A Servo Control Algorithm Based on an Explicit Model Predictive Control and Extended State Observer with a Differential Compensator by Zhuobo Dong, Shuai Chen, Zheng Sun, Benyi Tang, Wenjun Wang

“…This paper introduces a novel two-degree-of-freedom (2-DOF) control algorithm that integrates explicit model predictive control (EMPC) with a differential-compensated extended state observer (DCESO). …”
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Rendering algorithm for 3D model of goods in power warehouse based on linear interpolation and 2D texture mapping by Gui Luo, Xin Chen, Quan Liu, Anlin Liu, Xuan Zhang, Li Tian, Yueshi Gao

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Prediction of Water Quality in Agricultural Watersheds Based on VMD-GA-LSTM Model by Yuxuan Luo, Xianglan Meng, Yutong Zhai, Dongqing Zhang, Kaiping Ma

“…The VMD-GA-LSTM model utilizes the variational mode decomposition technique to decompose the time series data into multiple intrinsic mode functions and then uses the optimized LSTM network to predict each component to improve the accuracy of water quality prediction. …”
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Optimization of regional coverage satellite constellations based on ant colony algorithm by WEI Jiao-long, CEN Zhao-hui

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Machine learning algorithms for diabetic kidney disease risk predictive model of Chinese patients with type 2 diabetes mellitus by Lu-Xi Zou, Xue Wang, Zhi-Li Hou, Ling Sun, Jiang-Tao Lu

“…Among the seven forecasting models constructed by MLAs, the accuracy of the Light Gradient Boosting Machine (LightGBM) model was the highest, indicated that the LightGBM algorithms might perform the best for predicting 3-year risk of DKD onset.Conclusions Our study could provide powerful tools for early DKD risk prediction, which might help optimize intervention strategies and improve the renal prognosis in T2DM patients.…”
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Genetic programming-based algorithms application in modeling the compressive strength of steel fiber-reinforced concrete exposed to elevated temperatures by Mohsin Ali, Li Chen, Qadir Bux Alias Imran Latif Qureshi, Deema Mohammed Alsekait, Adil Khan, Kiran Arif, Muhammad Luqman, Diaa Salama Abd Elminaam, Amir Hamza, Majid Khan

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Robust Adaptive Path Tracking Control Scheme for Safe Autonomous Driving via Predicted Interval Algorithm by Cong Phat Vo, Jungeun Lee, Jeong Hwan Jeon

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A novel attention based vision transformer optimized with hybrid optimization algorithm for turmeric leaf disease detection by R. Selvaraj, M. S. Geetha Devasena

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Comparative analysis of machine learning models for the detection of fraudulent banking transactions by Pedro María Preciado Martínez, Ricardo Francisco Reier Forradellas, Luis Miguel Garay Gallastegui, Sergio Luis Náñez Alonso

“…The aim is to evaluate and determine the most effective model for identifying suspicious transactions, overcoming the challenge of a highly imbalanced dataset. …”
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An Application of Quasi Newton Algorithm and Improvement of Sliding Surface for Robot Control by Chi-Ngon Nguyen, Thanh Tung Pham

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FATIGUE CRACK GROWTH PREDICTION BASED ON IPSO-PF ALGORITHM by JIN Ting, WANG Xiaolei, LIU Yu, YUAN Jianming

“…The traditional Paris formula ignores the influence of various uncertain factors in the crack growth process, which leads to a big difference between the predicted crack growth process and the real crack growth process. In order to improve the prediction accuracy of fatigue crack growth, a fatigue crack growth prediction method based on the improved particle swarm optimization particle filtering (IPSO-PF) algorithm was proposed. …”
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The electromagnetic transient simulation acceleration algorithm based on delay mitigation of dynamic critical paths by Qi Guo, Yuanhong Lu, Jie Zhang, Jingyue Zhang, Libin Huang, Haiping Guo, Tianyu Guo, Liang Tu

“…We first validate the theoretical feasibility of the algorithm using a theoretical case study and illustrate the algorithmic effectiveness using two real case studies, direct current (DC) model and alternating current (AC) model respectively. …”
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A novel trajectory learning method for robotic arms based on Gaussian Mixture Model and k-value selection algorithm. by Jingnan Yan, Yue Wu, Kexin Ji, Cheng Cheng, Yili Zheng

“…Next, k-means clustering is applied with the optimal k-value to initialize the parameters of the Gaussian Mixture Model, which are then refined and trained through the Expectation-Maximization algorithm. …”
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A metaheuristic approach to model the effect of temperature on urban electricity need utilizing XGBoost and modified boxing match algorithm by Nihuan Liao, Zhihong Hu, Davud Magami

“…The XGBoost model’s hyperparameters are optimized using MBM to achieve the best possible solution. …”
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Dynamic Error Modeling and Predictive Compensation for Direct-Drive Turntables Based on CEEMDAN-TPE-LightGBM-APC Algorithm by Manzhi Yang, Hao Ren, Shijia Liu, Bin Feng, Juan Wei, Hongyu Ge, Bin Zhang

“…Our methodology comprises four key stages: Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN)-based decomposition of historical error data, development of component-specific prediction models using Tree-structured Parzen Estimator (TPE)-optimized Light Gradient Boosting Machine (LightGBM) algorithms for each Intrinsic Mode Function (IMF), integration of component predictions to generate initial values, and application of the Adaptive Prediction Correction (APC) module to produce final predictions. …”
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Distributionally Robust Variational Quantum Algorithms With Shifted Noise by Zichang He, Bo Peng, Yuri Alexeev, Zheng Zhang

“…Given their potential to demonstrate near-term quantum advantage, variational quantum algorithms (VQAs) have been extensively studied. Although numerous techniques have been developed for VQA parameter optimization, it remains a significant challenge. …”
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Gradient-Enhanced Kriging-Based Parallel Efficient Global Optimization Algorithm and Its Application in Aerodynamic Shape Optimization by Hang Fu, Qingyu Wang, Takuji Nakashima, Asahi Kawasaki, Chenguang Lai, Keigo Shimizu, Rahul Bale, Makoto Tsubokura

“…To further enhance the optimization potential of the parallel EGO algorithm, an improved system that integrates the parallel EGO algorithm with gradient-enhanced kriging (GEK) is proposed. …”
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Provide a method to diagnose and optimize diabetes using data mining methods and firefly algorithm by Reza Molaee Fard

“…In this research, the DBSCAN clustering algorithm is used to cluster the data. Then, using SVM, we classify the data to identify useful data, and finally, with the firefly algorithm, we increase the obtained data to increase we optimize performance with this algorithm. …”
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Genetic Algorithm for Optimal Control Design to Gust Response for Elastic Aircraft by Mauro Iavarone, Umberto Papa, Alberto Chiesa, Luca de Pasquale, Angelo Lerro

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Optimizing Renewable Energy Integration Using IoT and Machine Learning Algorithms by Orken Mamyrbayev, Ainur Akhmediyarova, Dina Oralbekova, Janna Alimkulova, Zhibek Alibiyeva

“…The study also implemented a reinforcement learning-based grid optimization system. Results showed significant improvements in forecasting accuracy, with the LSTM model achieving a 59.1% reduction in Mean Absolute Percentage Error compared to the persistence model. …”
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