Damage Recovery Method for Air–Sea Cross-Domain Communication Network Based on Improved Dijkstra and Load Balancing by Zhigang Shang, Hongyu Zhang, Jing Yang

“…This paper proposes a link selection strategy based on an improved Dijkstra algorithm and load balancing on the basis of link quality prediction. …”
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Scalable data assimilation with message passing by Oscar Key, So Takao, Daniel Giles, Marc Peter Deisenroth

“…In combination with a GPU-accelerated implementation, we can scale the algorithm to very large grid sizes while retaining good accuracy and compute and memory requirements.…”
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Estimation of State of Charge for Lithium-Ion Battery Based on Finite Difference Extended Kalman Filter by Ze Cheng, Jikao Lv, Yanli Liu, Zhihao Yan

“…The results show that the model can essentially predict the dynamic voltage behavior of the lithium-ion battery, and the FDEKF algorithm can maintain good accuracy in the estimation process and has strong robustness against modeling error.…”
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Using Time Clusters for Following Users’ Shifts in Rating Practices by Dionisis Margaris, Costas Vassilakis

“…In that sense, the practice of using a single mean value for adjusting users’ ratings is inadequate, since it fails to follow such shifts in users’ rating practices, leading to decreased rating prediction accuracy. In this work, we address this issue by using the concept of dynamic averages introduced earlier and we extend earlier work by (1) introducing the concept of rating time clusters and (2) presenting a novel algorithm for calculating dynamic user averages and exploiting them in user-user collaborative, filtering implementations. …”
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Boosting Barlow Twins Reduced Order Modeling for Machine Learning‐Based Surrogate Models in Multiphase Flow Problems by T. Kadeethum, V. L. S. Silva, P. Salinas, C. C. Pain, H. Yoon

“…To address the challenge of high contrast data in multiphase flow problems due to injection wells and faults, we employ a boosting algorithm within BBT‐ROM. This algorithm sequentially trains a set of weak models (i.e., inaccurate models), improving prediction accuracy through ensemble learning. …”
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A unique, consistent identifier for alternatively spliced transcript variants. by Alberto Riva, Graziano Pesole

“…The isoform signature uniquely identifies a transcript structure, and can therefore be used as a key in databases of alternatively spliced isoforms, or to compare alternative splicing predictions produced by different methods. In this paper we present the algorithm to generate isoform signatures, we provide some examples of its application, and we describe a web-based resource to generate isoform signatures and use them in database searches.…”
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Privacy leakage in online social networks based on public information by Shao-qing LV, Yu-qing ZHANG, Ping NI

“…An algorithm was proposed to predict privacy information in social network with public information. …”
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Navigating Samarinda's climate: A comparative analysis of rainfall forecasting models by Mislan, Andrea Tri Rian Dani

“…The superior points in this research are: • Modeling rainfall data in Samarinda City using several forecasting methods: Exponential Smoothing, ARIMA, and Neural Network. • The Neural-Network algorithm used is Backpropagation with data standardization. • Information about predicted high rainfall can be used to issue early warnings of floods or landslides. …”
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Detection of capsaicin content by near-infrared spectroscopy combined with optimal wavelengths by LÜ Xiaohan, JIANG Jinlin, YANG Jing, CHEN Jianying, CEN Haiyan, FU Hongfei, ZHOU Yifei

“…Partial least square (PLS) models based on full spectra and optimal wavelengths were then developed to predict the capsaicin content, and the prediction performances and operation efficiency were compared. …”
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Closing the Open System by Nina Stener Jørgensen, Guillaume Laplante-Anfossi

“…The review of the programme questions how the probability distributions Schöffer included in the algorithm to ensure a random treatment of predictable city data was imagined to avoid stagnation, repetition and programmatic saturation, all elements essential to maintaining the tower’s open framework. …”
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Mixed Gas Detection and Temperature Compensation Based on Photoacoustic Spectroscopy by Sun Chao, Hu Runze, Liu Niansong, Ding Jianjun

“…Experimental results show that, compared to the traditional SVM algorithm, the KNN-SVM algorithm performs better in gas classification prediction, with an accuracy rate of 99.167% and an AUC indicator of 99.375%, enhancing the accuracy of gas detection. …”
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LogProb: Online Parsing Evolving Logs With Complex Parameters by Yan Li, Ziying Wang, Jiaming Mao, Zhimin Gu, Haitao Jiang

“…The extraction process includes two stages: identifying candidate templates with predicted static tokens, and using a fast matching algorithm to determine the final template. …”
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Method of Construction of pareto set At a dynamic initial data reception by S. V. Chebakov, L. V. Serebryanaya

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Dynamic VaR Measurement of Gold Market with SV-T-MN Model by Fenglan Li, Jie Wang, Liyun Su, Bao Yang

“…Secondly, future sample volatility prediction was realized by using approximate filtering algorithm. …”
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Short-term Power Load Forecasting Method of Data Center Considering PUE by WU Jin-song, ZHANG Shao feng, XU Xiang-min, LI Shu-tao, HUANG Yong, LIAO Xiao

“…Therefore, the influence of PUE is considered in the prediction model, and the adaptive moment estimation algorithm is used for deep learning. …”
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Unsteady Lifting-Line Free-Wake Aerodynamic Modeling for Morphing Wings by Gregorio Frassoldati, Riccardo Giansante, Giovanni Bernardini, Massimo Gennaretti

“…A time-stepping, lifting-line solution algorithm for the prediction of the unsteady aerodynamics of morphing wings is presented. …”
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Fractional Order Accumulation NGM (1, 1, k) Model with Optimized Background Value and Its Application by Jun Zhang, Yanping Qin, Xinyu Zhang, Bing Wang, Dongxue Su, Huaqiong Duo

“…The simulation and prediction results show the practicality and efficiency of the FBNGM (1, 1, k) model proposed in this study, which further broadens the application scope of the grey prediction model.…”
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Exhaustive search for novel multicomponent alloys with brute force and machine learning by Viktoriia Zinkovich, Vadim Sotskov, Alexander Shapeev, Evgeny Podryabinkin

“…It is particularly important for high entropy alloys (HEAs), where multiple principal elements can form numerous potential intermetallic compounds during the condensation process, making it challenging to predict the dominant phase. Our algorithm is based on a brute-force evaluation of candidate structures with a fixed underlying lattice (FCC or BCC) accelerated by machine-learning interatomic potentials. …”
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Optimization of a Coupled Neuron Model Based on Deep Reinforcement Learning and Application of the Model in Bearing Fault Diagnosis by Shan Wang, Jiaxiang Li, Xinsheng Xu, Ruiqi Wu, Yuhang Qiu, Xuwen Chen, Zijian Qiao

“…Using the SNR as the evaluation metric, the algorithm performs data screening on the replay buffer parameters before training the deep network for predicting coupled neuron model performance. …”
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Improved Ant Colony Optimization for the Operational Aircraft Maintenance Routing Problem with Cruise Speed Control by Qing Zhang, Felix T. S. Chan, Xiaowen Fu

“…The operational aircraft maintenance routing problem (OAMRP) plays a critical part in producing considerable cost reductions for airlines, since its solution directly influences the number of operating leased aircraft. …”
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