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651 articles for “predictive systems”
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Support Vector Machine Inspired Load Forecasting of a State University in Haryana
Abstract: Estimating the possible environmental impact and determining probable capital requirements are made easier with a solid grasp of electricity demand. Beginning in the middle of the 20th century, demand forecasting for electric power networks was studied theoretically. Prior to that, the study of demand forecasting had not developed because of the small scale of power networks. With the use of statistical prediction techniques, plans for the electric power industry have …
Published in Trends in Electrical Engineering · Vol. 15, Issue 2, 2025 · pp. 33–40 Read article
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Unified Ensemble Techniques for Enhanced DDoS Attack Prevention and Detection
Abstract: Today’s world is entirely reliant on the internet. The internet is a worldwide information source that all users rely on, hence its accessibility is critical. There have been reports in recent years, particularly in the information and technology division of significant organizations worldwide, of data breaches where the terms denial-of-service (DoS) and DDoS are consistently present in the stolen material. Network security is seriously threatened by DoS attacks. They have …
Published in International Journal of Wireless Security and Networks · Vol. 2, Issue 2, 2024 · pp. 20–27 Read article
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Machine Learning Optimization for VARTM Carbon Polymer Laminates
Abstract: Vacuum-assisted resin transfer moulding (VARTM) is a key low-cost, out-of-autoclave process for manufacturing large-scale carbon-fibre reinforced polymer (CFRP) laminates crucial to aerospace wings, wind-turbine blades, marine hulls, and automotive structures. Unpredictable resin flow often leads to voids, dry spots, and race-tracking defects, resulting in 27.9% scrap rates and lengthy, costly trial-and-error design cycles. Although surrogate models provide rapid impregnation predictions for simple flat-plate geometries, vision-based monitoring is limited to idealized …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 229–245 Read article
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Malicious Network Traffic Detection Using Hybrid Feature Selection with Ensemble Neural Network
Abstract: The detection of malicious network traffic is a critical aspect of cybersecurity, aiming to protect sensitive data and maintain the integrity of network systems. This study introduces a novel approach that combines hybrid feature selection with ensemble neural networks to enhance the accuracy and efficiency of malicious network traffic detection. The dataset used in this study was obtained from Kaggle and offers a wide-ranging and varied collection of network traffic …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 27, Issue 3, 2025 Read article
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Calorie Measurement and Food Recognition Using Machine Learning
Abstract: Nowadays, all over the world most people are suffering from different types of diseases or obesity. This is because of bad food habits or eating food without knowing the calorie and other sources from the foods. Precise techniques for gauging food and energy consumption play a vital role in addressing obesity. Offering users or patients accessible and smart solutions to assess their food intake and gather dietary information constitute valuable …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 1, 2024 · pp. 1–9 Read article
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Data-Driven Predictive Analytics and Decision- Making in FinTech Using MongoDB and High-Throughput Data Pipelines
Abstract: This paper examines the implementation of MongoDB and high-throughput data pipelines within the financial technology (FinTech) sector to drive data-informed predictive analytics and decision-making. The study focuses on the architectural components, scalability, and challenges of integrating NoSQL databases into real-time data ingestion and analytics pipelines. The transformative potential of these technologies in modern financial systems is highlighted through practical use cases such as fraud detection, credit scoring, and personalized financial …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 1, 2025 · pp. 1–15 Read article
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Navigating the Principles and Practice of Oral Anticoagulant Therapy: A Comprehensive Healthcare Guide
Abstract: Oral anticoagulant therapy plays a critical role in the prevention and treatment of thromboembolic disorders, including atrial fibrillation (AF), venous thromboembolism (VTE), and mechanical heart valve replacement. This research article aims to provide a comprehensive overview of the principles and practice of oral anticoagulant therapy, focusing on the mechanisms of action, pharmacokinetics, clinical indications, monitoring, and management of associated complications. The cornerstone of oral anticoagulant therapy includes vitamin K antagonists …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 15, Issue 1, 2025 · pp. 76–82 Read article
