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68 articles for “Predictive Analytics”
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AI-Powered Traffic Management: Enhancing Urban Mobility and Efficiency
Abstract: AbstractUrban traffic congestion is a persistent challenge, resulting in economic setbacks, extended traveldurations, excessive fuel consumption, and environmental harm. The rapid urbanization and increasingnumber of vehicles have intensified this issue, highlighting the need for smarter and more efficienttraffic management solutions. With advancements in artificial intelligence (AI), innovative trafficcontrol strategies can be implemented to optimize urban mobility and alleviate congestion. This paperexplores AI-driven traffic management solutions, focusing on machine learning-based adaptive …
Published in International Journal of Transportation Engineering and Traffic System · Vol. 11, Issue 1, 2025 · pp. 32–36 Read article
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CFD Analysis of Hydrodynamic Journal Bearing
Abstract: Journal bearings have the longest history on scientific study of any class of fluid-film bearings. These journal bearings are widely used in most of the rotating machineries due to its high load-carrying capacity and formation of fluid-film thickness during the operation. This research paper represents performance evaluation of hydrodynamic journal bearing using Computational Fluid Dynamics (CFD) approach. For this study, two different geometrical bearings are considered (circular and non-circular) operating …
Published in International Journal of Manufacturing and Materials Processing · Vol. 4, Issue 2, 2018 · pp. 23–29 Read article
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Finite Element Modeling of Deep Reinforced Concrete Beams with Web Openings
Abstract: The effects of openings on the ultimate capacity of deep beams have been studied experimentally by many researchers. However, there’s still need for analytical study using numerical methods and also the development of simple stiffness reduction models that can be easily used for quick prediction of the effects of opening sizes on the stiffness of deep reinforced concrete beams. This study is focused on modeling the behavior of deep reinforced …
Published in International Journal of Structural Mechanics and Finite Elements · Vol. 4, Issue 2, 2018 · pp. 22–30 Read article
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A Machine Learning-Based Framework for Urban Traffic Congestion Prediction and Control Using Intelligent Transportation Systems
Abstract: Abstract Traffic congestion remains a critical challenge in rapidly expanding urban areas, causing increased travel delays, excessive fuel consumption, environmental degradation, and economic inefficiencies. Traditional traffic management approaches are often insufficient, as they lack the ability to respond dynamically to continuously changing traffic conditions. This study proposes a novel data-driven framework for the prediction and management of traffic congestion using Intelligent Transportation Systems (ITS). The methodology integrates real-time and historical …
Published in International Journal of Transportation Engineering and Traffic System · Vol. 12, Issue 1, 2026 · pp. 12–17 Read article
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A Machine Learning-Based Framework for Urban Traffic Congestion Prediction and Control Using Intelligent Transportation Systems
Abstract: Abstract Traffic congestion remains a critical challenge in rapidly expanding urban areas, causing increased travel delays, excessive fuel consumption, environmental degradation, and economic inefficiencies. Traditional traffic management approaches are often insufficient, as they lack the ability to respond dynamically to continuously changing traffic conditions. This study proposes a novel data-driven framework for the prediction and management of traffic congestion using Intelligent Transportation Systems (ITS). The methodology integrates real-time and historical …
Published in International Journal of Transportation Engineering and Traffic System · Vol. 12, Issue 1, 2026 Read article
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The Effect of Stand-off Distance and Blast Yield OverStructure in Blast Test
Abstract: AbstractExplosive loads have garnered a lot of attention lately because of numerous unintentional and deliberateoccurrences that have affected important structures all over the world. As a result, there has been a lot ofresearch in this area over the last ten years. Although most of the early studies were empirical, morerecent studies have progressed into thorough and organized studies that focus on understanding thebehavior of structures subjected to blast loading conditions. …
Published in International Journal of Structural Engineering and Analysis · Vol. 12, Issue 1, 2026 Read article
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Distribution Parameter Concentration of Alkalinity and Total hardness in Stagnant Water Environment: The Concepts of Oil and Gas Emission Influence
