Risk Assessment of High-Voltage Power Grid Under Typhoon Disaster Based on Model-Driven and Data-Driven Methods by Xiao Zhou, Jiang Li

“…Additionally, a power grid failure risk assessment model is built based on Light Gradient Boosting Machine (LightGBM), and the Borderline-Smoothing Algorithm (BSA) is used for the modeling of power grid faults. …”
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From Tables to Computer Vision: Transforming HPDC Process Data into Images for CNN-Based Deep Learning by A. Burzyńska

“…The approach assists in predicting key values of the dependent variable associated with defect occurrence, enabling foundries to enhance product quality, reduce waste, and augment overall production process efficiency. …”
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Bias-aware degradation models for reinforced concrete bridges based on XAI by Francesca Marsili, Filippo Landi, Rade Hajdin, Sylvia Kessler

“…The analysis comprises four steps: (1) cluster analysis of damage transition times using the k-means algorithm to identify damage patterns with similar damage evolution rates (fast, normal, slow, corresponding to bridge components with a fragile, normal, and robust deterioration behavior); (2) Random Forest classification to predict the cluster based on bridge inventory data; (3) SHAP analysis to explain the predictions of the Random Forest classifier; (4) application of the gamma process to the grouped damage transition times to assess damage evolution. …”
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Crack Detection Method of Sleeper Based on Cascade Convolutional Neural Network by Liming Li, Shubin Zheng, Chenxi Wang, Shuguang Zhao, Xiaodong Chai, Lele Peng, Qianqian Tong, Ji Wang

“…The sleeper is inputted into CEDNet for crack feature extraction to predict the coarse crack saliency map. The prediction graph is inputted into CRRNet to improve its edge information and local region to achieve optimization. …”
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Structure, short-range order, and phase stability of the Al x CrFeCoNi high-entropy alloy: insights from a perturbative, DFT-based analysis by Christopher D. Woodgate, George A. Marchant, Livia B. Pártay, Julie B. Staunton

“…When the underlying lattice is fcc, at low concentrations of Al, depending on the value of x, we predict either an L12 or D022 ordering emerging below approximately 1000 K. …”
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Preliminary Research on Intelligent Baking Room Dehydration and Drying Technology for Rice Sterile Seeds by Man Luo

“…An adaptive integral sliding mode control algorithm based on Smith prediction was proposed for intelligent baking room temperature. …”
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Travel route recommendation with a trajectory learning model by Xiangping Wu, Zheng Zhang, Wangjun Wan

“…Then, it integrates this information through neural networks to predict the next intersection. Finally, a beam search algorithm is applied to generate and recommend multiple candidate routes. …”
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Processivity and coupling in messenger RNA transcription. by Stuart Aitken, Marie-Cécile Robert, Ross D Alexander, Igor Goryanin, Edouard Bertrand, Jean D Beggs

“…We demonstrate that these alternatives have a significant impact on the predicted distributions. Models are simulated by the Gillespie algorithm, and the third and fourth moments of the resulting distribution are computed in order to characterise the length of the tail, and sharpness of the peak. …”
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Identification of differentially expressed genes associated with ferroptosis in ulcerative colitis. by Fang Zhang, Xin Jiang, Xuyu Chen, Zheng Wang, Jianlei Xia, Bingcheng Wang, Mei Wang, Yanbing Ding

“…<h4>Results</h4>Eleven ferroptosis-related DEGs were identified (nine upregulated and two downregulated genes) in UC, with eight genes chosen from the PPI network. MCC algorithm demonstrated that SLC7A11, PSAT1, SLC7A5, ACSF2, and ACSL4 were hub genes, predicting TFs, miRNAs and drugs. …”
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Classifying the Mortality of People with Underlying Health Conditions Affected by COVID-19 Using Machine Learning Techniques by Rami Mustafa A. Mohammad, Malak Aljabri, Menna Aboulnour, Samiha Mirza, Ahmad Alshobaiki

“…The best performance was demonstrated by the Bagging algorithm with an accuracy of 83.55% when using all the dataset features. …”
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The global invasion risk of rice yellow stem borer Scirpophaga incertulas Walker (Lepidoptera:Crambidae) under current and future climate scenarios. by Shravani Sanyal, A V M Subba Rao, H Timmanna, G Baradevanal, Santanu Kumar Bal, M A Sarath Chandran, P R Shashank, V K Singh, P K Ghosh

“…The pest identity was confirmed with morphological taxonomy, and the possible habitat distribution and further spread in future climate scenarios were modelled using the MaxEnt algorithm. The climate niche for S. incertulas was also established by analyzing the correlation between the pest occurrence data of 143 locations in India and seven bioclimatic variables viz., bio01, bio02, bio03, bio05, bio12, bio13, and bio15, were chosen for predicting the distribution of S. incertulas. …”
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Constructing a web recommender system using web usage mining and user’s profiles by T. Mombeini, A. Harounabadi, J. Rezaeian Sheshdeh

“…Experiments show that the proposed method of predicting user recent requested pages has more accuracy and cover than other methods.…”
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Incorporation of Sub‐Resolution Porosity Into Two‐Phase Flow Models With a Multiscale Pore Network for Complex Microporous Rocks by Sajjad Foroughi, Branko Bijeljic, Ying Gao, Martin J. Blunt

“…We then show that our model can successfully predict steady‐state relative permeability measurements on a water‐wet Estaillades carbonate sample within the uncertainty of the experiments and modeling. …”
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Quantitative structure-activity relationship study of some angiotensin-converting enzyme inhibitor drugs in the treatment of hypertension based on Monte Carlo optimization method by Shahram Lotfi, Shahin Ahmadi, Ali Azimi

“…Materials & Methods: In this study, quantitative structure-activity relationship to predict the inhibitory activity of the data set containing 255 angiotensin-converting enzyme inhibitor compounds based on the algorithm Monte Carlo was studied. …”
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Spatial transcriptomics and scRNA-seq: decoding tumor complexity and constructing prognostic models in colorectal cancer by Wei Song, Yatao Wang, Min Zhou, Fengqin Guo, Yanliang Liu

“…We developed a 13-gene prognostic signature (PS) using machine learning algorithm (StepCox backward), which predicts the prognosis of CRC patients. …”
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Estimation of drought-induced forest decline of Scots pine in the Navarrese Pyrenees (Spain) by Marina Rodes-Blanco, Paloma Ruiz-Benito, Miguel A. Zavala, Inmaculada Aguado, Mariano García

“…Identifying and predicting areas affected by drought-induced forest decline using remote sensing is key for monitoring forest-responses to drought, as well as for forest conservation and management. …”
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Data Balancing Techniques Using the PCA-KMeans and ADASYN for Possible Stroke Disease Cases by Uung Ungkawa, Muhammad Avilla Rafi

“…This condition can cause the minority class prediction to be wrong because the model tends to predict the majority class. …”
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Variance exchange process: overcoming the problem of singular information matrices in quadratic three−variable response designs by Okim Ikpan, Felix Nwobi

“…For such matrices, the variances of predicted responses at variance points cannot be evaluated, and the variance exchange process, not possible. …”
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A robust, deep learning-based analysis of time-domain signals for NMR spectroscopy by Kyungdoe Han, Eunhee Kim, Kyoung-Seok Ryu, Donghan Lee

“…As a proof of concept, we present the resulting spectra, along with peak lists predicted by supplying only FID input to the deep learning algorithm. …”
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Methodological levels of research the post-industrial development of the city by Olha Suptelo

“…A detailed study of these processes makes it possible to predict the possible paths of developed countries and individual territories. …”
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