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268 articles for “error model”
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Errors-in-Variables Model for Photovoltaic Cell
Abstract: AbstractThe contribution of solar energy to the world's total energy supply has grown significantly. Energy from the sun is the most abundant and freely available energy on the planet. So, the importance of modelling the photovoltaic cell also increased remarkably. Many models for photovoltaic cell had been proposed since the beginning of the solar energy exploitation. Electronic equivalent circuit models, first-principles models and empirical models are the different modelling techniques …
Published in Journal of Semiconductor Devices and Circuits · Vol. 6, Issue 3, 2019 · pp. 8–15 Read article
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Compensation of Volumetric Error in CNC Machine Tools: A Review
Abstract: In today’s high competitive market, the customer requirement for quality products has increased rapidly. Abundant researches are carried out to make machine tools more versatile and accurate in the fulfilment of such requirements. Now days the CNC machine tools of various configurations with more motion flexibility are used to prepare high quality in machined components. But still, the accuracy is not achieved up to desirable level for some of crucial …
Published in Journal of Mechatronics and Automation · Vol. 4, Issue 2, 2017 · pp. 12–20 Read article
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Mathematical Modeling Analysis of India's Accident &Use of Fly Ash and Polymers in Road Safety
Abstract: Accident predicting models (APMs) are exceptionally strong tools for adaptation and mitigation strategies because they have the ability to predict both the severity and frequency of crashes. Road accidents are a major problem all throughout the world, especially in developing countries. Understanding the key variables that contribute can assist in reducing the frequency of traffic collisions. This study also discovered recent developments on fly ash, green composites, other polymer materials …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 488–499 Read article
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Enhancing Dimensional Accuracy of Affordable 3D-Printed Objects Via Solid Model Tuning For Industrial Manufacturing
Abstract: In the industrial applications of 3D printing (3DP) technologies, achieving precise dimensional accuracy and precision as well as improving surface quality are essential goals. With a focus on cost-effective engineering applications, this experimental research examines how solid model geometry tuning improves the internal and exterior dimensional accuracy of inexpensive 3DP technologies. Dimensional errors in the X, Y, and Z directions were meticulously measured on 3D parts made using Material Extrusion/Fused …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 201–210 Read article
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Intercomparison of Parameter Estimation Methods of EVI Distribution for Rainfall Frequency Analysis
Abstract: For planning, design and management of civil and hydraulic structures, estimation of extreme rainfall for a given return period is considered as one of the important parameters. This can be achieved through Extreme Value Analysis (EVA) by fitting of Extreme Value Type-I (EVI) distribution to the observed data. In this paper, a comparative study on determination of parameters of EVI distribution by eight different methods such as graphical method, method …
Published in Journal of Water Resource Engineering and Management · Vol. 7, Issue 3, 2020 · pp. 1–13 Read article
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PERFORMANCE-BASED WIND RESPONSE ANALYSIS OF TALL RCC IREGULAR STRUCTURES USING AUTODESK REVIT AND ROBOT STRUCTURAL ANALYSIS
Abstract: The increasing trend of vertical construction has made wind effects a critical consideration in the design of tall reinforced concrete (RCC) buildings. The response of such structures is largely governed by their geometric configuration, stiffness characteristics, and modelling accuracy under wind loading conditions Wind loads are evaluated based on standard provisions such as IS 875 (Part 3): 2015, which provide essential guidelines for structural safety This study focuses on evaluating …
Published in Journal of Structural Engineering and Management · Vol. 13, Issue 3, 2026 Read article
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Capacitance–Resistance Model Application to Reservoirs Primarily Under Aquifer Influx
Abstract: Previous Capacitance – Resistance Models that have been developed to characterise black oil reservoirs undergoing waterflooding do not apply to waterflooding of reservoirs primarily under aquifer influxresulting in significant error. This paper has attempted to overcome this limitation by presenting the aquifer influx as a pseudo injector whose injection rate is represented by an existing aquifer model.The influencing parameters of the model have been modified to include an aquifer influx …
Published in Journal of Materials & Metallurgical Engineering · Vol. 10, Issue 1, 2020 · pp. 16–29 Read article
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Predictive Modeling and Optimization of Tensile and Flexural Strength in FDM 3D Printing Using Decision Trees and Bayesian Optimization.
