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1332 articles for “Predictive Modeling”
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Time Series Methods in Meteorology: A Review of Predictive Models and Applications
Abstract: The accurate prediction of time series data holds substantial significance in various fields, enabling informed decision-making and resource optimization. In this study, temperature variations over time are predicted using the Autoregressive Integrated Moving Average (ARIMA) model. Reliable temperature projections are more important now than ever because of climate change and its effects. For time series prediction problems, the ARIMA model—which is well-known for its ability to capture temporal dependencies in …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 13, Issue 2, 2024 · pp. 35–46 Read article
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Optimization of Maximum Charge Per Delay Using Site-Specific Ground Vibration Prediction Models for Safe Blasting in an Opencast Coal Mine
Abstract: Drilling and blasting are critical operations in opencast coal mining that directly influence rock fragmentation, excavation efficiency, and production performance. However, excessive blast-induced ground vibration and air overpressure can create safety and environmental concerns, particularly in mines located near villages and sensitive structures. The present study was conducted at Chapapur-II Colliery, Mugma Area, Eastern Coalfields Limited (ECL), with the objective of optimizing blast design through the determination of safe maximum …
Published in Journal of Geotechnical Engineering · Vol. 13, Issue 2, 2026 · pp. 1–13 Read article
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A Combined ECG and PPG Signal Powered Artificial Intelligence-Based Prediction Model for Stroke
Abstract: Stroke is one of the most common causes of morbidity and mortality around the world, and emphasis on prevention and early detection strategies cannot be overstated. This review aims to integrate techniques of artificial intelligence with electrocardiogram and photoplethysmogram signals to enhance stroke prediction and monitoring of cardiovascular health. All in all, the application of artificial intelligence that incorporates machine learning, deep learning, or hybrid models gives robust tools toward …
Published in Journal of Control & Instrumentation · Vol. 16, Issue 2, 2025 · pp. 18–26 Read article
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ML-Based Predictive Modeling of Mechanical Properties in 3D-Printed Polymer Composites for IoT Applications
Abstract: This study aims to develop an interpretable and high-accuracy machine learning framework for predicting the mechanical properties of 3D-printed fiber-reinforced polymer composites, with a focus on structure–property correlations relevant to polymer processing and functional performance. Composite specimens based on PLA and ABS matrices were fabricated using FDM with varying weight fractions (5–20 wt%) of carbon and glass fibers. Standardized mechanical testing (ASTM D638, D256, D790) was performed to evaluate tensile …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 61–78 Read article
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Predictive Modeling of Polymer Elasticity and Mechanical Strength Using Deep Learning for Functional Polymer Material Characterization and Performance Assessment
Abstract: Knowing the polymers elasticity and mechanical strength is essential in the characterization of functional polymer materials, for rapid characterization and to avoid extensive experiments. Traditional polymer characterization methods are often time consuming and resource intensive and the mechanical response of polymers can be nonlinear, thus complicating the prediction of the properties. These limitations can be overcome by introducing a Variational Temporal Fusion Transformer (VaTFT) for the deep learning prediction of …
Published in Journal of Polymer & Composites · Vol. 14, Issue 5, 2026 Read article
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CIPHER Intelligence: AI-Powered Global Military Expenditure Analysis and Predictive Modeling
Abstract: Military expenditure analysis has emerged as a critical component of economic and geopolitical intelligence in the modern era. This paper presents CIPHER Intelligence, a comprehensive AI-powered platform for analyzing and predicting global military spending patterns across 211 countries spanning54 years (1970-2024). We employ advanced machine learning techniques, particularly Random Forest regression models, to achieve 99.5% prediction accuracy for military expenditure forecasting based on economic indicators. The platform integrates data from …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 1, 2026 · pp. 1–8 Read article
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PREDICTIVE MODEL TO MONITOR THE TRANSPORT OF URANIUM IN UNCONSOLIDATED PREDOMINANT LATERITIC SOIL FORMATION