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Pothole Detection utilising Machine Learning: A Review
Abstract: Potholes must be found and fixed quickly in order to maintain infrastructure, maximize transportation systems, and guarantee road safety. Using the Sequential API and the Keras library, this study presents a neural network model for pothole detection. Convolutional layers with ReLU activation, global average pooling, dense layers with dropout, and softmax activation for binary classification make up the model architecture. Image loading, resizing, array conversion, labeling, shuffling, normalization, and one-hot …
Published in Journal of Control & Instrumentation · Vol. 16, Issue 1, 2025 · pp. 35–43 Read article
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Overview AI-Driven Antenna Technologies and Privacy- Preserving Methods for Next-Generation 6G Wireless Systems
Abstract: The next generation of wireless communications, 6G, will be built on the convergence of artificial intelligence (AI) and advanced antenna systems. AI-driven antennas are poised to address the unprecedented requirements for data rate, reliability, adaptability, and ubiquity in future networks. An overview of current advancements in AI-enabled antenna systems for 6G networks is provided in this study. From traditional base station deployments to distributed, cell-free, and user-centric frameworks, it examines …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 13, Issue 1, 2026 · pp. 28–34 Read article
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Intelligent Power Quality Enhancement Strategies for PV-Integrated Smart Distribution Networks: A State-of-the-Art Review
Abstract: The rapid integration of photovoltaic (PV) systems into modern power distribution networks has introduced significant challenges related to power quality. Issues such as voltage fluctuations, harmonic distortion, flicker, and reactive power imbalance arise due to the intermittent and nonlinear nature of solar energy generation. This paper presents a concise literature review of various power quality enhancement techniques employed in PV-integrated networks. Key approaches include the use of active power filters …
Published in International Journal of Electrical Power and Machine Systems · Vol. 4, Issue 1, 2026 · pp. 30–53 Read article
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Innovations in Civil Engineering: Advancing Infrastructure through AI Technology
Abstract: A comprehensive exploration of the intersection of civil engineering and artificial intelligence (AI) technology, highlighting the transformative impact of AI on infrastructure development, management, and sustainability. The journal encompasses a wide array of research articles, case studies, and reviews that demonstrate the integration of AI into various facets of civil engineering, including but not limited to smart infrastructure, predictive maintenance, structural analysis, and urban planning. By showcasing cutting-edge applications and …
Published in Journal of Structural Engineering and Management · Vol. 11, Issue 2, 2024 · pp. 1–11 Read article
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Accelerating Drug Discovery with AI: Transforming the Pharmaceutical Pipeline
Abstract: The revolutionary potential of artificial intelligence (AI) is examined in this essay the pharmaceutical industry, highlighting its application across the drug development lifecycle. Artificial Intelligence, specifically via deep learning models and machine learning (ML) such as GANs, RNNs, and transformers, enhances drug discovery, formulation, toxicity prediction, and clinical trials. It streamlines processes like identification of targets, virtual screening, modelling of structure-activity relationships, and medication repurposing. AI is also employed in …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 2, 2025 · pp. 77–84 Read article
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Wear and Tribological Characteristics of Novel Metal Matrix Composites
Abstract: The development of advanced metal matrix composites (MMCs) with enhanced tribological performance has become increasingly important due to the premature failure of critical engineering components operating under severe wear conditions in automotive, aerospace, marine, defense, and power generation systems. Conventional composites such as Copper–Alumina and Aluminium–Silicon Carbide have demonstrated improved mechanical and wear characteristics; however, their widespread application is often limited by issues including particle agglomeration, non-uniform reinforcement distribution, porosity …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1326–1346 Read article
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Multiphysics Optimization of Polymer–Metal Hybrid Electrode Geometry in Electrostatic Precipitators for Enhanced Particle Collection Efficiency