Abstract: This research investigates predictive modelling and optimization technique for the tensile and flexural strength of PlA (Poly Lactic Acid) in Fused Deposition Modelling (FDM) 3D printing. Employing Decision Trees and Bayesian Optimization enhances comprehension and control of 3D printing process. Precise model predicts PLA material properties based on input parameters. Methodology involves rigorous data preprocessing, encompassing, cleaning, transformation, and normalization. Hyperparameter optimization via grid search systematically explores configurations, optimizing model …
Published in Journal of Polymer & Composites · Vol. 11, Issue 12, 2023 · pp. 203–214 Read article
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Non-Contact Quantification of Swelling-Induced Deformation in Polymer Hydrogels Using Image Analysis
Abstract: Swelling of polymer hydrogels governs transport, mechanics, and functional performance in biomedical systems, yet it is often reported using bulk ratios that conceal spatially heterogeneous deformation and boundary-driven instabilities. This study presents a non-contact image-analysis framework to quantify swelling-induced deformation by tracking shape and boundary evolution from time-lapse imaging. The approach segments the hydrogel region, extracts a sub-pixel refined contour, and computes boundary displacement descriptors including mean and upper-percentile normal …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1499–1509 Read article
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Comparative Analysis of P, PI, and PID Controllers Based on Time Domain Specifications
Abstract: In this research, proportional (P), proportional-integral (PI), and proportional-integral-derivative (PID) controllers utilized in control systems are thoroughly compared. The study attentions on assessing system presentation with time-domain specifications such as rise time, settling time, overshoot, and steady-state error. Mathematical modeling and controller design are discussed, shadowed by analytical comparison. The results establish that while P and PI controllers offer simplicity, PID controllers provide superior performance in terms of stability and …
Published in International Journal of Advanced Control and System Engineering · Vol. 4, Issue 2, 2026 Read article
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Demand Forecasting for Seasonal Demand Patterns: Case Study of a Pharmaceutical Company
Abstract: In this paper the authors have developed a heuristic model that addresses demand forecasting for products those follow seasonal patterns. The model is checked against various renowned forecasting methods by comparing forecast errors. The proposed heuristic model is found to give better results than the Winters’ and other exponential models. Non-linear optimization is used to choose the values of smoothing parameters rather than depending on human judgment or experience. This …
Published in Journal of Production Research & Management · Vol. 4, Issue 3, 2014 · pp. 1–7 Read article
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Time Series Forecasting of Electricity Consumption: A Comparative Analysis of ARIMA and SARIMA Models
Abstract: Accurate electricity demand forecasting plays a vital role in energy planning, efficient power system operation, and sustainable resource management. This study conducts a comparative evaluation of the Autoregressive Integrated Moving Average (ARIMA) and Seasonal Autoregressive Integrated Moving Average (SARIMA) models using ten years of monthly electricity consumption data collected from a national electricity regulatory authority. The performance of both models is assessed using forecasting accuracy metrics, including Mean Absolute Error …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 2, 2026 · pp. 43–53 Read article
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Enhancement in Biomedical Polymer Nanocomposites: Biocompatibility and Mechanical Property Predictions using Machine Learning
Abstract: A machine learning (ML)-based framework is developed and validated through experimental analysis and comparative modeling to enhance system dependability and improve prediction performance. The proposed framework includes key stages such as data preprocessing, feature evaluation, model training, and performance benchmarking to determine the most effective prediction technique. Several machine learning models were evaluated, including Ensemble models, Artificial Neural Networks (ANN), Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 275–296 Read article
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Machine Learning Assisted Design and Analysis of Polymer Composite Materials for Sustainable Renewable Energy Systems
