The Adaptive-Clustering and Error-Correction Method for Forecasting Cyanobacteria Blooms in Lakes and Reservoirs by Xiao-zhe Bai, Hui-yan Zhang, Xiao-yi Wang, Li Wang, Ji-ping Xu, Jia-bin Yu

“…Globally, cyanobacteria blooms frequently occur, and effective prediction of cyanobacteria blooms in lakes and reservoirs could constitute an essential proactive strategy for water-resource protection. …”
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Fog Study at Ardabil Airport for the Statistical Period From 2011 to 2020 by Razieh Pahlavan, Mohammad Moradi, Sahar Tajbakhsh, Majid Azadi, Mehdi Rahnama

“…Climatology of fog can help better diagnosis and prediction of fog. In this study, METAR data from 2011 to 2020 were used to detect fog events at Ardebil Airport and according to the classification algorithm of Tardif and Rasmussen (2007), the types of events were determined. …”
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Ray-Tracing method for fields of view simulation in agricultural and forestry vehicles by Lorenzo Landi, Luca Burattini, Maurizio Cutini, Leonardo Vita, Luca Landi

“…In this paper, a virtual prediction method of the field of view for a tractor is analyzed using a rendering based on the Ray-Tracing algorithm. …”
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Assimilating Summer Sea‐Ice Thickness Observations Improves Arctic Sea‐Ice Forecast by Ruizhe Song, Longjiang Mu, Svetlana N. Loza, Frank Kauker, Xianyao Chen

“…The long‐term Arctic‐wide SIT prediction is also improved. In spite of remaining uncertainties, summer CryoSat‐2 SIT observations have the potential to improve Arctic sea‐ice forecast on multiple time scales.…”
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基于多重分形谱的转子系统故障诊断与参数优选 by 刘岩, 王金东, 郭建华, 胡清明

“…Because of the robustness of one dimensional time series reconstruction G-P algorithm to extract the fault omen is poor,especially influenced by a sensitive noise in the measured signal.A noise reduction method is proposed based on detrended fluctuat ion analysis（FDA） and kernel principal component analysis（KPCA）,the eigenvalue extraction algorithm based on Mult ifractal spectrum is presented.Through pseudo-phase portrait to determine the weighting factor threshold,optimize and choose parameter and compare with the defects of single G_P algorithm,and combine with the 3 kinds of rotor system common faults,the stability and accuracy of eigenvalue extraction of this method is analyzed,the results prove that,the diagnosis result is good.…”
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基于正态反高斯模型的自适应小波消噪方法 by 吴国洋

“…A locally adaptive wavelet de-noising method based on normal inverse Gaussian modal is proposed.Firstly,the db5 wavelet is used to decompose the signal.For those wavelet coefficients which contain a lot of noise,the normal inverse Gaussian modal with good approximation property is constructed as the prior distribution model of those coefficients,on the basis of the model,Bayesian maximum a posteriori estimator is used to estimate the noisy wavelet coefficients and got the realistic wavelet coefficients.Then in the process of posteriori estimation,in order to get the best posteriori approximation model,the particle swarm optimization algorithm is used to select the key coefficient of the model.Finally,new wavelet coefficients are used for the reconstruction of the de-noised signal,and the de-noised signal is gotten.The algorithm is analyzed by simulation and bearing fault signal respectively.Analysis results show that this algorithm has good noise reduction effect,and can efficiently reduce the noise.…”
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Deep-Learning-Based Approach in Imaging Radiometry by Aperture Synthesis: Application to Real SMOS Data by Ali Khazaal, Richard Faucheron, Nemesio J. Rodriguez-Fernandez, Eric Anterrieu

“…A novel image reconstruction algorithm for aperture synthesis measurements using deep learning techniques was introduced recently. …”
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Fluid flow characteristics estimation of a new integrated bifluid/airbased photovoltaic thermal system utilizing a hybrid optimization method by Ghassan A. Bilal, Abdullateef A. Jadallah, Omayma M. Abdulmajeed, Müslüm Arıcı

“…Furthermore, combining two techniques gives the best predictions compared to actual data. The results of the comparison showed a satisfactory correspondence between the predicted and the experimental data. …”
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Nanodesigner: resolving the complex-CDR interdependency with iterative refinement by Melissa Maria Rios Zertuche, Şenay Kafkas, Dominik Renn, Magnus Rueping, Robert Hoehndorf

