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503 articles for “predictive analysis”
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Multi-factor Fused Lightpath QoT Prediction for Optical Networks: A Multiple Reservoir Analysis Strategy
Abstract: Investigating the channel quality of transmission (QoT) in-depth is crucial for responsive and instant transparent optical network management. However, current lightpath QoT predictions are devoted to univariate modeling. Due to the QoT metrics complicated time-varying process and the existing effects of inter-channel factors, despite the use of an advanced and efficient echo state network (ESN), it is difficult to obtain ideal results in univariate prediction mode. Thus, this paper considers …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 1, 2024 · pp. 28–34 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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Performance Analysis of Machine Learning Algorithms For Disease Prediction
Abstract: In this 21st century, where Digitization makes humans measure, record, analyze and to manipulate the huge amount of data as per the requirement, prediction of the decease based on Machine Learning models will be representing one of the good applications of the efficient data handling. An Automatic Decease Prediction system based on the symptoms would be the great boon for the medical practitioners. The Supervised Machine Learning models, such as …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 11, Issue 3, 2024 · pp. 9–18 Read article
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A Review on Lung Cancer Prediction Using Machine Learning
Abstract: Lung cancer continues to be a major contributor to cancer-related mortality across the globe. Timely diagnosis and reliable prediction models play a crucial role in enhancing treatment outcomes and survival rates for patients. The present study focuses on the utilization of machine learning (ML) methods for the prediction of lung cancer. Using datasets that incorporate clinical records, imaging modalities, and genetic profiles, the research assesses the predictive capabilities of multiple …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 3, 2025 · pp. 1–11 Read article
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Machine Learning Assisted Timing Violation Prediction in Sub-7nm VLSI Physical Design
Abstract: The continuous scaling of semiconductor technology into the sub-7nm regime has introduced significant challenges in timing closure due to process variability, interconnect delay, power density, and manufacturing uncertainties. Conventional static timing analysis techniques often require extensive computational resources and iterative optimization cycles, resulting in increased design complexity and longer turnaround time. This research proposes a Machine Learning Assisted Timing Violation Prediction framework for sub-7nm VLSI physical design to improve early-stage …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 4, Issue 1, 2026 Read article
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Data-Driven Digital Twin Model for Real-Time Strength Estimation in Polymeric Materials
Abstract: The real-time prediction of mechanical properties in polymeric materials is essential for ensuring quality, consistency, and operational efficiency in modern manufacturing systems. As industrial processes become increasingly complex, traditional trial-and-error approaches to material characterization are no longer sufficient to meet the demands of high-throughput production environments. This study introduces a digital twin-integrated machine learning approach for the real-time estimation of tensile strength in polymeric materials by combining simulation-driven insights with …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 246–257 Read article
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Early Alzheimer’s Disease Prediction Using Vision Transformers and Attention-Guided MRI Analysis
Abstract: Alzheimer’s Disease (AD) continues to be a major global health concern, with early detection being crucial for effective intervention. While conventional machine learning and convolutional neural network (CNN) approaches have made notable progress in automated AD diagnosis using MRI data, they often struggle with capturing long-range dependencies and maintaining spatial contextual awareness. In this research, we propose a novel framework using Vision Transformers (ViTs) for early Alzheimer’s prediction from 3D …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 30–40 Read article
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Predictive Maintenance Strategies for Safety-critical Mechanical Systems
Abstract: Ensuring the reliability and safety of industrial systems is essential, especially in high-risk sectors such as aerospace, manufacturing, and energy. Predictive maintenance (PdM) has become a crucial approach for minimizing operational failures and improving maintenance efficiency. This research introduces an advanced PdM framework that enhances industrial safety by integrating Internet of Things (IoT) technology, machine learning (ML), and big data analytics. By enabling real-time monitoring and predictive fault detection, this …
Published in Journal of Industrial Safety Engineering · Vol. 12, Issue 1, 2025 · pp. 12–17 Read article
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Loan Prediction Using Random Forest Algorithm
Abstract: With the growth of the banking sector, more and more people are applying for bank loans. All of these loans are not allowed. The principal income of bank assets arises from the interest earned on the loan. Bank profit or loss depends largely on the amount of the loan, i.e., whether customers pay off the loan or fail. The main purpose of banks is to invest their assets in secure …
Published in Journal of Advanced Database Management & Systems Read article
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Multi-factor Fused Light path QoT Prediction for Optical Net-works: A Multiple Reservoir Analysis Strategy
Published in Trends in Opto-electro & Optical Communication Read article
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Supply Chain Optimization Using Big Data
