Search
275 articles for “predictive modeling”
-
Multiple Regression Analysis of Compressive, Flexural, and Split Tensile Strength in M40 Grade Concrete
Abstract: Concrete plays a key role as a construction material across the globe. The strength parameters of the concrete are primary reason for which it is designed for. The design mixed concrete has multiple strength parameters like compressive strength, spilt tensile strength, flexural (bending) strength etc. For each newly design mixed concrete, the mentioned strength parameters are tested for various time duration like 3 days, 7 days, 14 days, 28 days …
Published in International Journal of Construction Engineering and Planning · Vol. 11, Issue 2, 2025 · pp. 20–34 Read article
-
Dynamic Matrix Control Versus Nonlinear ModelPredictive Control for the Van de Vusse ContinuousStirred-Tank Reactor: Diagnosing and Correcting aCost-Function Pathology That Masked NMPC’sTrue Performance
Abstract: The Van de Vusse reaction in a continuous stirred-tank reactor (CSTR) is a benchmark for nonlinear multivariable control, but its narrow operating envelope creates a trap for nonlinear model predictive control (NMPC): when the setpoint step is small relative to the plant’s reachable range, a standard quadratic NMPC cost function can make zero control action mathematically optimal, even with a perfect prediction model. This paper documents that failure mode, traces …
Published in International Journal of Chemical Separation Technology · Vol. 12, Issue 2, 2026 · pp. 55–66 Read article
-
A Performance Evaluation of Transformer, LSTM, and ARIMA Models for LoadForecastinginIndia'sRenewable-RichSmart Grid
Abstract: India is trying to use renewable energy such as solar and wind to produce extreme and unpredictable fluctuations within India's National Smart Grid. These extreme fluctuations create difficulties for traditional load forecasting methods, including Autoregressive Integrated Moving Average (ARIMA) models, to provide stable and efficient operation through the creation of accurate short-term load forecasts. To accomplish this, the research aims to develop high-quality predictive models by comparing three modelling methods: …
Published in International Journal of Renewable Energy and its Commercialization · Vol. 12, Issue 2, 2026 Read article
-
Predictive Analytics in E-Learning: Enhancing Student Performance Through Machine Learning Models
Abstract: With the explosion of electronic devices and internet technologies in today’s world, the amount of data we store has grown massively. Data is simply information that has been organized in a way that makes it easy to share or work with. A potent technology that enables computers to learn from data without direct programming is machine learning, which we employ in our research. The focus of this study is on …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 10, Issue 2, 2024 · pp. 1–5 Read article
-
A Study on Supervised Machine Learning-based Airports/Flight Delay Analysis and Classification
Abstract: Airline delays are a major cause of the financial losses that plague the global aviation business. Airports, airlines, and passengers all suffer when flights are delayed. Their forecast is vital to the commercial aviation industry's decision-making process. Flight presents a significant obstacle for the aviation sector. Increased air traffic and subsequent flight delays are a direct result of the aviation industry's rapid growth over the past two decades. The economic …
Published in International Journal of Software Computing and Testing · Vol. 9, Issue 2, 2023 · pp. 20–36 Read article
-
Predicting User Engagement on Social Media: A Comparative Study of Machine Learning-based Modeling Approaches
Abstract: Abstract Even while mobile social apps are becoming more and more important in people's daily lives, little is known about the elements that motivate users to interact with these apps. The goal of this work is to analyze and define the transition patterns of individual users' in-app actions as a temporally changing action graph. According to our investigation, action graphs are a useful tool for characterizing user behaviour patterns and …
Published in International Journal of Computer Aided Manufacturing · Vol. 11, Issue 2, 2025 · pp. 41–62 Read article
-
A comparative study on the use of conventional and osadebe mix designs in predicting the marshall stability of asphalt concrete
Abstract: Asphalt concrete is an important construction material all over the world with its design always following conventional procedure in developing countries such as Nigeria. This study was channelled towards using Osadebe’s theory in comparison to the conventional design procedure in the design of asphalt concrete providing a handy mathematical model for the determination of the stability of asphalt concrete given any components’ mix proportion and vice versa. Two designs were …