“…NanoDesigner integrates key stages—structure prediction, docking, CDR generation, and side-chain packing—into an iterative framework based on an expectation maximization (EM) algorithm. …”
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Deep Learning-Based Signal Constellation for OFDM Underwater Acoustic Communications by Ammar E. Abdelkareem, Majid Dherar Younus, Emad A. Al-Sabawi

“…The hegemony was depicted in the performance of the bit error rate (BER) of the proposed DL-based signal constellation prediction algorithm, which achieved 100% accuracy and a gain of 10dB and 12dB over minimum mean square error (MMSE) and least square (LS) channel estimation performance, respectively, when CP=0 at N_p=N/4. …”
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Elucidating Early Radiation-Induced Cardiotoxicity Markers in Preclinical Genetic Models Through Advanced Machine Learning and Cardiac MRI by Dayeong An, El-Sayed Ibrahim

“…Despite normal global left ventricular ejection fraction in both groups, strain analysis showed significant reductions in the anteroseptal and anterolateral segments of irradiated rats. …”
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Online Meta-Recommendation of CUSUM Hyperparameters for Enhanced Drift Detection by Jessica Fernandes Lopes, Sylvio Barbon Junior, Leonimer Flávio de Melo

“…With the increasing demand for time-series analysis, driven by the proliferation of IoT devices and real-time data-driven systems, detecting change points in time series has become critical for accurate short-term prediction. The variability in patterns necessitates frequent analysis to sustain high performance by acquiring the hyperparameter. …”
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TARNet: An Efficient and Lightweight Trajectory-Based Air-Writing Recognition Model Using a CNN and LSTM Network by Md. Shahinur Alam, Ki-Chul Kwon, Shariar Md Imtiaz, Md Biddut Hossain, Bong-Gyun Kang, Nam Kim

“…LSTM is good for time series prediction yet time-consuming; on the other hand, CNN is superior in feature generation but comparatively faster. …”
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Modelling maintenance scheduling strategies for highway networks. by Bao Tong, Jianwei Wang, Xue Wang, Feihao Zhou, Xinhua Mao, Yaxin Duan

“…A simulated annealing algorithm and augmented Lagrange algorithm are employed to solve the two proposed models, respectively. …”
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Computer Course Design Plan for Film and Television Media Major by Shan Hui, Xiao Zhang, Tian Yang

“…In view of the excellent global optimization ability of GA and the defects of the BP algorithm itself, this work adopts the improved GA algorithm to optimize the BP network, and establishes an IGA-BP network combination model with higher prediction accuracy. …”
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Dynamic scheduling strategies for cloud-based load balancing in parallel and distributed systems by Nasser S. Albalawi

“…The Least Response Time (LRT) technique for the Load Monitoring procedures will be developed once the job scheduling is complete. The Harmony Search Algorithm with Linear Regression (LR-HSA) is then used to do Distributed Computing-based Load Prediction and Adjustment. …”
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Cyclical hybrid imputation technique for missing values in data sets by Kurban Kotan, Serdar Kırışoğlu

“…Because incorrect imputation of missing data increases the error in the modeling phase and reduces the prediction performance of the model. When it comes to health, it is inevitable to choose models that show a higher success rate. …”
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Modeling the cooling effect of urban green infrastructures with an ecosystem services approach ( case study: Tehran metropolis) by S. Malekzadeh, H.R. Jafari, R. Nazari, T. Blaschke, A. Hof, M. Karimi

“…An additional reduction of 66 hectares is predicted over the next decade. …”
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The Method of Elimination of Vibrations and Forces Excited by Unbalanced Rotary Machines with Inaccesible Rotor by J. Michalczyk, G. Cieplok

“… Possibilities of application of the method of synchronous elimination to the reduction of vibrations and forces in unbalanced rotary machines with inaccessible axes were considered in this paper. …”
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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

“…Multiscale features are then extracted with Inception v3 and combined with principal component analysis (PCA) for dimensionality reduction. Finally, an SVM classification algorithm is employed for personnel detection. …”
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