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103 articles for “AI forecasting”
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Deep Learning Architectures for Predictive Modeling in Financial Time Series
Abstract: This study investigates the application of deep learning architectures, particularly convolutional neural networks (CNNs), to the challenging task of financial time series forecasting. Financial markets are inherently complex and influenced by a range of factors, making accurate prediction of price movements a difficult problem. In this research, historical financial data including stock prices, volumes, and other relevant indicators are used to train CNN models aimed at capturing the underlying patterns …
Published in Current Trends in Signal Processing · Vol. 15, Issue 3, 2025 · pp. 45–55 Read article
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Revolutionizing Blood Cancer Treatment: Emerging Therapies and Future Perspectives
Abstract: Blood cancer inclusive of leukemia, lymphoma and multiple myeloma poses a significant threat in the world today because of its multifactorial process and its non-amenable to standard therapies. Some of such approaches are immunotherapy, gene-editing technology and targeted small molecule inhibitors that have altered the nature of treatments. CAR T cell therapy is a molecular targeted therapy for cancers and several clinical studies have reported a huge success. Also, the …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 3, Issue 2, 2025 Read article
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A Review on Predicting Wear and Friction of PTFE Composites - Fillers to Machine Learning Models
Abstract: Polytetrafluoroethylene (PTFE) composites, a self-lubricating material with low friction, became an indispensable material in engineering applications where load carrying capacity and wear are crucial. The pure PTFE has poor mechanical strength and wear resistance which can be enhanced by the addition of fillers in appropriate volume fraction. The wear performance is dependent on various factors such as fillers, operating parameters, environmental conditions as well as manufacturing attributes. This makes the …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 114–128 Read article
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Integrating Atmospheric Science: Understanding Greenhouse Gases, Aerosols, and Air Quality Dynamics
Abstract: Atmospheric science investigates the Earth’s atmospheric systems to understand their composition, dynamics, and the implications for climate, weather, and air quality. This review explores five primary areas within the field: atmospheric composition, atmospheric modeling, remote sensing, air pollution, and boundary layer dynamics, highlighting critical challenges and advancements. Rising levels of greenhouse gases (GHGs), including carbon dioxide and methane, continue to drive global warming, while feedback mechanisms—like cloud interactions and surface …
Published in International Journal of Atmosphere · Vol. 1, Issue 1, 2024 · pp. 32–35 Read article
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Machine Learning Based House Price Forecasting
Abstract: This research endeavours to craft a predictive model leveraging machine learning to estimate the market value of houses in Delhi. By integrating Python and its powerful libraries, pandas for data processing, Plot for interactive visualizations, scikit-learn for implementing machine learning algorithms, XGBoost for boosting the model's prediction accuracy, and to evaluate the model's performance cross-validation techniques are used. An interactive user interface is created using a Flask web application to …
Published in Current Trends in Information Technology · Vol. 14, Issue 1, 2024 · pp. 5–11 Read article
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Energy-Efficient Design Strategies for Sustainable Machine Tool Development
Abstract: The design of energy-efficient machine tools is essential for promoting sustainable manufacturing, as it addresses the significant energy consumption and carbon emissions generated by these tools in industrial settings. This study investigates innovative design approaches that enhance energy efficiency, with a focus on lightweight materials, improved drive systems, smart control frameworks, and methods for recovering energy. Implementing lighter structural materials allows machine tools to operate with less force, which in …
Published in Trends in Machine design · Vol. 12, Issue 3, 2025 · pp. 30–34 Read article
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Literature Review and Discussion of Machine Learning Algorithms for Predicting Chronic Kidney Disease
Abstract: Being one of the most serious and most occurring diseases in our era, chronic kidney disease requires a fast and correct diagnosis. The usage of machine learning in medicine has now grown to such a level that it could be a means of diagnosis. The doctor can be the first one to get the ailment by using machine learning classifier algorithms. This has been the data science sector’s new horizons, …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 3, 2024 · pp. 34–39 Read article
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Industry 4.0 and Smart Supply Chains: Transforming Supply Chain Processes for Enhanced Efficiency and Sustainability
Abstract: The fourth industrial revolution, or Industry 4.0, is an important transformation in how industries function via the use of cutting-edge digital technology. Supply chain management is being substantially altered by integrating technologies like blockchain, big data, automated processes, artificial intelligence, and the internet of things into typical operations of the supply chain. With the help of these technologies, corporations can design intelligent supply chains that are more effective, flexible, and …
Published in International Journal of Industrial and Product Design Engineering · Vol. 3, Issue 1, 2025 · pp. 36–41 Read article
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Computational Intelligent Techniques for Enhancing the Capabilities and Efficiency of Smart Water Meters
Abstract: In recent years, the realm of smart water meters has undergone a transformative evolution driven by the integration of computational intelligent techniques. This research work embarks on an exploration of the multifaceted applications of these techniques, delving into their profound impact on enhancing the functionality and efficiency of smart water meters. The convergence of artificial intelligence (AI) and machine learning (ML) algorithms with smart water meters presents a paradigm-shifting opportunity …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 66–74 Read article
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Enhancing Maintenance Decision-Making in Thermal Power Plants Using Generative AI-Based Fault Diagnosis
Abstract: The growing complexity of operation and power consumption of thermal power stations involve the need to have intelligent fault diagnosis systems that can be used to guarantee reliability and safety in operation. In this research, a Generative AI (GenAI)-based hybrid architecture of early fault detection and predictive maintenance is proposed to improve the decision-making process of the maintenance team. The data-driven analytic approach combines methods of data-driven analytics, Generative AI …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 25–33 Read article
