Uncertainty prediction of wind speed based on improved multi-strategy hybrid models by Xinyi Xu, Shaojuan Ma, Cheng Huang

“…Due to insufficient traditional wind speed interval prediction methods for mining nonlinear features, in this paper, a novel interval prediction method was proposed by combining improved wavelet threshold and deep learning (BiTCN-BiGRU) with the nutcracker optimization algorithm (NOA). …”
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Weak form shallow ice approximation models with an improved time-step restriction by Igor Tominec, Josefin Ahlkrona

“…In this paper, we write the SIA model in weak form and add in the free-surface stabilization algorithm (FSSA) terms. …”
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Research on intra-day multi-objective operation control of distribution network system under quantum communication optimization by QIAN Hao, DONG Zhihui, XIANG Jundong, ZHENG Jiewen, TANG Zhipeng, GUO Qiang

Subjects: “…improved imperial competition algorithm…”
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Improving the performance of damage repair in thin-walled structures with analytical data and machine learning algorithms by Abdul Aabid, Md Abdul Raheman, Meftah Hrairi, Muneer Baig

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A hybrid model for improving customer lifetime value prediction using stacking ensemble learning algorithm by Amir Mohammad Haddadi, Hodjat Hamidi

“…These essential metrics are subsequently integrated into the dataset. In order to further improve the accuracy of the predictions, this research uses a Stacking Ensemble model that combines four algorithms, i.e., Elastic Net, Random Forest, XGBoost, and SVM. …”
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Improving brain tumor classification: An approach integrating pre-trained CNN models and machine learning algorithms by Mohamed R. Shoaib, Jun Zhao, Heba M. Emara, Ahmed S. Mubarak, Osama A. Omer, Fathi E. Abd El-Samie, Hamada Esmaiel

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The short video platform recommendation mechanism based on the improved neural network algorithm to the mainstream media by Mengruo Qi

“…This method combines natural language processing and image analysis in deep learning to construct accurate user and video models, deeply explore user interests, and improve the accuracy and effectiveness of recommendation systems for user preferences. …”
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Improved Quantum Artificial Bee Colony Algorithm-Optimized Artificial Intelligence Models for Suspended Sediment Load Predicting by Peng Wei, Wang Yu

“…To evaluate the predictive capability, the models are compared with quantum bee colony algorithm-optimized AI models (QABC-SVR and QABC-ANN), genetic algorithm-optimized AI models (GA-SVR and GA-ANN) and traditional AI models (SVR and ANN). …”
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Remaining useful life prediction of a small sample of aero-engine based on an improved gray Markov model by Dong-hai Li, Ji-liang Tu, Hui Liu, Nai-zhi Liao

“…The improved model achieves an average absolute percentage error reduction of 2.04 % compared to the original gray Markov model. …”
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RESEARCH ON DEEP NEURAL NETWORK LEARNING BASED ON IMPROVED BP ALGORITHM by HUANG Pei

“…Deep learning can make the computing model that contains a number of processing layers to learn the data that contains many levels of abstract representation.This kind of learning way in the most advanced speech recognition,visual object recognition,object detection and many other areas,such as biology,genetics and medicine brought significant improvement.Deep learning can find the complex structure of large data,and the convolution neural network as one of the important models of the depth study in the processing of voice,image,video and text,and other aspects of a new breakthrough.It is the use of BP algorithm to guide the machine how to get the error before the layer to adjust the parameters of this layer,so that these parameters are more conducive to the calculation of the model.In view of the shortcomings of traditional BP algorithm,a fast BP algorithm is proposed,which has the disadvantages of slow convergence speed and often falls into local minimum points.The improved convolutional neural network is used to validate the data set MNIST,English character recognition and medical image.The simulation results show the effectiveness of the proposed algorithm.…”
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Improved grey wolf optimization algorithm based service function chain mapping algorithm by Yue ZHANG, Junnan ZHANG, Xiaochun WU, Chen HONG, Jingjing ZHOU