Abstract: This paper express the rare of uranium transport in predominant lateritic soil formation, the formation were observed to be unconsolidated in the study environment thus deposit high uranium substance in the area, their migration were influenced by manmade and natural origin activities, but the soil experiences migration rate in linear and fluctuation phase in there transport process, the study explain the rate of pressure from void ratio and it low …
Published in Journal of Geotechnical Engineering · Vol. 6, Issue 1, 2019 · pp. 31–39 Read article
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Deep Learning Architectures for Predictive Modeling in Financial Time Series
Abstract: This study investigates the application of deep learning architectures, particularly convolutional neural networks (CNNs), to the challenging task of financial time series forecasting. Financial markets are inherently complex and influenced by a range of factors, making accurate prediction of price movements a difficult problem. In this research, historical financial data including stock prices, volumes, and other relevant indicators are used to train CNN models aimed at capturing the underlying patterns …
Published in Current Trends in Signal Processing · Vol. 15, Issue 3, 2025 · pp. 45–55 Read article
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Predictive Modeling and Optimization of Citric Acid Bioproduction Using Ipomoea batatas Peel (Sweet Potato)
Abstract: In this research, the Box–Behnken design was adopted and applied to the process and the total of 30 experimental runs were generated for the liquefaction steps considered for the purpose of citric acid bioproduction using Ipomoea batatas peel (sweet potato) which was very helpful during the investigatory process of this research. The liquefaction step adopted were very sensitive as gross investigations to ascertain their usability was made and proven worthy …
Published in Journal of Modern Chemistry & Chemical Technology · Vol. 13, Issue 1, 2022 · pp. 32–43 Read article
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A study on IoT and AI for Predictive Modeling and Control of Infectious Disease Transmission
Abstract: Background: The global response to novel and recurring infectious diseases is frequently hindered by surveillance systems that are slow, siloed, and reactive. Traditional epidemiology relies on retrospective analysis of clinical reports, often missing the critical early phase of autocatalytic spread. The urgency of modern public health necessitates a shift toward real-time, predictive intelligence. Methods: This study investigates the development and deployment of a synergistic paradigm integrating the Internet of Things …
Published in International Journal of Pathogens · Vol. 2, Issue 2, 2025 Read article
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Model Prediction to Monitor the Transport of Nocardia Influenced by Bulk Density and Dissolved Oxygen in Eleme Stream
Abstract: This paper monitors the behavior of Nocardia deposition in Eleme Streams, the study was carried out to determine the rate of this predominant microbe in the stream, the migration of the contaminant experienced highest rates of concentration at the point of discharge, which is the initial concentration of the contaminants. Decreases with respect to increase in distances at ninety metres in the entire figures were observed. Bulk density and dissolved …
Published in Journal of Water Pollution & Purification Research · Vol. 7, Issue 1, 2020 · pp. 1–14 Read article
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Predictive Modeling of Polymer Composites for Medical Implants Using Artificial Intelligence Techniques
Abstract: The use of polymers in biomaterials was now key to designing the next generation of medical implants, which need to be strong and also compatible with living tissue. Tests for biocompatibility, such as those done in the laboratory and by doing experiments on animals, require much time and many resources, so the need for computer-based approaches becomes clear. An artificial intelligence approach was provided in this study to determine how …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 665–692 Read article
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Integration of Soil Profile Data in Crop Prediction Models: A Comprehensive Review
Abstract: Farmers in many areas of India are having crop production issues due to soil and climate. There is no comprehensive guide accessible to assist them in developing the appropriate types of plants using modern technology. Farmers may be unable to benefit from agricultural scientific developments due to illiteracy and may continue to rely on human practises. This complicates getting the desired yield. Crop failure, for example, could be the result …
Published in Current Trends in Signal Processing · Vol. 13, Issue 1, 2023 · pp. 6–11 Read article