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Currents, Waves, and Whirls: An Academic Exploration of Fluid Mechanics
Abstract: Fluid mechanics investigates the behavior of liquids and gases in motion and at rest, revealing the principles that control natural occurrences and engineering systems alike. This article gives an easy review of essential concepts such as fluid characteristics, pressure, flow patterns, and the contrast between laminar and turbulent flow. It explores how fundamental rules, including conservation of mass and energy, impact the transport of fluids across varied settings. Through real-world …
Published in Recent Trends in Fluid Mechanics · Vol. 13, Issue 1, 2026 · pp. 8–13 Read article
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Innovations in Atmospheric Remote Sensing: From Satellites to Lidar and Beyond
Abstract: Atmospheric remote sensing plays a vital role in monitoring and understanding the Earth's atmosphere, providing essential data for climate studies, weather forecasting, and environmental management. This review discusses various remote sensing technologies, including satellites, radiometers, lidar, radar, and GPS radio occultation, each contributing unique capabilities for atmospheric observations. Satellite remote sensing allows for global coverage and continuous monitoring of atmospheric parameters, while ground-based systems enhance localized measurements. Key applications include …
Published in International Journal of Atmosphere · Vol. 1, Issue 2, 2024 · pp. 10–15 Read article
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Bending and Single Edge Notch Bending Test (SENB) Investigation of Natural Fiber- Reinforced Epoxy Composites using Machine Learning
Abstract: The present study aims to determine the behavior of hemp fiber-reinforced epoxy composites in terms of bending behavior and fracture toughness under bending load resembles the substitutive behavior of existing synthetic composites. The fabrication was carried out by hand lay-up assembly of hemp fiber with Lapox-12 epoxy resin volume fraction of 60:40 fiber: matrix volume. Flexural testing revealed an average strength of 93.5 ± 2.8 MPa and SENB testing revealed …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 59–69 Read article
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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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Digital Transformation of Urban Infrastructure with the Help of AI Guardians
Abstract: The construction industry continues to face challenges related to quality control, safety protocols, and meeting project deadlines. These issues often result in significant cost overruns and project delays. Traditional inspection and site management approaches rely heavily on manual work and individual judgment. As a result, human errors can easily occur, and these methods provide only limited snapshots of site conditions over time. This paper presents a comprehensive framework that uses …
Published in Recent Trends in Civil Engineering & Technology · Vol. 16, Issue 1, 2026 · pp. 16–25 Read article
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ANN Approach to Forecasting the Strength of Nano Silica Incorporated Geopolymer Composite
Abstract: Coal and steel industry by-products, such as fly ash (FA) and blast furnace slag (GGBS), have gained significant attention as precursors for geopolymer concrete (GPC) due to their high aluminosilicate content, offering a sustainable alternative to conventional cement. Nano silica (NS), recognized for its exceptional pozzolanic activity and ability to refine microstructure, has shown potential to enhance the mechanical and durability properties of GPC. This study investigates the influence of …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 267–278 Read article
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Predictive Analytics for Student Well-Being and Occupational Success
Abstract: The integration of predictive analytics into higher education has significantly transformed institutional decision-making processes. However, prevailing implementations remain predominantly performance-centered, focusing on dropout prediction and grade forecasting rather than holistic developmental outcomes. Concurrently, higher education systems worldwide are confronting escalating concerns regarding student mental health, disengagement, career uncertainty, and labor market volatility. These intersecting challenges necessitate a broader theoretical reconceptualization of predictive analytics—one that integrates psychological well-being and long-term occupational …
Published in International Journal of Education Sciences · Vol. 3, Issue 1, 2026 · pp. 155–163 Read article
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Harnessing Machine Learning for Stock Movement Prediction: A Review of Current Approaches
Abstract: Stock price prediction is a crucial task in financial analysis, aiding investors and traders in making informed decisions. This study investigates the use of deep learning methods, particularly Long Short-Term Memory (LSTM) networks, for predicting stock prices based on historical market data. The dataset, sourced from Yahoo Finance, consists of time-series stock price data, which is preprocessed, feature-engineered, and visualized to improve prediction accuracy. The model's performance is assessed using …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 2, 2025 · pp. 29–40 Read article
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CampusX: Empowering College Selection with 3D insights using machine Learning approach.
Abstract: CampusX redefines college selection with dynamic 3D insights, empowering students to navigate campuses virtually. Utilizing cutting-edge machine learning and visualization techniques, it transforms static data into interactive experiences. Personalized comparisons enable informed decision-making, while predictive analytics forecast future campus developments. With a user-centric interface and robust privacy protocols, CampusX ensures seamless exploration and data security. This innovative platform bridges the gap between prospective students and their ideal educational environments, revolutionizing …
Published in International Journal of Optical Innovations & Research · Vol. 2, Issue 2, 2024 · pp. 23–29 Read article
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A Detailed Survey of Machine Learning Applications, Methods, and Future Prospects in Agriculture
Abstract: Agriculture is undergoing a digital transformation driven by machine learning (ML) and artificial intelligence. The integration of ML techniques with data from sensors, drones, satellites, and IoT devices has enabled precision agriculture, early disease detection, optimized resource use, and improved yield prediction. This paper presents a comprehensive review of machine learning applications in modern agriculture, covering key areas such as crop monitoring, soil analysis, irrigation scheduling, pest, and disease detection, …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 15, Issue 1, 2026 · pp. 39–45 Read article