A Miniaturized and Intelligent Lensless Holographic Imaging System With Auto-Focusing and Deep Learning-Based Object Detection for Label-Free Cell Classification by Jin Chen, Wentao Han, Liangzun Fu, Zhihang Lv, Haotian Chen, Wenjing Fang, Jiale Hou, Haohan Yu, Xiwei Huang, Lingling Sun

“…Our system uses unstained cells suspended in solution as samples and employs a threshold segmentation-based auto-focusing algorithm to determine the optimal focusing distance for each imaging session. …”
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A Robust Adaptive Strategy for Diesel Particulate Filter Health Monitoring Using Soot Sensor Data by Bilal Youssef

“…Different cost functions have been tested and evaluated to improve the diagnostic performance. …”
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Solar FaultNet: Advanced Fault Detection and Classification in Solar PV Systems Using SwinProba‐GeNet and BaBa Optimizer Models by Praveen Kumar Balachandran, Muhammad Ammirrul Atiqi Mohd Zainuri, Faisal Alsaif

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A Hybrid Evolutionary Fuzzy Ensemble Approach for Accurate Software Defect Prediction by Raghunath Dey, Jayashree Piri, Biswaranjan Acharya, Pragyan Paramita Das, Vassilis C. Gerogiannis, Andreas Kanavos

“…To address this, effective feature selection is essential but remains an NP-hard challenge best tackled with heuristic algorithms. This study introduces a binary, multi-objective starfish optimizer for optimal feature selection, balancing feature reduction and classification performance. …”
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An intelligent SWMM calibration method and identification of urban runoff generation patterns by Zixin Yang, Zixin Yang, Zixin Yang, Jiahong Liu, Jiahong Liu, Jiahong Liu, Youcan Feng, Youcan Feng, Youcan Feng, Jia Wang, Jia Wang, Hao Wang, Hao Wang, Hao Wang, Changhai Li, Changhai Li, Changhai Li

“…This study proposes a universal and effective method to enhance model accuracy by optimizing parameter value ranges through an unsupervised intelligent clustering algorithm. …”
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Agricultural Machinery Movement Trajectory Recognition Method Based on Two-Stage Joint Clustering by Shuya Zhang, Hui Liu, Xiangchen Cao, Zhijun Meng

“…The silhouette coefficient method is used to determine the optimal number of clusters k for the K-Means algorithm, thus reducing the data scale. …”
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Balance Control Method for Bipedal Wheel-Legged Robots Based on Friction Feedforward Linear Quadratic Regulator by Aimin Zhang, Renyi Zhou, Tie Zhang, Jingfu Zheng, Shouyan Chen

“…A constant-speed excitation trajectory is designed to gather data for friction identification, and the Particle Swarm Optimization (PSO) algorithm is applied to determine the optimal friction parameters. …”
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APPLICATION RESEARCH OF HIGH STRENGTH STEEL TO COMMERCIAL VEHICLE FRONTAL IMPACT SAFETY DESIGN by LEI Fei, LI GuiTao, XIE XiaoPing

“…In this paper,High strength steel was applied to the frontal impact safety design of a commercial cabin with the requirement of ensuring the survival space and not increasing body weight as well as material cost. Firstly the global sensitivity analysis was carried out to choose the prominent parts,then their material were changed into HSS,the optimization was conducted by employing NAGA- Ⅱ algorithm with their thickness chosen as design variables. …”
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Real-time information-based combined control method for bus delay by Baoyu Hu, Xinlei Song, Yangyang Fu

“…The backup bus replacement strategy, on the other hand, is implemented at bus terminals, where a backup bus replaces a delayed one to maintain the schedule. A heuristic algorithm based on Particle Swarm Optimization (PSO) is incorporated into the model, enhancing its effectiveness by iteratively updating the positions and velocities of particles in the search space. …”
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Research Progress and Prospect of Multi-robot Collaborative SLAM in Complex Agricultural Scenarios by MA Nan, CAO Shanshan, BAI Tao, KONG Fantao, SUN Wei

