristic band, and a prediction model was established by combining random forest regression (RFR), least squares support vector regression (LSSVR) and particle swarm optimization least squares support vector regression (PSO-LSSVR). …”
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A multitasking ant system for multi-depot pick-up and delivery location routing problem with time window by Haoyuan Lv, Ruochen Liu, Jianxia Li

“…Furthermore, ignoring the potential general knowledge among different schemes leads to redundant optimization. In this work, MDPDLRPTW is modeled as a multi-transformation optimization (MTFO) problem and a novel two-stage algorithm based on multitasking ant system (MTAS) is designed to solve it. …”
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Transmission Error Prediction of RV Reducer based on SSA-BP by Houzhen Sun, Hongbing Yuan, Bin Yu

“…In response to this situation， an optimized BP neural network quality prediction model based on the Sparrow Search Algorithm （SSA） is established. …”
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An Optimization Strategy for Unit Commitment in High Wind Power Penetration Power Systems Considering Demand Response and Frequency Stability Constraints by Minhui Qian, Jiachen Wang, Dejian Yang, Hongqiao Yin, Jiansheng Zhang

“…To address the issue of accommodating large-scale wind power integration into the grid, a unit commitment model for power systems based on an improved binary particle swarm optimization algorithm is proposed, considering frequency constraints and demand response (DR). …”
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A hybrid simple exponential smoothing-barnacles mating optimization approach for parameter estimation: Enhancing COVID-19 forecasting in Malaysia by Azlan Abdul Aziz, Zuriani Mustaffa, Suzilah Ismail, Nor Azriani Mohamad Nor, Nurin Qistina Mohamad Fozi

“…Therefore, this study aims to propose a new hybrid model, the Single Exponential Smoothing (SES)-Barnacles Mating Optimization (BMO) algorithm, to estimate the optimal smoothing parameter alpha and initial value that can improve the percentage of forecast accuracy. …”
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IT diagnostics of Parkinson's disease based on voice markers and decreased motor activity by U. V. Vishniakou, X. Yiwei

“…A Bayesian optimizer was also used to improve the hyperparameters of the KNN algorithm. …”
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