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190 articles for “nonlinear modelling”
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Wind Forecasting Using Various Neural Networks in Machine Learning
Abstract: Wind Power Forecasting, as the name applies is a process in which data of past is used to tell what kind of output can be expected from a wind turbine in the foreseeable future. Machine learning, can be said to be a derivation of artificial intelligence that makes it possible for the system to learn automatically and improve upon itself from faults, without needing to tell the system to do …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 8, Issue 2, 2021 · pp. 32–43 Read article
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Structure–Property Modeling of Cement-Based Multi-Component Composites Using Ensemble Machine Learning and Explainable Feature Attribution
Abstract: Accurate prediction of compressive strength is central to structure–property optimization, quality control, and sustainability-driven design in cement-based composite materials. Cementitious systems represent heterogeneous multi-phase composites composed of reactive binder matrices and dispersed aggregate phases, whose macroscopic mechanical performance emerges from complex nonlinear interactions among constituents and curing-dependent microstructural evolution. This study develops a data-driven structure–property modeling framework to quantify the nonlinear dependence of compressive strength on multi-component composite composition and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 112–131 Read article
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Machine Learning-Based Structure–Property Quantification of Advanced Polymer Composites
Abstract: Advanced polymer composites are widely used in high-performance engineering due to their superior mechanical and multifunctional properties. Accurate structure–property quantification is essential for efficient material design and reducing experimental costs. Existing Machine Learning (ML) approaches often exhibit limited predictive generalization due to inadequate feature discrimination and suboptimal hyperparameter tuning. To address these limitations, the proposed method enhances the ability to capture the complex nonlinear interactions among composite structural descriptors. The …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Study of an Improved Quantum Particle Swarm Optimization-Based Framework for Neural Network Optimization in Modelling of Polymer Data
Abstract: The accurate forecasting of polymer viscosity at various physicochemical conditions has been quite critical due to the nonlinear interactions and interrelations between the variables. This paper suggests a better hybrid modelling framework, which involves the use of Artificial Neural Networks (ANN) and more advanced versions of Quantum Particle Swarm Optimization (QPSO) to better predict polymer viscosity. The input parameters taken are, namely, log (shear rate), polymer concentration, NaCl concentration, Ca …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 282–297 Read article
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Nonlinear Finite Element Analysis of Reinforced Concrete Exterior Beam Column Joint Subjected to Monotonic Loading
Abstract: A numerical analysis of exterior beam-column joint subjected to constant axial load on the column top and monotonic load applied at the beam tip is presented in this work. A strain-based nonlinear finite element program is developed in MATLAB R2009a. The nonlinear analysis of reinforced concrete structural member is carried out considering it as a two-phase system. The concrete in nonlinear range is considered as orthotropic material having different stress-strain …
Published in Recent Trends in Civil Engineering & Technology · Vol. 4, Issue 2, 2014 · pp. 12–21 Read article
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Viscoelastic Behavior, Interfacial Mechanics, and Reliability of Polymer Interlayers in Laminated Glass Composites: A Comprehensive Review
Abstract: The laminated glass systems are regarded as hybrid polymer–glass composites where the viscoelastic behavior of polymer interlayers mostly controls mechanical response. These interlayers (polyvinyl butyral (PVB), ionoplast, ethylene-vinyl acetate (EVA), etc.) have time-, temperature- and rate-dependent properties which significantly affect shear transfer, energy dissipation, and fracture resistance. But the baseline polymer-relevant processes at the molecular and interfacial level are to a large extent unknown [1]. This review provides a materials-focused …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 258–268 Read article
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A Machine Learning Approach to Forecasting Outcomes in Limited Overs Cricket
Abstract: This study explores the application of machine learning techniques to forecasting outcomes in limited overs cricket matches, with a particular focus on One Day Internationals (ODIs). The research investigates how classification algorithms can be effectively utilized to analyze both contextual and dynamic factors that influence match results, including venue details, toss decisions, team strength, and historical performance records. By employing a structured methodology encompassing feature selection, data preprocessing, model training, …
Published in Recent Trends in Sports · Vol. 2, Issue 2, 2025 · pp. 09–19 Read article
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Parameter Estimation of Software Reliability Growth Model
Abstract: Reliability normally covers each and every part of the device thinking about hardware, software program and processes but software program reliability paperwork an important factor as we are continually worried with efficient and quality software program. Software reliability is a crucial characteristic of software, nice for predicting the diploma of creditability of the precise software for the specified time frame and in particular surroundings. Software reliability models are categorized into …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 7, Issue 1, 2020 · pp. 15–22 Read article
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Design of Model-based Controllers for a CSTR Process
Abstract: The objective of this paper is to propose suitable control strategies for controlling highly nonlinear system represented by the mathematical model of the jacketed continuous stirred tank reactor (CSTR) with so called Van de Vusse reaction. The operating point of the reactor is chosen so as to give maximum yield of the desired product. The mathematical model of reactor is obtained by considering the feed flow rate (Fr) as the …
Published in Journal of Instrumentation Technology & Innovations · Vol. 5, Issue 1, 2015 · pp. 13–20 Read article
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Extended Fixed Point Theorems in Menger PM-Type Spaces: Generalized Auxiliary Functions and Contractivity Conditions