Abstract: Model for predicting the distribution parameter concentration of alkalinity and total hardness in stagnant water environment upon the influence of oil and gasemission was investigated in this paper. The model was formulated from the basic principle of mass and momentum concept which was resolved to obtain an ordinary differential equation. A mathematical tool known as the least square method was applied to resolve the differential equation to obtain quadratic equation …
Published in International Journal of Chemical Separation Technology · Vol. 6, Issue 1, 2020 · pp. 14–22 Read article
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THE EFFECT OF STAND OFF DISTANCE AND BLAST YIELD OVER STRUCTURE IN BLAST TEST
Abstract: Abstract Explosive loads have garnered a lot of attention lately because of numerous unintentional and deliberate occurrences that have affected important structures all over the world. As a result, there has been a lot of research in this area over the last ten years. Although the majority of the early studies were empirical, more recent studies have progressed into thorough and organised studies that focus on understanding the behaviour of …
Published in International Journal of Structural Engineering and Analysis · Vol. 12, Issue 1, 2026 Read article
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Optimizing Internal Combustion Engine Performance and Fleet Fuel Economy through Machine Learning and AI using Big Data Analytics
Abstract: Abstract This paper presents a software-defined operational intelligence approach for optimizing internal combustion engine performance and fleet fuel economy using Big Data Analytics combined with Machine Learning and Artificial Intelligence. Real-world vehicle data is transformed into engineered features and virtual sensing outputs to estimate fuel consumption, driver behaviour, and component health without additional hardware. The proposed system integrates fuel optimization, predictive maintenance, driver assistance, and sustainability assessment into a unified …
Published in International Journal of I.C. Engines and Gas Turbines · Vol. 12, Issue 1, 2026 · pp. 1–7 Read article
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Smart Video Surveillance System in Banks
Abstract: This review paper represents an aristocratic approach for acute video surveillance system and human activities automatic recognition from video sequences and has an embellish presence in every sphere of life. This paper is reviewed about video monitoring systems with its uses and kinds of video superintendence techniques. But we have mainly concentrated on acute video surveillance technique based on summarization because it provides behavioral analysis capabilities based on any videos. …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 7, Issue 2, 2021 · pp. 1–4 Read article
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Machine Learning and Big Data in Smart Grid Renewable Energy Systems: Trends and Challenges
Abstract: This paper reviews eight research studies on smart grids and their role in mitigating greenhouse gas (GHG) emissions, which have become a critical concern worldwide. Renewable energy sources such as solar, wind, and hydro produce minimal or no greenhouse gases and, unlike fossil fuels, are abundant, sustainable, and ensure a long-term energy supply. Large volumes of data have been produced by recent technical developments and thorough historical data collection. Efficient …
Published in International Journal of Power Electronics Controllers and Converters · Vol. 11, Issue 1, 2025 · pp. 21–26 Read article
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Data-Driven Multiscale Design of Nanostructured Composite Materials for Sustainable Engineering Applications.
Abstract: The increasing demand for high-performance, lightweight, and environmentally sustainable materials has accelerated the advancement of nanostructured composite systems in modern engineering. This study develops a comprehensive data-driven framework for the multiscale design and optimization of nanostructured composite materials, with emphasis on the interaction between structure–property relationships across nano-, micro-, and macro-scales. By integrating hybridization strategies with intelligent manufacturing techniques—such as machine learning-assisted modeling and additive fabrication—the research addresses critical limitations …
Published in International Journal of Composite and Constituent Materials · Vol. 12, Issue 1, 2026 · pp. 48–58 Read article
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Optimizing Internal Combustion Engine Performance and Fleet Fuel Economy through Machine Learning and AI using Big Data Analytics
Abstract: This paper presents a software-defined operational intelligence approach for optimizing internal combustion engine performance and fleet fuel economy using Big Data Analytics combined with Machine Learning and Artificial Intelligence. Real-world vehicle data is transformed into engineered features and virtual sensing outputs to estimate fuel consumption, driver behaviour, and component health without additional hardware. The proposed system integrates fuel optimization, predictive maintenance, driver assistance, and sustainability assessment into a unified one-stop …
Published in International Journal of I.C. Engines and Gas Turbines · Vol. 12, Issue 1, 2026 · pp. 35–51 Read article
