Effects of Polypropylene Waste Addition as Coarse Aggregates in Concrete: Experimental Characterization and Statistical Analysis by D. C. Naveen, K. Naresh, B. S. Keerthi Gowda, Madhu Sudana Reddy G, C. Durga Prasad, Ragavanantham Shanmugam

“…The Levenberg–Marquardt algorithm was used in predicting the mechanical properties using the ANN. …”
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A Dynamic Branch-Switching Method for Parametrically Excited Systems by A.Y.T. Leung, T. Ge

“…The branch-switching algorithm in static is applied to steady state dynamic problems. …”
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Modeling the Relationship Between Radon Anomalies and Seismic Activity Using Artificial Neural Networks and Statistical Methods by Kostadin Yotov, Emil Hadzhikolev, Stanka Hadzhikoleva

“…The methodology includes wavelet transformation for noise removal, a multilayer ANN trained using the Levenberg–Marquardt algorithm, and a segmentation approach based on radial zones (annuli) for localized predictions. …”
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PRE-PROCESSING DATA ON MULTICLASS CLASSIFICATION OF ANEMIA AND IRON DEFICIENCY WITH THE XGBOOST METHOD by Fathu Nurrahman, Hari Wijayanto, Aji Hamim Wigena, Nunung Nurjanah

“…Then pre-processing data will be carried out using MissForest imputation, Boruta featuring selection, and SMOTE to help improve the performance of the classification model in predicting a particular class. After the data pre-processing process is carried out, classification modeling will be carried out using the XGBoost algorithm. …”
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Quantitative sub-ice and marine tracing of Antarctic sediment provenance (TASP v1.0) by J. W. Marschalek, E. Gasson, T. van de Flierdt, C.-D. Hillenbrand, M. J. Siegert, M. J. Siegert, L. Holder

“…These results show that the algorithm could be used to predict the provenance signature of past ice sheet configurations. …”
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Multiclass Classification of Solar Flares in Imbalanced Data Using Ensemble Learning and Sampling Methods by Haodi Jiang, Ryoma Matsuura, Jason T. L. Wang

“…They are categorized into four classes: B, C, M, and X, depending on their intensity, with X-class flares being the strongest. Being able to predict a flare’s class before its occurrence is critical for anticipating the severity of its impact on Earth. …”
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A 3D Image Reconstruction Model for Long Tunnel Geological Estimation by Yongtao Liu, Jie Qiao, Tianyuan Han, Longhui Li, Ting Xu

“…To ensure personnel safety, the geological characteristics must be predicted before tunnel face excavation. In this study, the ground-penetrating radar (GPR) technique is introduced to obtain information regarding the tunnel excavation face at a certain interval. …”
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Assessing the potential of a Bayesian ranking as an alternative to consensus meetings for decision making in research funding: A case study of Marie Skłodowska-Curie actions. by Rachel Heyard, David G Pina, Ivan Buljan, Ana Marušić

“…While we set out to understand if algorithmic approaches, with the aim of summarising individual evaluation scores, could replace consensus meetings, we concluded that currently individual scores assigned prior to the consensus meetings are not useful to predict the final funding outcomes of the proposals. …”
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A smarter approach to liquefaction risk: harnessing dynamic cone penetration test data and machine learning for safer infrastructure by Shubhendu Vikram Singh, Sufyan Ghani

“…ML models, including Support Vector Machine (SVM) optimized with Particle Swarm Optimization (PSO), Grey Wolf Optimizer (GWO), Genetic Algorithm (GA), and Firefly Algorithm (FA), were employed to predict the e/qd ratio using key geotechnical parameters, such as fine content, peak ground acceleration, reduction factor, and penetration rate. …”
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Motion and Inertia Estimation for Non-Cooperative Space Objects During Long-Term Occlusion Based on UKF-GP by Rabiul Hasan Kabir, Xiaoli Bai

“…In particular, we implement the multi-output GP to predict the projection measurements of a stereo-camera system onboard a chaser spacecraft. …”
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Calibration and uncertainty quantification for deep learning-based drought detection by Mengxue Zhang, Miguel-Ángel Fernández-Torres, Kai-Hendrik Cohrs, Gustau Camps-Valls