Published in International Journal of Transportation Engineering and Traffic System · Vol. 6, Issue 1, 2020 · pp. 10–23 Read article
-
A Review on Surface Error Compensation in Thin-Walled Component Machining
Abstract: *Author for CorrespondenceManikandan HareendranE-mail: [email protected] 1,4,5,6Associate Professor, Department of Mechanical Engineering, Mangalam College of Engineering (APJAKTU), Kottayam, Kerala, India2,3Assistant Professor, Department of Mechanical Engineering, Mangalam College of Engineering (APJAKTU), Kottayam, Kerala, India7Professor, Department of Mechanical Engineering, Mangalam College of Engineering (APJAKTU), Kottayam, Kerala, India Received Date: November 12, 2024Accepted Date: November 14, 2024Published Date: November 22, 2024 Citation: Rajeeve K. Mohana, Santhu Varghese Thomas, Rahul Krishnan, Johan George Cherian, Navish …
Published in International Journal of Structural Mechanics and Finite Elements · Vol. 10, Issue 2, 2024 · pp. 1–11 Read article
-
Modeling legionella spp pressured by two dimensional variation of velocityand horizontal transverse dispersion in udi creek
Abstract: This study carried out was to monitor the transport system of Legionella in Udi creek.The rate of Legionella was determined through microbial analysis investigated at different location in the study environment.The contaminants was observed to be predominant in the creek.This condition implies that there will be serious illness since the human settlers collect waterfrom the creek for their every domestic activities.Monitoring the rate of pollution from Legionella becomes imperative based …
Published in International Journal of Water Resources Engineering · Vol. 6, Issue 1, 2020 · pp. 34–46 Read article
-
Climate Change Modeling Using Machine Learning and Big Data
Abstract: Climate change is now one of the biggest issues that affect the world today and studying its impacts for it is very significant in enabling the formulation of social policies. This paper also discusses how climate sciences, machine learning, and big data analytics can greatly help in the improvement of the current capacities in climate modeling. Explaining the methods of climate modeling, we look at how the big data offers …
Published in International Journal of Software Computing and Testing · Vol. 11, Issue 1, 2025 · pp. 6–11 Read article
-
Mathematical Models and Forecast of Effect of Flow Rate on Turbidity and Total Suspended Solids Within Water Bearing Aquifer
Abstract: The aim of study is to develop mathematical models to predict turbidity and total suspended solids upon the influences of recharge and flow rate as a functional parameter in distribution interaction of water parameters within the water bearing aquifer taking a main well A as dispersing point to other wells. Predictive models have been generated to account for the effect of flow rate on turbidity and total suspended solids within …
Published in International Journal of Water Resources Engineering · Vol. 4, Issue 1, 2018 · pp. 52–60 Read article
-
Simulation Models to Estimate Annual Runoff Volume in different Characteristics Soil Formation
Abstract: The study is aimed at developing mathematical models that will simulate annual runoff to acorresponding annual rainfall for different soil characteristics formation in the studied area. Theresearch established predictive models for sandy soil and sandy loam and coastal alluvium and siltyloam that can be used to simulate annual runoff to a corresponding annual rainfall usingmathematical tool of linear regression method and high correlation was found between annualrainfall and annual runoff …
Published in International Journal of Water Resources Engineering · Vol. 7, Issue 1, 2021 · pp. 26–33 Read article
-
Combine Effect of Dry and Decomposed Raffia Palm in the Bioremediation of Oil-based Drill Cutting
Abstract: This study determines the effect of dry substrate and decomposed raffia palm for degradation of oil- based drill cuttings bioremediation. The remediation process was effectuated using dry and decomposed raffia palm. The experiment was carried out at the research Centre located at Agricultural and Environmental Engineering departmental workshop in Rivers State University, Port Harcourt. Samples of oil-based drill cuttings were bulked in eleven reactors with four replications (T1, T2, T3-T11). …
Published in International Journal of Composite Materials and Matrices · Vol. 9, Issue 1, 2023 · pp. 21–29 Read article
-
Advancements in Predictive Maintenance: A Review of Data-Driven Approaches, Machine Learning, and AI in Diverse Industrial Landscapes