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Development of a predictive model for determining mechanical properties of nano Al2O3 reinforced adhesive bonded SS304 single lap joint
Abstract: In this study, single lap joints were prepared by adding nano-additives (Al2O3) in the quantity of 3 wt % in the phenolic resin, and the overlap length was varied to observe the effect on joint engineering properties. In the experiments, a single component system of a specific grade of phenolic resin was used as a binder, and aluminum (AA8011), as well as stainless steel (SS304), was used as adherends. The …
Published in Journal of Polymer & Composites · Vol. 10, Issue 3, 2022 · pp. 20–28 Read article
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Model to Predict a Split Range Control of Hot and Cold Water System
Abstract: Mathematical model was developed to monitor, predict, and stimulate hot and cold water system using split range control application. Computer program language of MATLAB software of ODE function was applied to monitor the trend of temperature parameter in the system. Result obtained revealed decrease in temperature value of the hot water and increase in the temperature value of cold water until equilibrium was attained at 132°F at > 1.0 h. …
Published in Journal of Water Pollution & Purification Research · Vol. 8, Issue 4, 2021 · pp. 32–42 Read article
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A Mathematical Model for the Prediction of Microbial Decay and Kinetics
Abstract: The application of mathematical model for the prediction of kinetics of microbial decay was developed and simulated with variation in time. The result obtained demonstrates increase in the microbial decline in concentration revealing high depletion in substrate concentration as well as the available nutrient in the system. The functional parameters of the kinetic used in the monitoring, predicting and simulating the microbial characteristics in terms of decay rate is within …
Published in Journal of Modern Chemistry & Chemical Technology · Vol. 12, Issue 3, 2021 Read article
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A Predictive Analytics Model for Maximising Profit in e-commerce Companies
Abstract: AbstractPredictive analytics have become a crucial aspect for many e-commerce companies. The primary objective of this work is to apply and compare different machine learning techniques to build an efficient and accurate predictive model for the analysis and identification of customers who are expected to purchase again in the next 90 days. The main performance goal of the predictive model is to maximize profit for the e-commerce company by providing …
Published in E-Commerce for Future & Trends · Vol. 4, Issue 2, 2017 · pp. 10–23 Read article
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Statistical Models for Predicting Genetic Variability and Disease Susceptibility
Abstract: Differences in genetics are key to understanding why some individuals are more prone to certain diseases than others. Recent advancements in genomic research, combined with statistical modeling techniques, have made significant strides in predicting disease risk based on genetic factors. This review explores the application of statistical models for predicting genetic variability and their role in disease susceptibility. We discuss traditional methods like linear regression and genome-wide association studies (GWAS), …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 1, 2025 · pp. 30–34 Read article
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Advancing Healthcare Systems: A Machine Learning Approach to Multi-Disease Prediction
Abstract: The integration of machine learning algorithms in healthcare has revolutionized the way we approach disease prediction and diagnosis. An attempt to employ machine learning techniques to forecast numerous diseases is presented in this study. A diverse dataset containing patient records, medical history, and relevant features for various diseases was used to develop predictive models. Feature selection and normalization were among the preprocessing methods used to clean and prepare the data. …
Published in Journal of Electronic Design Technology · Vol. 16, Issue 1, 2025 · pp. 1–6 Read article
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The Integrity of Eadic-Hofstee Plot Model to Predict the kinetic Parameters of Crude Oil Degradation using Vernonia amygdalina Stem
Abstract: The integrity of Eadic-Hofstee concept was tested for the determination of the functional coefficients and parameters of crude oil degradation kinetics. The techniques enhanced the relationship between the substrate divided by the specific rate of the substrate degradation against substrate concentration (TPH). The investigation reveals the values of the biokinetic parameters of maximum specific rate of substrate degradation (Vmax) and the equilibrium constant values of the substrate degradation (Ks). The …
Published in Journal of Petroleum Engineering & Technology · Vol. 14, Issue 2, 2024 · pp. 37–47 Read article