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Analytical study of non-linear dynamic analysis of skew bridge
Abstract: After earthquakes, the function of highway bridges is an important issue. The history of major earthquakes helps in the understanding of the performance of bridges during earthquakes. Many parameters affect the response of skewed highway bridges under both service and seismic loads which makes their behavior complex. However, under certain conditions, it may be necessary to analyze a structure to more accurately predict its structural behavior. The current procedure of …
Published in International Journal of Transportation Engineering and Traffic System · Vol. 9, Issue 2, 2023 · pp. 17–23 Read article
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Application of Hengstebeck's Model in Multicomponent Crude Oil Distillation Design
Abstract: Mathematical models were developed for the analysis of the Atmospheric Crude Distillation Unit of Port Harcourt Refinery in Nigeria. The resultant system of equations was solved using the method of matrix inversion using Mathlab software and the models predicted with reasonable accuracy composition of side draws (different fractions) and temperatures. Also, the effect of process parameters on the overall performance of the unit was studied. In addition, the study applied …
Published in International Journal of Chemical Separation Technology · Vol. 8, Issue 1, 2022 · pp. 13–19 Read article
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An Analytical Approach to Calculate the One-Dimensional Drift Velocity in Bubble Columns
Abstract: The design and scale-up of a bubble column reactor require a complete understanding of its complex hydrodynamics, which is influenced by the physical properties of the phases, the operating variables, and the design parameters. Current design procedures for bubble columns involve several steps of pilot-plant experimentation, which is expensive and time-consuming. One of the critical unknown parameters involved in designing any gas-liquid system is the gas holdup. The gas holdup …
Published in International Journal of Chemical Engineering and Processing · Vol. 5, Issue 2, 2019 · pp. 1–9 Read article
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Cloud-Based IoT Monitoring System for Pump Canal Operations: A Case Study of Narayanpur Pump Canal, Mirzapur
Abstract: Abstract The technical paper presents a comprehensive analysis of the Internet of Things (IoT)-based cloud monitoring system deployed at the Narayanpur Pump Canal (NPC), Chunar, Mirzapur, Uttar Pradesh. The system, operationalized in September 2024, provides real-time remote monitoring of 15 critical parameters across 14 pump sets through cloud-based analytics, automated alerts, and intelligent dashboards. The paper evaluates the technical architecture, demonstrated operational benefits – including a documented case of preventing …
Published in International Journal of Water Resources Engineering · Vol. 12, Issue 1, 2026 · pp. 49–68 Read article
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Smart Electricity Consumption Monitoring and Billing System
Abstract: Electricity consumption monitoring is essential for optimizing energy use and reducing costs. Traditional meters provide only cumulative readings, leading to inefficiencies and billing discrepancies. This research presents a smart electricity consumption monitoring and billing system that enables users to track real-time power usage and generate automated bills based on actual consumption. A hardware device measures voltage and current, calculates power consumption, and transmits data to a web-based platform via the …
Published in International Journal of Electrical Power System and Technology · Vol. 11, Issue 2, 2025 · pp. 8–15 Read article
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Smart Electricity Consumption Monitoring and Billing System
Abstract: Electricity consumption monitoring is essential for optimizing energy use and reducing costs. Traditional meters provide only cumulative readings, leading to inefficiencies and billing discrepancies. This research presents a smart electricity consumption monitoring and billing system that enables users to track real-time power usage and generate automated bills based on actual consumption. A hardware device measures voltage and current, calculates power consumption, and transmits data to a web-based platform via the …
Published in International Journal of Electrical Power System and Technology · Vol. 11, Issue 2, 2025 Read article
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A New Model for Prediction of Wellbore Stability Using the Three Dimensional Hoek–Brown Failure Criterion
Abstract: Wellbore stability is one of the crucial issues in oil and gas industries. The issues related to instability of wells, impose significant unwanted costs on drilling operation.The objective of this paper is to present the 3D-wellbore stability prediction models for vertical wellbores. The three dimensional Hoek–Brown strength criterion developed by Zhang and Zhu conjunction with linear poroelastic constitutive model is utilized to develop the models. This models leads to easily …
Published in International Journal of Geological and Geotechnical Engineering · Vol. 3, Issue 2, 2017 · pp. 10–15 Read article