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54 articles for “non-linear optimization”
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AI/ML-Based Approach to Solar Irradiance Prediction and Energy Suitability
Abstract: In this paper, due to challenges in precisely predicting solar irradiance, which is essential for solar power system optimization, we employed six diverse machine learning (ML) techniques: Linear Regression, Decision Tree, Random Forest, Gradient Boosting methods (including XGBoost), and Neural Networks—to analyze and predict outcomes using a dataset containing meteorological and temporal features. Key variables include wind speed, humidity, and temperature, which significantly influence the model’s predictive capability. Each method …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 16, Issue 3, 2025 · pp. 36–48 Read article
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Measuring Microstructure, Wear Resistance, and Mechanical Reliability Enhancement in Polymer Nanocomposites via Data-Driven Analysis with Deep Learning
Abstract: Polymer nanocomposites have gained great attention owing to their superior mechanical performance, better wear resistance and customizable microstructural properties for aerospace, automotive, medicinal and industrial engineering applications. However, the correct evaluation of the link between the microstructure evolution and the material reliability is a huge issue due to the intricacy of nanoscale interactions and diverse material characteristics. In this study, we propose a data-driven approach that integrates deep learning and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Intuitionistic Fuzzy Hypergraph Laplacians and Dominating Transversals for Resilient Discrete Network Design
Abstract: This manuscript develops a discrete mathematical framework for resilience analysis on networks whose interactions are polyadic, uncertain, and partially conflicting. Classical graphs compress multi-way coordination into pairwise edges, while ordinary fuzzy graphs often ignore the non-membership information that becomes critical in emergency logistics, infrastructure interdependence, and cyberphysical coordination. We therefore formulate an intuitionistic fuzzy hypergraph in which each vertex hyperedge incidence carries membership, non-membership, and hesitation, and we construct a …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 13, Issue 2, 2026 · pp. 15–21 Read article
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Data-Driven Energy Forecasting for Smart Homes: Ensemble Learning from IoT Meters and Relevance for Polymer-Composite Based Smart Infrastructure
Abstract: Reliable estimation of household electricity demand is relevant in creating efficiency in energy usage, optimization of the loads, and intelligent demand-side management in intelligent grid systems. This paper introduces a varied machine learning model that approaches residential electric consumption prediction using an assortment of ensemble regression boosts, including Linear Regression, Lasso Regression, Decision Tree Regressor, Random Forest, and Gradient Boosting, to predict residential electricity consumption environments on a time-series arrested …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 29–64 Read article
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Comparison of Mamdani and Sugeno Fuzzy Inference Systems for a Three Tank Level Control System
Abstract: The level control of a three tank system has become a research focus due to the nonlinear process and multivariables. It is well known that the conventional controllers are suitable to control linear processes and their design is based on the exact mathematical model. In this paper, we developed a mathematical model for a three tank system and proposed an effective controller design based on fuzzy logic by which more …
Published in Journal of Control & Instrumentation · Vol. 5, Issue 2, 2014 · pp. 14–20 Read article
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A Hybrid Multi-Physics Ensemble Deep Learning Framework for Simultaneous Prediction of Thermal and Electrical Conductivity in Functional Polymer-Based Nanocomposites
Abstract: Polymer-based nanocomposites have become promising materials for applications in energy storage, flexible electronics, biomedical devices, aerospace components, and advanced engineering because of their tunable thermal and electrical properties. Reliable prediction of these properties is essential for accelerating material design; however, existing analytical models and conventional machine learning techniques often fail to represent the complex interactions among filler characteristics, polymer matrices, processing conditions, and interfacial transport phenomena. This work presents HMEP-Net, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1062–1082 Read article
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Design and Performance Investigation with Erbium-Ytterbium Co- Doped Fiber Amplifier Link
Abstract: AbstractLight wave propagation through optical fiber suffers from numerous linear and nonlinear effects. To compensate it techniques have been adopted. Amongst optical fiber amplifiers doped with ions are one of the key tools to enhance spectral efficiency further. In this vision, an optical design with EDFA and Erbium ytterbium co-doped fiber amplifier is presented for the single channel. The design’s performance has been investigated for numerous optical parameters for instance …
