Development and Fuel Economy Optimization of Series–Parallel Hybrid Powertrain for Van-Style VW Crafter Vehicle by Ahmed Nabil Farouk Abdelbaky, Aminu Babangida, Abdullahi Bala Kunya, Péter Tamás Szemes

“…A MATLAB (R2024b) Simulink model of the hybrid system is developed, and its speed tracking PID controller is optimized using genetic algorithm (GA) and particle swarm optimization (PSO) methods. …”
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An Improved Low-Bit-Rate Image Compression Framework Based on Semantic-Aware Model and Neighborhood Attention by Chengbin Zeng, Liang Zhang

“…In future work, we plan to improve the model’s robustness under low-light conditions and enhance compression efficiency through lightweight optimization techniques, enabling broader real-world deployment.…”
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A Data Resource Trading Price Prediction Method Based on Improved LightGBM Ensemble Model by Wan Nie, Bingliang Shen, Desheng Li

“…To address the key challenges of limited practical application, high implementation difficulty, and poor generalization capability in existing theoretical models for data resource pricing, this study employs generative adversarial network (GAN) to augment the dataset and constructs a DRV-LightGBM model based on a Bayesian parameter optimization algorithm that maximizes the coefficient of determination (<inline-formula> <tex-math notation="LaTeX">$R^{2}$ </tex-math></inline-formula>) to predict data resource transaction prices and provide post-hoc explanations for the prediction model. …”
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Predicting Ocean Current Temperature Off the East Coast of America with XGBoost and Random Forest Algorithms Using Rstudio by Lulut Alfaris, Anas Noor Firdaus, Ukta Indra Nyuswantoro, Ruben Cornelius Siagian, Aldi Cahya Muhammad, Rohana Hassan, Rodulfo T. Aunzo, Jr., Reza Ariefka

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Energy storage configuration considering user-shared costs in peak shaving auxiliary services with improved multi-objective particle swarm optimization by Yiyou Xing, Jin Shen, Xinru Li

“…Moreover, an improved particle swarm optimization algorithm, specifically adapted for this model, is developed. …”
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Optimizing high voltage gain interleaved boost converters for PV and wind systems using hybrid deep learning with bitterling fish and secretary bird algorithms by G.Veera Sankara Reddy, S. Vijayaraj

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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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Classification of biomedical lung cancer images using optimized binary bat technique by constructing oblique decision trees by Shobha Aswal, Neelu Jyothi Ahuja, Ritika Mehra

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The berth allocation problem in bulk terminals under uncertainty by Filipe Rodrigues

“…To solve the model, we use an exact decomposition algorithm (DA) in which the probability distribution information is iteratively included in the master problem through optimal dual cuts. …”
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Hybrid Disassembly Line Balancing of Multi-Factory Remanufacturing Process Considering Workers with Government Benefits by Xiaoyu Niu, Xiwang Guo, Peisheng Liu, Jiacun Wang, Shujin Qin, Liang Qi, Bin Hu, Yingjun Ji

“…Furthermore, a discrete zebra optimization algorithm is proposed to solve the model, integrating a survival-of-the-fittest strategy to improve its optimization capabilities. …”
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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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PM2.5 Concentration Prediction Based on Markov Blanke Feature Selection and Hybrid Kernel Support Vector Regression Optimized by Particle Swarm Optimization by Lian-Hua Zhang, Ze-Hong Deng, Wen-Bo Wang

“…Abstract This study employed air quality and meteorological data as research materials and extracted the optimal feature subset by using the approximate Markov blanket-based normal maximum relevance minimum redundancy (nMRMR) algorithm to serve as the input data of the prediction model. …”
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Improvement of quality of 3D printed objects by elimination of microscopic structural defects in fused deposition modeling. by Evgeniy G Gordeev, Alexey S Galushko, Valentine P Ananikov

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A Discrete Brain Storm Optimization Algorithm for Hybrid Flowshop Scheduling Problems with Batch Production at Last Stage in the Steelmaking-Refining-Continuous Casting Process by Kunkun Peng, Chunjiang Zhang, Weiming Shen, Xinfu Pang, Yanlan Mei, Xudong Deng

“…In this paper, a Discrete Brain Storm Optimization (DBSO) algorithm is proposed to handle SRCC scheduling problems. …”
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An improved Harris hawks optimizer with enhanced logarithmic spiral and dynamic factor and its application for predicting molten iron temperature in the blast furnace by Zhendong Liu, Yiming Fang, Le Liu, Shuidong Ma

“…Abstract In response to the problem of poor search performance and difficulty in escaping from the local optimum in the Harris hawks optimizer, an improved Harris hawks optimizer with enhanced logarithmic spiral and dynamic factor (IHHO‐ELSDF) is proposed in this paper. …”
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Lightweight Tea Shoot Picking Point Recognition Model Based on Improved DeepLabV3+ by HU Chengxi, TAN Lixin, WANG Wenyin, SONG Min

“…[Conclusions]This study effectively implements an efficient and accurate tea shoot recognition method through targeted model improvements and optimizations, furnishing crucial technical support for the practical application of intelligent tea picking robots. …”
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Optimization of extraction in supercritical fluids in obtaining Pouteria lucuma seed oil by response surface methodology and artificial neuronal network coupled with a genetic algo... by Alex Chauca-Cerrutti, Marianela Inga, José Luis Pasquel-Reátegui, Indira Betalleluz-Pallardel, Gustavo Puma-Isuiza

“…LS was previously characterized, and the extraction parameters were optimized using a Box-Behnken design, considering temperature (40–60°C), pressure (100–300 bar), and CO2 flow rate (3–7 mL/min), applying the response surface methodology (RSM) and neural networks with genetic algorithm (ANN+GA). …”
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Application of genetic algorithm for the set-covering problem solution by Igor S. Konovalov, Vladimir A. Fatkhi, Valery G. Kobak

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A Hybrid Deep Learning and Improved SVM Framework for Real-Time Railroad Construction Personnel Detection with Multi-Scale Feature Optimization by Jianqiu Chen, Huan Xiong, Shixuan Zhou, Xiang Wang, Benxiao Lou, Longtang Ning, Qingwei Hu, Yang Tang, Guobin Gu

“…Finally, an SVM classification algorithm is employed for personnel detection. To process small sample categories, data enhancement techniques (e.g., random flip and rotation) and K-fold cross-validation are applied to optimize the model parameters. …”
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