“…Firstly, the development of enhanced data fusion algorithms will facilitate improved integration of sensor information, leading to greater accuracy and robustness of the system. …”
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Enhanced prediction of heating value of municipal solid waste using hybrid neuro-fuzzy model and decision tree-based feature importance assessment by Oluwatobi Adeleke, Obafemi O. Olatunji, Tien-Chien Jen, Iretioluwa Olawuyi

“…Moreover, understanding the relative importance and contribution of different waste properties to HHV prediction is critical for improving the model's predictive capability and optimizing the waste-to-energy (WTE) process. …”
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Operational Decision Model for Demand Response Considering Carbon Reduction Value of Adjustable Loads by Xiaoxuan ZHANG, Song XUE, Ye XU, Yi XU, Zeyu DING, Qingkai SUN

“…A genetic algorithm was used to determine the various chromosomes of the advantageous population that are conducive to achieving optimization goals. …”
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Research on early warning model of coal spontaneous combustion based on interpretability by Huimin Zhao, Xu Zhou, Jingjing Han, Yixuan Liu, Zhe Liu, Shishuo Wang

“…XGBoost, SVR, RF, LightGBM and BP models were selected as base models to establish an early warning model for CSC based on the stacking integration architecture. The grid search algorithm was utilized to optimize the model parameters, ensuring the selection of the most suitable parameter configurations. …”
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New QSPR/QSAR Models for Organic and Inorganic Compounds: Similarity and Dissimilarity by Alla P. Toropova, Andrey A. Toropov, Alessandra Roncaglioni, Emilio Benfenati

“…<b>Conclusions:</b> A comparison of different methods for the optimization of correlation weights using the Monte Carlo method showed that optimization can be improved using the coefficient of conformism of a correlative prediction (CCCP) or the index of the ideality of correlation (IIC). …”
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Dimensionless analysis and novel configuration for enhanced natural convection cooling in lithium-ion batteries by Congyu Mao, Min Liang Wang, Kewei Gao, Hongdi Jin, Woo Young Cho, Hernando Leon-Rodriguez, Kootaek Hong, Seunghwoi Han, Jihoon Jeong, Hyun Wook Kang

“…To address the increased computational cost for larger modules, a priority-based sequential optimization method was introduced. …”
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A data-driven approach utilizing machine learning (ML) and geographical information system (GIS)-based time series analysis with data augmentation for water quality assessment in M... by Abhijeet Das

“…Our research in Mahanadi River Basin, Odisha, presents an enhanced methodology based on data, specifically designed to be beneficial for Water Quality (WQ) based on Synthetic Pollution Index (SPI) and machine learning models such as Long Short-Term Memory (LSTM) and Sparrow Search Algorithm (SSA), for its analysis and interpretation of extensive, intricate data sets on water quality, as well as the allocation of pollution sources or contributing elements, in order to improve knowledge of the water quality and the planning of monitoring networks for efficient water resource management. …”
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Constrained MPC for a linear system to track time-varying reference signals by Renlong WU, Nobutaka WADA

“…A double integrator is inserted into the controller as a servo compensator, when the cost function is large, the state of the integrator can be reset at each sampling moment, thereby allowing the cost function to decrease rapidly to improve the system’s performance. …”
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Feasibility of U-Net model for cerebral arteries segmentation with low-dose computed tomography angiographic images with pre-processing methods by Seong-Hyeon Kang, Kyuseok Kim, Jina Shim, Youngjin Lee

“…For the dataset to which both the optimized NLM algorithm and semiautomatic thresholding technique were applied, the segmentation model showed the most improved performance. …”
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A hybrid deep learning-based intrusion detection system for EV and UAV charging stations by Rosebell Paul, Mercy Paul Selvan

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Research on Abstraction-Based Search Space Partitioning and Solving Satisfiability Problems by Yuexin Huang, Qinzhou Niu, Yanfang Song

“…Solving satisfiability problems is central to many areas of computer science, including artificial intelligence and optimization. Efficiently solving satisfiability problems requires exploring vast search spaces, where search space partitioning plays a key role in improving solving efficiency. …”
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