Abstract: The Internet of Things (IoT), the use of machine learning (ML), and artificial intelligence (AI)-driven advances in predictive maintenance are the key topics of this study. With the goal of offering a thorough grasp of existing approaches and potential future developments, it analyzes applications in predictive maintenance in many sectors. Predictive maintenance approaches are the major topic of discussion, with an emphasis on their advantages, disadvantages, difficulties, and prospects. Additionally, …
Published in International Journal of Computer Aided Manufacturing · Vol. 10, Issue 2, 2024 · pp. 19–32 Read article
-
Predicting the TPH Concentration along Horizontal Direction of Stagnated Water Contaminated with Crude Oil
Abstract: The research predicts and models TPH concentration along Horizontal Direction of Stagnated water contaminated with Crude Oil. TPH diffusion in the stagnant water media was studied using Developed Dispersion and Degradation Model incorporated with first order degradation rate and the Monod equation. TPH content decreased with increase in time, but randomly varied across the depths. The impact of crude oil was more in the fresh water compared to salt water …
Published in International Journal of Chemical Separation Technology · Vol. 9, Issue 1, 2023 · pp. 12–22 Read article
-
Cognitive Metallurgy: A Study on Microstructure and Energy Efficiency in High-Temperature Alloying via Sensor Fusion and Deep Reinforcement Learning
Abstract: Background Traditional high-temperature metallurgical processes, such as continuous casting and specialty alloy synthesis, are characterized by high energy consumption, stochastic variability, and reliance on post-process defect inspection. The inability to precisely monitor, model, and predict the real-time thermal, chemical, and mechanical state of molten metal and cooling substrates results in significant material waste and inconsistent microstructural integrity. Methodology This study introduces a novel framework for Cognitive Metallurgy utilizing an integrated …
Published in International Journal of Metallurgy and Alloys · Vol. 11, Issue 2, 2025 · pp. 27–36 Read article
-
Integrating Cellular Automata for Predicting Urban Expansion: A Case Study of Bavdhan, Sus, and Mahalunge
Abstract: Rapid Urban Expansion in the metropolitan cities like Pune, result in indiscriminate land use changes transforming natural landscapes. Such haphazard spatial development poses a risk to depletions of resources along with the disarray of the ecological system. A proactive approach to predicting and analyzing such changes is necessary in promoting the well-managed growth of cities. For the complex nature of urban growth, simulation method is used for analyzing spatial patterns, …
Published in International Journal of Town Planning and Management · Vol. 12, Issue 1, 2026 · pp. 51–62 Read article
-
Advanced Magnesium-Based Metallic GlassComposites for Biomedical Implant Applications: AMachine-Learning-Informed Approach
Abstract: Magnesium-based bulk metallic glasses (Mg-BMGs) combine strength, low density, and tunable degradability. Their amorphous matrix has a small plastic process zone. This zone is only about 4 μm wide. A small process zone keeps most glasses brittle. Adding a second phase is the best fix. This chapter extends Mg-BMGs to true composites. We call these Mg-based bulk metallic glass composites, or Mg- BMGCs. The chapter covers matrix engineering and interfacial …
Published in International Journal of Composite Materials and Matrices · Vol. 12, Issue 2, 2026 · pp. 48–65 Read article
-
A Role of Machine Learning for Students' Academic Success Prediction
Abstract: This research paper aims to identify early predictions of students’ academic success with the help of different indicators. One of the crucial parts of the study is identifying additional indicators that play an essential role in defining students' academic success. Early prediction of success will be helpful for various stakeholders such as students, parents, educators/teachers, institutions, universities, and the government. Machine Learning is a part of Artificial Intelligence (AI) and …
Published in International Journal of Computer Aided Manufacturing · Vol. 10, Issue 1, 2024 · pp. 1–6 Read article
-
AI-Integrated Precision Agriculture System for Fertilizer Optimization, Multimodal Crop Yield Prediction
Abstract: Agriculture is rapidly transforming into a data-driven ecosystem supported by advances in artificial intelligence (AI), Internet of Things (IoT) sensor networks, and satellite remote sensing technologies. These innovations enable precision-driven decision-making aimed at improving productivity while minimizing environmental impact. This paper presents an AI-integrated precision agriculture system designed to optimize fertilizer usage and enhance crop yield prediction accuracy through a robust multimodal deep learning framework. The proposed approach integrates heterogeneous …
Published in International Journal of Plant Biotechnology · Vol. 12, Issue 1, 2026 · pp. 11–17 Read article