Abstract: In the references to add productivity and short the appendences, and increase customer value, supply chain optimization is a very crucial part of contemporary business operations. Supply chain management has been transformed by the emergence of big data, which can provide analysis and insight from many different sources of information. This content explores the importance of using big data analytics to improve the delivery process. Thanks to the evolution of …
Published in Journal of Production Research & Management · Vol. 14, Issue 2, 2024 · pp. 19–25 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 on polyhouse monitoring system
Abstract: The integration of Internet of Things (IoT) technology in agriculture has revolutionized traditional farming practices, offering innovative solutions to enhance productivity, sustainability, and resource efficiency. This study explores the role of loT-based systems in smart agriculture, focusing on applications such as environmental monitoring, automated irrigation, crop health prediction, and precision farming. The reviewed systems utilize advanced sensors to monitor parameters like temperature, humidity, soil moisture, and light intensity, transmitting real-time …
Published in International Journal of Advanced Control and System Engineering · Vol. 3, Issue 2, 2025 · pp. 1–9 Read article
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IoT-Based Adaptive Irrigation Solution for Smart Farming
Abstract: Facing escalating global challenges such as water scarcity and unpredictable weather conditions, precision farming emerges as a crucial solution for enhancing agricultural productivity and sustainability. This paper introduces a smart irrigation system which employs IoT-based technology, integrating sensors and a designed to enhance water efficiency and boost agricultural productivity. The system leverages live data related to soil moisture and temperature, cloud cover, and precipitation, coupled with a cloud-based infrastructure using …
Published in Journal of Microcontroller Engineering and Applications · Vol. 12, Issue 3, 2025 · pp. 17–24 Read article
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The Role of Mathematical Reasoning in Legal Analysis: Bridging Two Disciplines
Abstract: This research paper explores the integration of mathematical reasoning into legal analysis, emphasizing the inherent similarities between the two disciplines. Both fields rely on logical structures, such as deductive reasoning, inductive reasoning, and other formal methods of thought. By examining these parallels, the paper reveals the nascent but growing interaction between mathematics and law, uncovering how the organizational schemes that underpin mathematical principles can enhance legal argumentation, decision-making, and analysis. …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 11, Issue 3, 2024 · pp. 1–5 Read article
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Exploring Antimalarial Activity of Chalcone Derivatives through QSAR
Abstract: Background: The core structure of chalcones contains a reactive α,β-unsaturated system within the aromatic rings, which plays a key role in mediating various biological effects. These effects include enzyme inhibition, anticancer activity, anti-inflammatory properties, as well as antibacterial, antifungal, antimalarial, antiprotozoal, and anti-filarial actions.Modifying the structure by introducing substituent groups to the aromatic ring can enhance potency, reduce toxicity, and expand their range of pharmacological actions. Methods: A total of …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 3, Issue 2, 2025 · pp. 1–6 Read article
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Efficient Energy Management using Artificial Intelligence (AI) and Machine Learning (ML) in Chemical Industry
Abstract: The globe is moving toward higher usage of renewable energy sources, particularly solar and wind energy, as a result of depleting fossil fuel supplies and growing environmental concerns. There are several forecasting methods available for effective wind energy utilization. This review uses algorithms for predicting solar and wind energy as well as artificial intelligence (AI) techniques. A wind-coal coupling energy system planning scheme was designed to lower the high energy …
Published in Journal of Modern Chemistry & Chemical Technology · Vol. 16, Issue 2, 2025 · pp. 33–50 Read article
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A Review of Machine and Deep Learning Techniques for Cyber Security
Abstract: Nowadays in the digital landscape, cyber threats and attacks are increasing in an exponential manner, posing server risks to organizations and critical infrastructures. Data breaches often result from sophisticated threat models that exploit vulnerabilities in networks, systems and user behaviors. Cyber solutions are increasingly incorporating machine learning and deep learning to prevent and mitigate these security issues. These technologies have the potential to detect anomalies, classify threats and predict potential …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 01–07 Read article
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Computational Fluid Dynamics and Composite Material Study on Scoop-Type Savonius Turbine for Train-Based Energy Generation
Abstract: This study investigates the feasibility of integrating a scoop-type savonius vertical-axis wind turbine (VAWT) on the rooftop of a moving train to generate renewable onboard power. The motivation stems from increasing demands for sustainable energy solutions and reducing reliance on fossil fuels, particularly in transportation. A two-blade savonius turbine, with dimensions of 0.4 m in diameter and 0.5 m in height, was modeled in PTC Creo Parametric 3.0 and analyzed …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 566–580 Read article
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Evaluating Delay Impacts: From Root Cause Analysis to Dispute Resolution
Abstract: Construction projects inherently involve complex coordination among multiple stakeholders, interdependent tasks, and unpredictable external challenges, which frequently cause schedule overruns and disputes. Traditional contractual mechanisms—such as extensions of time (EoT), liquidated damages, and force majeure clauses—serve to define responsibilities, allocate risk, and establish formal dispute pathways when delays arise. For example, EoT provisions protect contractors from penalties when delays are beyond their control, provided proper notice and evidence are submitted …
Published in Journal of Structural Engineering and Management · Vol. 12, Issue 3, 2025 · pp. 11–25 Read article