“…With the rise of new Internet applications such as the industrial Internet, the Internet of vehicles, and the metaverse, the network’s requirements for low latency, reliability, security, and certainty are facing severe challenges.In the process of virtual network deployment, when using network function virtualization technology, there were problems such as low service function chain mapping efficiency and high deployment resource overhead.The node activation cost and instantiation cost was jointly considered, an integer linear programming model with the optimization goal of minimizing the average deployment network cost was established, and an improved grey wolf optimization service function chain mapping (IMGWO-SFCM) algorithm was proposed.Three strategies: mapping scheme search based on acyclic KSP algorithm, mapping scheme coding and improvement based on reverse learning and nonlinear convergence were added to the standard grey wolf optimization algorithm to form this algorithm.The global search and local search capabilities were well balanced and the service function chain mapping scheme was quickly determined by IMGWO-SFCM.Compared with the comparison algorithm, IMGWO-SFCM reduces the average deployment network cost by 11.86% while ensuring a higher service function chain request acceptance rate.…”
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Chain hybrid feature selection algorithm based on improved Grey Wolf Optimization algorithm. by Xiaotong Bai, Yuefeng Zheng, Yang Lu, Yongtao Shi

“…It also shows that the algorithm improves the generalization ability and performance of the model.…”
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A new mathematical model to improve encryption process based on Split-Radix Fast Fourier Transform algorithm by Abdulle Hassan Mohamud

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Cloud-based Optimized Intelligent Substation Secondary System Rapid Test Model and System Design by Rongrong JI, Mengzhi WANG, Guowei ZHOU, Qingyao LIU, Hai LI, Ruofan HUANG

“…The operations of switching the applied quantity, throwing and closing the soft and hard plates and starting and stopping the terminal are further considered, and a fast testing mathematical model aiming at the shortest time is proposed. The test sequence is optimized based on the improved whale optimization algorithm (SWOA). …”
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Improving Cell Detection and Tracking in Microscopy Images Using YOLO and an Enhanced DeepSORT Algorithm by Mokhaled N. A. Al-Hamadani, Richard Poroszlay, Gabor Szeman-Nagy, Andras Hajdu, Stathis Hadjidemetriou, Luca Ferrarini, Balazs Harangi

“…This combination ensures continuous detection and compensates for missed detections, thereby improving overall recall. Our approach achieves a recall of 93.21% with the enhanced DeepSORT algorithm, compared to the 53.47% recall obtained by the original YOLOv8x model. …”
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Passenger Flow Prediction for Rail Transit Stations Based on an Improved SSA-LSTM Model by Xing Zhao, Chenxi Li, Xueting Zou, Xiwang Du, Ahmed Ismail

“…According to the experimental results, the proposed SSA-LSTM model has a more effective performance than the Support Vector Regression (SVR) method, the eXtreme Gradient Boosting (XGBoost) model, the traditional LSTM model, and the improved LSTM model with the Whale Optimization Algorithm (WOA-LSTM) in the passenger flow prediction. …”
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A New Stochastic Model to Improve Positioning Accuracy of the Recursive Least Squares Method by Nerjes Rahemi, Kurosh Zarrinnegar, Mohammad Reza Mosavi

“…To evaluate the complexity of the proposed models, we employed an ARM STM32H743 processor. The findings indicate a modest increase in the proposed model complexity compared to earlier models, along with a substantial improvement in positioning accuracy.…”
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Machine learning models and dimensionality reduction for improving the Android malware detection by Pablo Morán, Antonio Robles-Gómez, Andres Duque, Llanos Tobarra, Rafael Pastor-Vargas

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Ripe Tomato Detection Algorithm Based on Improved YOLOv9 by Yan Wang, Qianjie Rong, Chunhua Hu

“…After collecting tomato data, we used Mosaic for data augmentation, which improved model robustness and enriched experimental data. …”
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Fault Diagnosis of Power Equipment Based on Improved SVM Algorithm by Youle Song, Yuting Duan, Tong Rao

“…Therefore, this study proposes an improved support vector machine model, combined with grey wolf optimization algorithm, aimed at improving the accuracy and efficiency of power equipment fault diagnosis. …”
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