Mechanisms and optimization for simultaneous removal of Cd(II) and Sb(V) from aqueous solutions using birnessite and fulvic acid composite by Changsheng Jin, Jingjing Lu, Yin Gao, Baowei Hu, Yuxi Liu

“…The RF model demonstrated superior predictive accuracy (R² = 0.8037, RMSE = 0.0625) compared to the RSM and GABP models. …”
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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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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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Development of a mathematical model of dependence of specific volumetric electrical resistance of SIW-4 insulation on factors affecting its reliability by Denisov I. V.

“…It also opens up the possibility of developing the second stage of the study, associated with the construction of an algorithm for the method of predictive assessment of the residual life of the insulation material of the conductor under study.…”
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Comprehensive analysis of cuproptosis-related genes in immune infiltration and development of a novel diagnostic model for acute kidney injury by Yajing Li, Yingxue Ding

“…The six-gene cuproptosis-related signature exhibited remarkable predictive efficiency for AKI.…”
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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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Bioinformatics analysis of potential targets influencing the prognosis of OSCC by ZOU Xian, SONG Tao

“…The prognostic model based on SPP1 and ITGA3 genes can effectively predict the prognosis of OSCC patients. [Conclusion:] ITGA3 and SPP1 may be biomarkers for the prognosis of OSCC patients. …”
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The J-PLUS collaboration. Additive versus multiplicative systematics in surveys of the large scale structure of the Universe by Carlos Hernández-Monteagudo, G. Aricò, J. Chaves-Montero, L. R. Abramo, P. Arnalte-Mur, A. Hernán-Caballero, Francisco José Galindo-Guil, C. López-Sanjuan, V. Marra, R. von Marttens, E. Tempel, J. Cenarro, D. Cristóbal-Hornillos, A. Marín-Franch, M. Moles, J. Varela, H. Vázquez Ramió, J. Alcaniz, R. Dupke, A. Ederoclite, L. Sodré Jr., R. E. Angulo

“…This model allows us devising a novel algorithm that addresses the identification and correction for either additive and/or multiplicative contaminants. …”
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Forecasting dengue in Bangladesh using meteorological variables with a novel feature selection approach by Mahadee Al Mobin

“…The study concludes that relative humidity is redundant in predicting dengue infection, while meteorological factors exhibit more significant short-term impacts compared to long-term and immediate impacts. …”
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Edge computing-based ensemble learning model for health care decision systems by Asir Chandra Shinoo Robert Vincent, Sudhakar Sengan

“…The main drawback of traditional Machine Learning (ML) techniques is their failure to predict reliably. To solve this problem, the proposed model creates an Ensemble Extreme Learning Machine (EN-ELM) algorithm that combines predictors trained on several different data sets. …”
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Non-Destructive Detection of Soybean Storage Quality Using Hyperspectral Imaging Technology by Yurong Zhang, Wenliang Wu, Xianqing Zhou, Jun-Hu Cheng

“…The feature variables were extracted by a variable iterative space shrinkage approach (VISSA), competitive adaptive reweighted sampling (CARS), and a successive projections algorithm (SPA). Partial least squares regression (PLSR), support vector machine (SVM), and extreme learning machine (ELM) models were developed to predict crude fatty acid values of soybeans. …”
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Intelligent Resource Allocation for Immersive VoD Multimedia in NG-EPON and B5G Converged Access Networks by Razat Kharga, AliAkbar Nikoukar, I-Shyan Hwang

“…The SDN framework manages the entire network, predicts bandwidth requirements, and operates the immersive media dynamic bandwidth allocation (IMS-DBA) algorithm to efficiently allocate bandwidth to IVoD network traffic, ensuring that QoS metrics are met for IM services. …”
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The balance between traffic control and economic development in tourist cities under the context of COVID-19: A case study of Xi'an, China. by Wang Xiang, Zezhi Wang, Xin Pan, Xiaobing Liu, Xuedong Yan, Li Chen

“…The results show that the Pearson correlation coefficient between the predicted data of this improved model and the actual data is 0.996, the R-square in the regression analysis is 0.993, with a significance level of below 0.001, suggesting that the predicted data of the model are more accurate. …”
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Microseismic Signals in Heading Face of Tengdong Coal Mine and Their Application for Rock Burst Monitoring by JianJu Ren, Wenlong Zhang, Zheng Wu, Ji Li, Ying Shen

“…Through trial operation, it is found that large energy (three-channel and four-channel triggering) coal vibration events successfully predicted a rock burst. The MS system of 117 track gateway of Tengdong coal mine should be able to remove the interference signals in real time through the algorithm and take the number of large energy coal vibration signal rather than all coal vibration events as the predictor for rock burst risk monitoring.…”
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Analysis of a nonsteroidal anti inflammatory drug solubility in green solvent via developing robust models based on machine learning technique by Lijie Jiang, Qi Li, Huiqing Liao, Hourong Liu, Bowen Tan

“…Abstract This study develops and evaluates advanced hybrid machine learning models—ADA-ARD (AdaBoost on ARD Regression), ADA-BRR (AdaBoost on Bayesian Ridge Regression), and ADA-GPR (AdaBoost on Gaussian Process Regression)—optimized via the Black Widow Optimization Algorithm (BWOA) to predict the density of supercritical carbon dioxide (SC-CO2) and the solubility of niflumic acid, critical for pharmaceutical processes. …”
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Studi Komparasi Naive Bayes, K-Nearest Neighbor, dan Random Forest untuk Prediksi Calon Mahasiswa yang Diterima atau Mundur by Puteri Sejati, Munawar Munawar, Marzuki Pilliang, Habibullah Akbar

“…This study used the classification method to predict prospective students. They are accepted or withdrawn. …”
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Vehicular-Computational Resource Geofencing: Efficient Spatiotemporal Uncertainty Estimation by Ghada Afifi, Bassem Mokhtar

“…We evaluate the efficiency of the proposed resource geofencing algorithm under different realistic operating conditions. …”
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Integrated neural network and AspenPlus model for entrained flow gasification kinetics investigation by Balaban Dario, Lubura Jelena, Kojić Predrag

“…High R2 values (>0.99) for all models suggested good agreement between simulated and predicted values. Genetic algorithm-based optimization studies for maximization of hydrogen content and cold gas efficiency result in mean ER values of 0.35 and 0.41, respectively, at a temperature of 1200 °C. …”
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Artificial intelligence-driven mobile interpretation of a semi-quantitative cryptococcal antigen lateral flow assay by David Bermejo-Peláez, Ana Alastruey-Izquierdo, Narda Medina, Daniel Capellán-Martín, Oscar Bonilla, Miguel Luengo-Oroz, Juan Luis Rodríguez-Tudela

“…The system exhibited capability of predicting CrAg concentrations exclusively based on a photograph of the LFA (Pearson correlation coefficient of 0.85). …”
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Enhancing Fault Detection in AUV-Integrated Navigation Systems: Analytical Models and Deep Learning Methods by Huibao Yang, Bangshuai Li, Xiujing Gao, Bo Xiao, Hongwu Huang

“…In this model, the fault detection function was formulated by comparing the predictions generated by the PSO-LSTM model with those derived from the Kalman filter. …”
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