Daily reference evapotranspiration prediction in Iran: A machine learning approach with ERA5-land data by Ali Asghar Zolfaghari, Maryam Raeesi, Giuseppe Longo-Minnolo, Simona Consoli, Miles Dyck

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Predicting Running Vertical Ground Reaction Forces Using Neural Network Models Based on an IMU Sensor by Shangxiao Li, Jiahui Pan, Dongmei Wang, Shufang Yuan, Jin Yang, Weiya Hao

“…The sliding time window synchronization (STWS) algorithm was developed to sync IMU data with vGRF data. …”
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Automatic Distribution of PRVs for Leakage Reduction by Ramon Pérez, Guillem Roca, Sergi Grau

“…The manual introduction of a PRV shows its effectiveness regarding leakage reduction. An algorithm for finding the high-pressure areas and their boundary pipes is presented. …”
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Welcome to Class by Cornelia Linderoth, Carl-Johan Stenberg

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Parameter sensitivity analysis for diesel spray penetration prediction based on GA-BP neural network by Yifei Zhang, Gengxin Zhang, Dawei Wu, Qian Wang, Ebrahim Nadimi, Penghua Shi, Hongming Xu

“…Machine learning has started to be used in engine research to optimize combustion and predict fuel spray characteristics. This paper presents the development of a machine learning model using a Genetic Algorithm-Backpropagation (GA-BP) neural network to predict spray penetration. …”
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Prediction of Vehicle Interior Wind Noise Based on Shape Features Using the WOA-Xception Model by Yan Ma, Hongwei Yi, Long Ma, Yuwei Deng, Jifeng Wang, Yudong Wu, Yuming Peng

“…The key hyperparameters of the Xception model are adaptively optimized using the whale optimization algorithm to improve the prediction accuracy and generalization ability of the model. …”
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Reduction of Multiplicative Noise in Radar Images by A. A. Tuzova, V. A. Pavlov, A. A. Belov

“…The structure of speckle noise reduction filters often comprise one or more parameters to control the level of noise smoothing. …”
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Dynamic Classification: Leveraging Self-Supervised Classification to Enhance Prediction Performance by Ziyuan Zhong, Junyang Zhou

Subjects: “…Dynamic classification algorithm…”
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How can we predict transportation stock prices using artificial intelligence? Findings from experiments with Long Short-Term Memory based algorithms by Dinar Ajeng Kristiyanti, Willibrordus Bayu Nova Pramudya, Samuel Ady Sanjaya

“…It employs the Long Short-Term Memory (LSTM) algorithm, assessing different hyperparameter activation functions (linear, ReLU, sigmoid, tanh) and optimizers (ADAM, ADAGRAD, NADAM, RMSPROP, ADADELTA, SGD, ADAMAX) to refine prediction accuracy. …”
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Predicting Student Performance through Machine Learning Methods: Naive Bayesian Classifier by Chenyang Li, Qianzhi Zhou, Luming Du, Sihan Zhang

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Optimization design of an acoustic cover layer for a cylindrical cavity based on porous materials by Bohan ZHANG, Jili RONG, Xiuyan CHENG

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DO-MDS&DSCA: A New Method for Seed Vigor Detection in Hyperspectral Images Targeting Significant Information Loss and High Feature Similarity by Liangquan Jia, Jianhao He, Jinsheng Wang, Miao Huan, Guangzeng Du, Lu Gao, Yang Wang

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Traffic Flow Prediction Based on Fractional Seasonal Grey Model by SHEN Qinqin; ZHANG Zhijie; QI Xucun; YUE Xinyi

“…Based on the seasonal characteristic of urban road traffic flow data and the principle of new information, a new fractional seasonal GM(1, 1) prediction model is proposed. In the new model, a fractional cycle truncation accumulated generation operator(FCTAGO) was firstly proposed to weaken the stochastic disturbances and the seasonal characteristics of the original sequence, and then the particle swarm optimization(PSO) algorithm was adopted to find the optimal fractional order. …”
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Radial Basis Function Coupling with Metaheuristic Algorithms for Estimating the Compressive Strength and Slump of High-Performance Concrete by Amir Reza Taghavi Khangah, Erfan Khajavi, Hasti Azizi, Amir Reza Alizade Novin

Subjects: “…slump prediction…”
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Investigation of Micro-Scale Damage and Weakening Mechanisms in Rocks Induced by Microwave Radiation and Their Associated Strength Reduction Patterns: Employing Meta-Heuristic Optimization Algorithms and Extreme Gradient Boosting Models by Zhongyuan Gu, Xin Xiong, Chengye Yang, Miaocong Cao

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Customer active power consumption prediction for the next day based on historical profile by Ahmad A. Goudah, Mohamed El-Habrouk, Dieter Schramm, Yasser G. Dessouky

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Machine Learning Applications for Predicting High-Cost Claims Using Insurance Data by Esmeralda Brati, Alma Braimllari, Ardit Gjeçi

“…This study aimed to empirically evaluate the performance of classification algorithms, including Logistic Regression, Decision Tree, Random Forest, XGBoost, K-Nearest Neighbors, Support Vector Machine, and Naïve Bayes to predict high insurance claims. …”
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Denoising MEMS accelerometer sensors based on L2‐norm total variation algorithm by R. Abbasi‐Kesbi, A. Nikfarjam

“…By benefiting from the LTV algorithm, the obtained signals from the accelerometer are denoised. …”
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Predicting pregnancy loss and its determinants among reproductive-aged women using supervised machine learning algorithms in Sub-Saharan Africa by Tirualem Zeleke Yehuala, Sara Beyene Mengesha, Nebebe Demis Baykemagn

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EfficientNet-b0-Based 3D Quantification Algorithm for Rectangular Defects in Pipelines by Di Wu, Yong Hong, Jie Wang, Shaojun Wu, Zhihao Zhang, Yizhang Liu

“…Experimental results demonstrate that when compared to other algorithms, ETDN outperforms them on the identical test set, exhibiting average absolute errors of 0.1920, 0.1809, and 0.2904 for length, width, and depth, respectively.…”
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