Abstract: Accurate prediction and optimization of polymer composite properties is of paramount importance in the design of these lightweight, durable, and sustainable materials within renewable energy technologies. This work will provide a holistic machine learning-assisted framework that unites materials informatics with domain-specific features and state-of-the-art ML methodologies in the prediction of the mechanical properties of polymer composites, such as tensile strength. This includes embedding several ensemble models, including Random Forest and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 391–402 Read article
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Artificial Neural Network Modelling to Optimize Micro-Drilling Parameters of ECDM of Developed Novel Zn/(Ag+Fe)-MMC
Abstract: Several engineering fields have increased their use of metal matrix composites (MMCs) in the past few years. Due to the increase in composites, the demand for accurate machining has also become important. Specifically, pertaining to biomaterial applications, accuracy factor with desired surface finish is critical. While the near-net shape manufacturing process has advanced, MMCs frequently require post-mould machining to achieve surface quality, and dimensional tolerances. In the present study, a …
Published in Journal of Polymer & Composites · Vol. 11, Issue 1, 2023 · pp. 01–13 Read article
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A Review Paper on The Mathematical Foundations of Artificial Intelligence
Abstract: Artificial Intelligence (AI) is deeply rooted in various branches of mathematics, which provide the theoretical foundation and practical tools for developing intelligent systems. This paper explores the crucial role of mathematics in AI, focusing on key areas such as Linear Algebra, Probability and Statistics, Optimization Techniques, Calculus, Graph Theory, and Fourier and Wavelet Transforms. Linear Algebra is fundamental for representing and manipulating data, with applications in dimensionality reduction and neural …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 3, 2025 · pp. 7–14 Read article
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Comparative Analysis of AI-Based Approach vs. Traditional Methods in Climate Modeling
Abstract: Climate modeling helps to predict the future of climate variations and human interference with environment. The traditional General Circulation Models (GCMs) are based on physics-derived mathematical equations but are very expensive in terms of computation. There are alternative ways to perform climate modeling in recent years with the rise and improvement of Artificial Intelligence (AI) based approaches in term of predictability, efficiency, and classification of extreme events compared to conventional. …
Published in Current Trends in Information Technology · Vol. 15, Issue 3, 2025 · pp. 26–32 Read article
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Dependency of pure liquid pool boiling heat transfer coefficient to bubble contact angle on roughened Brass heater in new model
Abstract: Heat transfer coefficient of nucleate pool boiling Nucleation is a basic part of phase transformations, which plays an important role in understanding and describing any phase change processes. For a boiling process, nucleation appears in the initial stage, and directly affects bubble formation and boiling intensity. According to the heterophase fluctuations which induce phase transition, the phase change has two main types. Classically, phase change caused by the fluctuation with …
Published in Emerging Trends in Chemical Engineering · Vol. 9, Issue 2, 2022 · pp. 29–36 Read article
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Forecasting of Factors Affecting Thermiston Work Productivity Estimation by Using Artificial Neural Network
Abstract: The research aims to find factors affecting of Thermiston work productivity and the derivation of an equation to predict the rates of Thermiston work productivity by using artificial neural network technology and compared with traditional methods. The Artificial Neural Network with multilayer by back-propagation error technique for modeling the productivity estimation is used, it is founded that the ANN are able to manage to, can predict the productivity for Thermiston …
Published in Journal of Construction Engineering, Technology & Management · Vol. 7, Issue 1, 2017 · pp. 10–21 Read article
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Optimized Machine Learning Framework for Battery State Prediction in Smart Charging Systems
Abstract: Good estimation of battery states, including State-of-Charge (SoC), State-of-Health (SoH), and Remaining Useful Life (RUL), are important in managing energy wisely and controlling the adaptive charging. This work introduces a streamlined machine learning model based on the ability to use multi-dimensional sensor measurements in terms of voltage, current, temperature, and cycle number to forecast battery conditions with high accuracy. Decent preprocessing, such as noise elimination, feature scaling, and calculated features, …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 55–66 Read article