“…To address this shortcoming, we introduce methodologies for model calibration and entropy-based uncertainty quantification for deep learning-based drought detection. The calibration algorithm can deal with calibration errors by reducing distributional shifts and alleviating overconfident predictions. …”
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Machine learning developed immune-related exosome signature for prognosis and immunotherapy benefit in bladder cancer by Xiaoting Luo, Yi Luo

“…To investigate the performance of IES in predicting the immunotherapy benefit, three immunotherapy datasets (GSE91061, GSE78220 and IMvigor210) and several predicting scores were used. …”
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FORECASTING COHERENT VOLATILITY BREAKOUTS by A. S. Didenko, M. M. Dubovikov, B. A. Poutko

“…The paper develops an algorithm for making long-term (up to three months ahead) predictions of volatility reversals based on long memory properties of financial time series. …”
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ABC and HML-methods application for determination and optimization of stock for electrical equipment accessory parts by A. V. Beloglazov, A. G. Rusina, O. V. Fomenko, D. A. Pekhota, V. A. Fyodorova

“…To describe the use of ABC and HML-methods for predicting the volume of emergency stock for main electrical equipment accessory parts. …”
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A Few-shot Learning Method for Intent Analysis of Air Combat Confrontation Behaviors by PAN Ming, ZHENG Jingsong, LI Jinliang, FANG Long, YANG Yang, ZHAO Shijie

“…The experimental simulation results show that the accuracy of the few-shot contrastive learning algorithm based on data augmentation in predicting the behavior intention of few-shot air combat targets is 91. 13% .…”
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Load–Settlement Modeling of Micropiled Rafts in Cohesive Soils Using an Artificial Intelligence Technique by Ahmed Elsawwaf, Hany El Naggar

“…To advance the adoption of micropiles in geotechnical practice, this study employs a multi-objective genetic algorithm-based evolutionary polynomial regression (EPR-MOGA), a hybrid artificial intelligence method, to develop a robust and straightforward model for predicting the load–settlement response of micropiled rafts in cohesive soils under vertical loads. …”
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Wind Power Installed Capacity Forecast Based on a Two-Parameter Variable-Weight Buffer Operator and Subsidy Strategy Research by Ye Li, Xue Bai

“…Firstly, a new two-parameter variable-weight buffer operator is proposed to quantify the impact of the policy shock, whose optimal parameters are obtained by the genetic algorithm, and combined with the grey GM(1,1) model to predict the installed capacity of wind power in China under the cessation of subsidy policy. …”
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Analysis on waypoint-segment routing and performance evaluation for LEO satellite networks by Xin ZHAO, Guang ZHAO, Rui CHEN, Wennai WANG

“…A waypoint-segment routing (WSR) algorithm was proposed.Based on the predictable periodicity of the topological changes of satellite network, the location of satellite waypoints based on the link state of satellite nodes at the current moment was determined by WSR algorithm.The mechanism of flexible planning of packet transmission paths was responded by segment routing to changes in satellite network topology in advance, and a packet transmission path that was not affected by network topology snapshot switch was calculated.Simulation experiment was based on the NS-3, and the optimized link state routing (OLSR) algorithm and the shortest path algorithm were selected to compare with WSR in order to analyze the delay jitter and packet loss rate.It was proved that compared with OLSR, the maximum delay jitter of WSR was reduced by 46 ms and 126 ms respectively in the two scenarios, the packet loss rate was reduced by 30% and 21% respectively, and the problem of packet transmission path interruption caused by topology snapshot switching can be solved.…”
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The Sentiment Analysis Reviewing Indosat Services from Twitter Using the Naive Bayes Classifier by Febri Astiko, Achmad Khodar

“…This sentiment analysis uses machine learning to get patterns an model that can be used again to predict new data. …”
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Grasp Detection under Occlusions Using SIFT Features by Zhaojun Ye, Yi Guo, Chengguang Wang, Haohui Huang, Genke Yang

“…There are two key steps for the proposed method in the process of grasping occluded object: generating template information and grasp detection using the matching algorithm. A neural network, trained by the RGB-D data from the Cornell Grasp Dataset, predicts multiple grasp rectangles on template images. …”
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