Abstract: Background: Fixed point theory in probabilistic metric spaces, particularly Menger spaces, has been a subject of intensive research due to its applications in nonlinear analysis and mathematical modeling. Traditional approaches often impose restrictive constraints on the defining properties of Menger spaces and limit the class of auxiliary functions in contractivity conditions Methods: We extend recent fixed point theorems in Menger spaces by: (1) introducing the notion of Menger PM-type spaces …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 3, 2025 · pp. 1–6 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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Harmonic Analysis of 6-Pulse Diode Bridge Rectifier Circuits
Abstract: This paper analyzes the steady-state harmonic performance of the six-diode, 3-phase rectifier bridge circuits. A procedure for determining the frequency spectra of the different voltages and currents within the bridge circuit, resulting from a 60-Hz 3-phase supply, is presented. The effect of the smoothing shunt-capacitor is also demonstrated. Based on a Mathematica code, the paper presents the results of a comprehensive list of case studies. The procedure can handle unsymmetrical …
Published in Journal of Power Electronics and Power Systems · Vol. 10, Issue 2, 2020 · pp. 1–10 Read article
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A Multivariate Adaptive Regression Splines Based Study of Soil Parameters and Their Impact on Onion Yield in Bhavnagar District
Abstract: Bhavnagar district is one of the prominent onion-growing areas in the Saurashtra region of Gujarat, encompassing key talukas such as Mahuva, Talaja, Ghogha, Jesar, and Palitana. Onion cultivation in the district is carried out across three distinct seasons: rabi, kharif, and late kharif with harvesting periods extending from April to May for the rabi crop and from October to March for the kharif and late kharif crops. The productivity of …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 15, Issue 1, 2026 · pp. 53–64 Read article
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Artificial Intelligence and Constitutive Modeling Equations for Predictive Design of High-Performance Polymer Composites
Abstract: Growing polymer composite applications demand accurate mechanical prediction, yet complex interactions and conventional constitutive models limit predictive capability and require extensive calibration. To report these challenges, this research recommends a combined Artificial Intelligence (AI) and constitutive modeling approach based on an Enhanced Tasmanian Devil Optimizer-tuned Residual Neural Network with Multilayer Perceptron (ETDO-ResNet-MLP) for the predictive design of high-performance polymer composites. The study uses a publicly available Polymer Composite Property Dataset …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Organic Phase Speciation of 36% Tri-Iso Amyl Phosphate/N-Dodecane Solvent during Nitric Acid Extraction
Abstract: Several solutions of 36% TiAP/n-dodecane solvent were equilibrated with different concentrations of aqueous nitric acid solutions at 298.15 K at a phase ratio of unity. The resultant equilibrated aqueous and organic solutions were analyzed for acidity. A three-solvate model with molecular HNO3 based mechanism was assumed for nitric acid extraction by TiAP. This model was analogous to the 3-solvate model for nitric acid extraction by TBP, recently reported by authors. …
Published in Journal of Nuclear Engineering & Technology · Vol. 5, Issue 2, 2015 · pp. 28–34 Read article
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Multi-loop Adaptive Internal Model Controller for Two Interacting Conical Tank Process
Abstract: In this paper, an adaptive multi-loop internal model control (IMC) scheme is proposed for nonlinear process. Nonlinear multivariable process is decomposed into linear single input single output process. The interaction effect and illness of each linear region is analyzed by RGA (Relative Gain Array) and singular value decomposition method (SVD). It is a matrix technique used to determine condition number of steady state plant to avoid sensitivity problem which arises …
Published in Journal of Instrumentation Technology & Innovations · Vol. 5, Issue 1, 2015 · pp. 21–31 Read article
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Real-Time Air Quality Prediction Using IoT-Integrated Polymer Sensors and Recurrent Neural Networks
Abstract: Real-time air quality monitoring remains a critical challenge in urban environments, where traditional sensor infrastructures often suffer from limited responsiveness, poor scalability, and high deployment costs. The increasing prevalence of NO₂ pollution, a key contributor to respiratory and cardiovascular ailments, demands advanced sensing platforms capable of both accurate detection and predictive inference. Existing methods either rely on rigid electronic sensors lacking adaptability or on statistical forecasting models that fail to …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 332–347 Read article
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Mechanical Performance Assessment of Hybrid FRP Laminates with Carbon Fiber Core Using Experimental and Numerical Approaches
Abstract: The high strength-to-weight ratio, corrosion resistance and design flexibility of Fiber-reinforced polymer (FRP) composites have attracted considerable attention in aerospace, automotive and structural applications. This work presents an experimental and finite element study on the tensile and flexural behavior of epoxy-based hybrid FRP laminates. Five laminate configurations were manufactured, including a unidirectional carbon fiber laminate and four hybrid laminates, Kevlar–Carbon–Kevlar (K/C/K), Glass–Carbon–Glass (G/C/G), Kevlar–Carbon–Glass (K/C/G), and Glass–Carbon–Kevlar (G/C/K). For all …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Advancements in Agricultural Forecasting: A Review of Machine Learning Based Crop Yield Prediction
Abstract: Agricultural productivity plays a critical role in global food security, and accurate crop yield prediction is essential for optimizing resource allocation and decision-making in farming. The rapid advancements in Machine Learning (ML) and Deep Learning(DL)have transformed agricultural forecasting, enabling data-driven approaches for crop prediction. This review paper provides a comprehensive analysis of various ML and DL techniques applied in crop yield forecast, highlighting the ineffectiveness, challenges, and future directions. The …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 3, 2025 · pp. 32–38 Read article
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Computational Intelligence and Neuro-Fuzzy Modelling of Polymer Composites: A Critical Review of Performance Prediction and Optimization
Abstract: The increased variety in polymer matrices, reinforcements, fillers, and processing parameters has led to the need to better understand the structure-property, process-property relationships in order to accurately predict and optimize the performance of polymer composites. This paper reviews the applications of computational intelligence methods in polymer composites, with special focus on artificial neural networks, adaptive neuro-fuzzy inference systems, machine learning techniques, and hybrid optimization. The literature is analyzed based on …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article