Abstract: Electrostatic precipitators (ESPs) remain one of the most effective technologies for controlling fine particulate emissions in industrial exhaust systems. However, their performance is strongly influenced by electrode geometry and material characteristics, which govern electric field distribution, corona stability, and particle migration behaviour. In this study, a comprehensive numerical investigation is carried out to optimize electrode geometry using a multiphysics modelling framework, while introducing a novel polymer–metal hybrid design to enhance …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 701–716 Read article
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AI-Driven Inverse Design of Functionally Graded Bio-Nanocomposites for Sustainable High-Barrier Packaging
Abstract: Multilayer plastic packaging realizes high barrier performance through laminated heterogeneous structures, but the heterogeneous structure has severe end-of-life challenges caused by the interfacial incompatibility of materials and the poor recyclability. This study proposes the inverse design of functionally graded PLA-nanoclay composite films by reinforcement learning as a monolithic alternative to traditional multilayer systems. Twin-screw extrusion is designed as a continuous control Markov decision process, and proximal policy optimization (PPO) is …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1547–1564 Read article
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Leveraging Artificial Intelligence (AI) and Digitalization of Community Health Screening in Unani Medicine: Bridging Tradition with Technology – A Perspective Review
Abstract: AI and digitalization bring a great opportunity for reforming and even improvement of traditional healthcare systems in Unani physiology. This review, therefore, observes the important role played by AI and digital health solutions in modernizing health screening and diagnostic procedures in Unani medicine, thereby bridging traditional healing practices with contemporary technological advancement. AI refers to the advantages that may accrue via wearable health devices and telemedicine in real-time monitoring, early …
Published in Journal of AYUSH: Ayurveda, Yoga, Unani, Siddha and Homeopathy · Vol. 14, Issue 2, 2025 · pp. 20–31 Read article
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Machine Learning-Assisted Design and Optimization of Lightweight Polymer Composites for IoT-Enabled Automotive Applications
Abstract: This study aims to develop an integrated machine learning and optimization framework for the intelligent design of lightweight polymer composites suited for IoT-enabled automotive applications. The goal is to enhance material performance while satisfying multiple design constraints such as mechanical strength, thermal stability, and process compatibility. A curated dataset of polymer composite formulations was used to train a Random Forest Regression (RFR) model capable of predicting tensile strength, thermal conductivity, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 12–27 Read article
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Artificial Intelligence and Personalized Learning
Abstract: Artificial Intelligence is transforming education by delivering customized learning pathways that align with each learner’s unique abilities and areas for improvement. Traditional teaching often struggles to meet individual needs; however, AI-powered systems analyse learning patterns in real time, ensuring customized lessons. Virtual tutors and AI chatbots provide instant feedback and 24/7 support, improving comprehension. Gamified learning, combined with augmented and virtual reality, transforms education into a more engaging and enjoyable …
Published in Current Trends in Information Technology · Vol. 15, Issue 3, 2025 · pp. 11–18 Read article
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Automation and new mechanical technologies changing the next industrial age
Abstract: The fast growth of automation and new mechanical technologies is changing the way industries work, making manufacturing and production systems more efficient, accurate, and flexible than ever before. This article looks at how sophisticated mechanical design, robotics, and intelligent automation technologies can work together and how they can improve productivity, lower costs, and make operations more sustainable. To show how mechanical engineers are influencing the next industrial era, we look …
Published in International Journal of Manufacturing and Production Engineering · Vol. 3, Issue 2, 2025 · pp. 18–23 Read article
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Optimizing Glass to Metal Composite Seal Performance: An integrated Approach with Artificial Neural Network, Multiple Regression, and Taguchi
Abstract: Composite materials, particularly glass to metal composites, are critical components in solar receiver tubes, where vacuum leakage can significantly compromise the efficiency of solar plants. This research addresses the technical barriers associated with the development of durable and high-quality glass to metal composite seals. We investigate the principles that can enhance the physical and chemical properties of these composite seals, focusing on the incorporation of TiO2 and MgO nanoparticles into …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 418–435 Read article