Published in Recent Trends in Sensor Research & Technology · Vol. 4, Issue 2, 2017 · pp. 6–13 Read article
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A Study on Chemical Composition in Temperature Sensor
Abstract: As the demand for precision thermal monitoring in extreme environments – such as aerospace propulsion systems and micro-electromechanical systems (MEMS) – continues to escalate, the chemical stability of temperature sensing elements has become a critical focal point. This study investigates the correlation between the chemical composition of thin-film resistance temperature detectors (RTDs) and their operational longevity under thermal cycling. By employing X-ray Photoelectron Spectroscopy (XPS) and Energy-Dispersive X-ray Spectroscopy (EDS), …
Published in Journal of Nanoscience, NanoEngineering & Applications · Vol. 16, Issue 2, 2026 · pp. 1–7 Read article
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Optimization of Process Parameters of an Induction Furnace for Aluminium 6061 using Robust Design Approach
Abstract: Electric induction furnaces are extensively used in the foundry industries for the preparation of alloys and metal castings. The induction furnace works on the principal of electromagnetic induction. Some of the applications of induction heating include heat treatment, melting, surface treatment and in food industry. The detailed study about the working of an induction furnace was done. The induction furnace procured by mechanical department of our college is made by …
Published in Journal of Thin Films, Coating Science Technology & Application · Vol. 4, Issue 1, 2017 · pp. 6–12 Read article
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Challenges and Solutions in Load Frequency Control: A Review of Controller Design
Abstract: The Load Frequency Control (LFC) of two area interconnected reheat thermal systems utilising a traditional proportional integral (PI) controller is described in this study. Boiler dynamics, a non-linear generating rate constraint, and a regulator dead band are all integrated into the system. When nonlinearities and boiler dynamics are considered, the traditional PID & P controllers do not produce sufficient control performance. To overcome this issue, a PI Controller has been …
Published in Journal of Control & Instrumentation · Vol. 14, Issue 3, 2023 · pp. 36–50 Read article
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Machine-Learning-Assisted Development of Polymer-Biochar Composite Adsorbents for the Removal of Heavy Metals from Gomti River Water
Abstract: Rapid urbanization, industrial discharge, and agricultural runoff pose a significant threat to freshwater sustainability and public health. Within these ecosystems, polymer pollutants—such as microplastics, nanoplastics, synthetic fibres, and additive residues—have emerged as persistent vectors capable of adsorbing and transporting toxic heavy metals. Because these polymeric contaminants dynamically interact with conventional aquatic parameters to alter pollutant mobility and ecological risk profiles, there is an urgent need to transition from passive environmental …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 72–95 Read article
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Experimental and Simulation Study on Reduction Kinetics of Magnetite Ore by using Hydrogen
Abstract: In the present work, magnetite ore fines pellets were prepared for a study of reduction kinetics using hydrogen gas. In the present work, various parameters are investigated to assess their influence on reduction kinetics with respect to hydrogen utilisation. The different input variables influence the process, yielding the reduction fraction. The effect of temperature on reduction kinetics with hydrogen flow rate was explored for the optimum value of these parameters. …
Published in Journal of Materials & Metallurgical Engineering · Vol. 16, Issue 1, 2026 · pp. 71–81 Read article
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Comparative Seismic Analysis of Composite Building Frames Considering Wind Pressure per I.S. 875-III: An ETABS-Based Review
Abstract: The seismic analysis of composite building frames, while factoring in wind pressure in accordance with the I.S. 875-III standards, stands as a pivotal imperative. It serves as the linchpin in guaranteeing not only the structural robustness but also the optimal performance of these edifices, ensuring they can withstand the formidable forces of nature with unwavering resilience.This study provides an in-depth and thorough analysis of past research endeavors that have delved …
Published in Journal of Construction Engineering, Technology & Management · Vol. 13, Issue 3, 2023 · pp. 1–8 Read article
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From Differential Equations to Data Science: A Survey on Analytical Methods in Contemporary Problems
Abstract: The integration of differential equations and data science methods represents a dynamic and evolving approach to solving contemporary challenges across a wide range of disciplines, including engineering, physics, biology, economics, and finance. Differential equations have long served as fundamental tools for modeling continuous systems and processes, offering powerful insights into the behavior of natural and man-made phenomena. For example, they describe how heat diffuses through materials, how populations grow in …
Published in Recent Trends in Mathematics · Vol. 2, Issue 2, 2025 · pp. 1–6 Read article