Predictive modeling

To predict the survival probability of septic patients over time, integrating the Sequential Organ Failure Assessment (SOFA) score with other key clinical features. Subject and method: Using stepwise and exhaustive search techniques, we analyzed time-dependent data from 125 patients in the Intensive Care Unit of the 108 Military Central Hospital, collected during a cohort study conducted between December 2019 and February 2021.

11p vihizuzen 26-05-2025 2 1   Download

This paper presents an advanced machine learning model, named ES-ANN, which combines an Artificial NeuralNetwork (ANN) with Evolution Strategies (ES) to predict flyrock distance in open-pit mines with high accuracy.

14p vijiraiya 19-05-2025 1 1   Download

This article discusses an adaptive cruise control system aimed at monitoring the distance with the vehicle ahead. This system allows for the automatic control of the throttle by electronic control signals instead of manual pedal operation. In the research, a predictive control model (MPC) is utilized within the Matlab/Simulink software to simulate the control process of the research model.

4p vijiraiya 19-05-2025 1 1   Download

This study focuses on developing a machine learning model through the process of analyzing. comparing, and evaluating the performance of five models: AdaBoost, Decision Tree, RandomForest, ExtraTree, and BernoulliNB. All models are implemented using the "Predict Student Dropout Dataset." Based on the results obtained after processing the data, the study will conduct an analysis based on two main criteria: evaluation by average percentage, standard deviation, and final outcomes, as well as evaluation using a time-series model of age (Balanced Accuracy Progression).

16p visarada 28-04-2025 1 1   Download

In this article, we will discuss the use of a database, called Churn Modeling, which collects statistical data from banks. We will also explore the application of the BernoulliNB algorithm, combined with the incremental machine learning method, to process streaming data and analyze and predict customer churn rates in banks.

10p visarada 28-04-2025 1 1   Download

Bài viết này khảo sát và tính toán tham số bộ điều khiển dự báo (Model Predictive Control - MPC) cho tháp chưng cất, một trong những thiết bị quan trọng trong các quá trình công nghiệp hóa học. MPC là phương pháp điều khiển tiên tiến, cho phép tối ưu hóa quá trình trong thời gian thực bằng cách dự báo hành vi của hệ thống và điều chỉnh các tham số điều khiển để đạt được hiệu quả tối ưu. Trong bối cảnh tháp chưng cất, MPC giúp điều khiển các thông số như nhiệt độ, lưu lượng và tỷ lệ phân đoạn nhằm duy trì hiệu suất cao và giảm thiểu tiêu thụ năng lượng.

3p vimaito 11-04-2025 1 1   Download

In this study, we explore the potential of graph neural networks (GNNs), in combination with transfer learning, for the prediction of molecular solubility, a crucial property in drug discovery and materials science. Our approach begins with the development of a GNN-based model to predict the dipole moment of molecules.

8p viling 11-10-2024 1 1   Download

The process of neural stem cell (NSC) differentiation into neurons is crucial for the development of potential cell-centered treatments for central nervous system disorders. However, predicting, identifying, and anticipating this differentiation is complex. In this study, we propose the implementation of a convolutional neural network model for the predictable recognition of NSC fate, utilizing single-cell brightfield images.

7p viengfa 28-10-2024 2 2   Download

Early prediction of ovarian cancer has not been given much attention, the application of combined models in clinical practice is not widespread, and the calculation of these models is still difficult due to the complexity and multiple variables.

8p viengfa 23-10-2024 6 1   Download

This research provides a comprehensive investigation of the planar anisotropy in stainless steel SUS 304. Constitutive modeling approaches, employing both associated and non-associated flow rules, using quadratic functions have been applied in the simulation process.

10p viengfa 28-10-2024 2 2   Download

The main objective of this study is to predict accurately the loaddeflection of composite concrete bridges using two popular machine learning (ML) models namely Random Tree (RT) and Artificial Neural Network (ANN). Data from 83 track loading tests conducted on various bridges in Vietnam were collected and analyzed.

9p viengfa 28-10-2024 3 2   Download

This article conducts an exhaustive investigation into the utilization of machine learning (ML) methods for forecasting the maximum load capacity (MLC) of circular reinforced concrete columns (CRCC) using Fiber-Reinforced Polymer (FRP). Extreme Gradient Boosting (XGB) algorithm is combined with novel metaheuristic algorithms, namely Sailfish Optimizer and Aquila Optimizer, to fine-tune its hyperparameters.

18p viengfa 28-10-2024 2 2   Download

Predicting the macroscopic permeability of porous media is critical in various scientific and engineering applications. This study proposes a novel model that combines Random Forest (RF) and rime-ice (RIME) optimization algorithm, denoted RIME-RF-RIME, to predict permeability based on six key features covering fluid phase dimensions, geometric characteristics, surrounding phase permeability, and media porosity.

14p viengfa 28-10-2024 2 2   Download

This study delves into the application of machine learning (ML), specifically a Gradient Boosting (GB) model, for predicting the punching shear strength (PSS) of two-way reinforced concrete flat slabs.

16p viengfa 28-10-2024 3 2   Download

In this study, our primary aim is to assess and compare the efficacy of Support Vector Machines (SVM) employing various kernel functions: linear (LIN), polynomial (POL), Radial Basis Function (RBF), and sigmoid (SIG) in predicting the compressive strength of concrete.

14p viengfa 28-10-2024 2 2   Download

The present paper also includes strength prediction models that consider the influence of curing temperature. In addition, the Thermogravimetry analysis (TGA) used to determine the chemically bound water content in cement-treated soil and the X-ray diffraction (XRD) test to explain the chemical mechanism in cement-treated soil are also mentioned.

18p viengfa 28-10-2024 4 2   Download

This study introduces and evaluates the Long-term Traffic Prediction Network (LTPN), a specialized machine learning framework designed for realtime traffic prediction in urban environments.

12p viengfa 28-10-2024 3 2   Download

The Axial Load Capacity (ALC) of Concrete-Filled Steel Tubular (CFST) structural members is regarded as one of the most crucial technical factors for the design of these composite structures.

17p viengfa 28-10-2024 2 2   Download

The results of this study would be useful in quickly and accurately predicting CPI to the management agencies, investors, construction contractors to pre-plan the construction investment costs. This will also help in suitably adjusting changing construction cost with time.

11p viengfa 28-10-2024 2 2   Download

The study is a complement to the studies of the tensile strength of cement paste backfill gradually becoming complete. Evaluate the reliability of the proposed model and analyze the influence of the components on the tensile strength. At the same time, the study is also interested in the influence of the components.

9p viengfa 28-10-2024 4 2   Download