Conflict-based strategy combined integrated optimal conflict avoidance algorithm by Kejin Jia, Cheng Peng, Yun Du, Hongwei Wen, Yufei Gao, Zhe Zhang

“…Next, the low-level model of the traditional CBS algorithm is improved, transforming the path search process into two distinct algorithms with different focuses. …”
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Parameter identification of unmanned surface vehicle MMG model based on an improved extended Kalman filter by Pengbo SUN, Zaopeng DONG, Wei LIU, Jinliang SHENG, Zhihao LI

“…ObjectivesTo construct an accurate MMG （mathematical model group） model for a water-jet propulsion unmanned surface vehicle, the traditional extended Kalman filter algorithm and improved extended Kalman filter algorithm are combined with the real-world boat data for parameter identification. …”
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Rice disease and pest identification integrating albert pre-trained language model and improved BILSTM by Zhigui Dong, Tianyi Yang, Yanchao Wang

“…The fusion algorithm effectively improves the rice disease and pest identification accuracy and efficiency, providing strong technical support for preventing and controlling other agricultural diseases and pests.…”
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An improved deep learning approach for automated detection of multiclass eye diseases by Feudjio Ghislain, Saha Tchinda Beaudelaire, Romain Atangana, Tchiotsop Daniel

“…The overall average accuracy of the model reached 0.9621. Conclusion: The integration of biorthogonal wavelet transforms into our CNN model has proven effective, surpassing the performance of several similar algorithms reported in the literature. …”
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An Improved Phase Space Reconstruction Method-Based Hybrid Model for Chaotic Traffic Flow Prediction by Yue Hou, Da Li, Di Zhang, Zhiyuan Deng

“…The proposed PDRGA optimization algorithm is a lightweight improvement of the traditional genetic algorithm (GA) and solves the problem that the model tends to fall into a local optimum by optimizing the initial weights of CDBN. …”
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Snow Leopard Infrared Camera Image Detection Method Based on Improved EfficientDet Model by DAI Tianhong, LIU Chao

“… In view of the difficulty of snow leopard detection and recognition in infrared camera images, a snow leopard detection algorithm is proposed based on EfficientDet, which combines domain migration and new attention mechanism.Firstly, the algorithm adopts image enhancement to expand the training sample and adds non-snow leopard images to optimize the dataset structure to improve the robustness of the model. …”
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Improved sub-band JND model with textural decomposition and its application in perceptual image coding by Ming-kui ZHENG, Kai-xiong SU, Wei-xing WANG, Cheng-dong LAN, Xiu-zhi YANG

“…In order to improve the accuracy of the just noticeable difference (JND) model in transform domain, an en-hanced JND model with a new method for contrast masking factor estimation was proposed. …”
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Enhancing Speech Recognition Using Improved Particle Swarm Optimization Based Hidden Markov Model by Lokesh Selvaraj, Balakrishnan Ganesan

“…In this paper a novel speech recognition method based on vector quantization and improved particle swarm optimization (IPSO) is suggested. …”
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Improved Dab-Deformable Model for Runway Foreign Object Debris Detection in Airport Optical Images by Yang Cao, Yuming Wang, Yilin Zhu, Rui Yang

“…First, this paper introduces a Lightweight Deep-Shallow Feature Fusion algorithm (LDSFF), which integrates a hotspot sensing network and a spatial mapping enhancer aimed at focusing the model on significant regions. …”
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Research on Lightweight Model of Multi-person Pose Estimation Based on Improved YOLOv8s-Pose by FU Yu, GAO Shuhui

“…To address the issues of high computational load and slow detection speed in existing human pose estimation models, this paper proposes a lightweight improved algorithm based on the YOLOv8s-Pose model. …”
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A Study of Corrosion-Grade Recognition on Metal Surfaces Based on Improved YOLOv8 Model by Hao Chen, Ying Cao, Shengxian Cao, Heng Piao

“…Finally, based on ablation experiments and comparison experiments, performance analyses of multiple algorithmic models are conducted for horizontal and vertical comparisons in order to verify the effectiveness of the improved method and the superiority of the models in this paper. …”
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A population spatialization method based on the integration of feature selection and an improved random forest model. by Zhen Zhao, Hongmei Guo, Xueli Jiang, Ying Zhang, Changjiang Lu, Can Zhang, Zonghang He

“…Compared with MDA-RF, the prediction accuracy of the improved RF built on the same subset increased by 1.7%, indicating that improving the bootstrap sampling of random forest by using the K-means++ clustering algorithm can enhance model accuracy to some extent. …”
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An improved observer design approach for autonomous vehicles using error-based ultra-local model by Daniel Fenyes, Tamas Hegedus, Balazs Nemeth, Peter Gaspar

“…The design process combines two approaches: the Linear Parameter Varying framework and the error-based ultra-local model. The main goal of the error-based ultra-local model is to deal with the uncertainties and the nonlinearities of the model, whose effects cannot be taken into account during the modeling process. …”
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Interpretable prediction model for hand-foot-and-mouth disease incidence based on improved LSTM and XGBoost by Xiao LI, Shuyu HE, Yan PENG, Rongxin YANG, Lu TAO, Tingqi LOU, Wenqi HE

“…Based on daily HFMD incidence and meteorological monitoring data from a southern city between 2014 and 2019, comparative experiments were conducted to evaluate the performance of the proposed model in predicting HFMD incidence. The experimental results demonstrate that the ARIMA–LSTM–XGBoost model achieves a significantly improved prediction accuracy compared to other machine learning prediction models. …”
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A hybrid approach to time series forecasting: Integrating ARIMA and prophet for improved accuracy by Sherly A, Mary Subaja Christo, Jesi V Elizabeth

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Concrete Creep Prediction Based on Improved Machine Learning and Game Theory: Modeling and Analysis Methods by Wenchao Li, Houmin Li, Cai Liu, Kai Min

“…Therefore, in this study, three machine learning (ML) models, a Support Vector Machine (SVM), Random Forest (RF), and Extreme Gradient Boosting Machine (XGBoost), are constructed, and the Hybrid Snake Optimization Algorithm (HSOA) is proposed, which can reduce the risk of the ML model falling into the local optimum while improving its prediction performance. …”
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A model for shale gas well production prediction based on improved artificial neural network by LIN Hun, SUN Xinyi, SONG Xixiang, MENG Chun, XIONG Wenxin, HUANG Junhe, LIU Hongbo, LIU Cheng

“…The results indicate that the predictions from the improved network model align well with the actual production data. …”
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Identification method of canned food for production line sorting robot based on improved PSO-SVM by GAO Haiyan, GAO Jinyang, WANG Weicheng

“…By improving the particle swarm optimization algorithm to optimize support vector machine parameters, an optimized support vector machine classification model was obtained. …”
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An Intrusion Detection Model Based on Feature Selection and Improved One-Dimensional Convolutional Neural Network by Qingfeng Li, Bo Li, Linzhi Wen

“…In this paper, an intrusion detection model based on feature selection and improved one-dimensional convolutional neural network was proposed. …”
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Automatic Identification Model for Landslide Disaster Using Remote Sensing Images Based on Improved Multiresunet by Zhenyu Zhao, Shucheng Tan, Qinghua Zhang, Hui Chen

“…Furthermore, a new hybrid loss function, adaptive focal and Dice loss (AFD loss), is introduced through the adaptive AdaLoss algorithm by combining focal loss and Dice loss, improving the model’s ability to handle unbalanced samples. …”
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