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11 articles for “predictive analytics in mining”
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Optimizing Airline Efficiency Using Big Data and Predictive Analytics
Abstract: Recent technological advancements have resulted in the generation of vast volumes of data across industries, including the airline sector, supporting operational control and service quality. Big Data Analytics (BDA) enables organizations to analyze large and complex datasets to derive actionable insights that support informed decision – making and superior operational performance. This review paper systematically analyzes twenty relevant research studies to explore the application of Big Data Analytics (BDA) within …
Published in Journal of Advanced Database Management & Systems · Vol. 13, Issue 1, 2026 Read article
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Data-driven Approaches to Mineral Resource Management Using AI: A Brief Review
Abstract: The role of Artificial Intelligence (AI) in the mineral resource sector has become increasingly significant over the past few years, as industries seek to optimize and modernize their operations. AI encompasses a variety of technologies and techniques, such as machine learning, deep learning, and expert systems, that are now widely used in mineral exploration, resource estimation, and mine management. These AI-driven approaches have brought about a transformative shift, enhancing efficiency, …
Published in International Journal of Minerals · Vol. 2, Issue 1, 2025 · pp. 25–29 Read article
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Predicting Student Placement Readiness: A Machine Learning Approach Using Coding Activities and Multi-Dimensional Performance Indicators
Abstract: In the modern information-driven academic world, identifying student employability and placement preparedness has predicted. be made a part and parcel of academic planning and career. development. This study provides a machine learning-based. structure to evaluate and forecast student placement pre-paredness by combining various performance aspects-academic achieve- ment, coding activity, aptitude and behavioral engage-ment metrics. Multi-source was gathered and preprocessed in the study. student information, such as student records (CGPA, attendance), …
Published in International Journal of Education Sciences · Vol. 3, Issue 2, 2026 Read article
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Analyzing and Predicting Academic Behavior from Peer Pressure Indicators Using Machine Learning
Abstract: The academic achievement of a student is determined by their capability, but also by the companions with whom they associate. Friends can have a positive impact on students' motivation for school, and at times friends are distractions leading to a lack of attention on their school assignments. This particular study focuses on the number and quality of companions students associate with and to what extent that could be used as …
Published in International Journal of Education Sciences · Vol. 3, Issue 2, 2026 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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A Smart Framework that Combines Data Mining and Optimization for Different Applications
Abstract: Blending predictive data mining with metaheuristic optimization has become essential for tackling tough, real-world problems across all kinds of fields. Most existing methods stick to fixed algorithms, each focused on a tiny slice of the puzzle, barely budging when new variables or unpredictability show up—especially with messy, human-generated data. So, here’s the idea: a Unified Metaheuristic and Predictive Data Mining (UMPDM) framework that finally connects adaptive search methods with powerful …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 2, 2026 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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Data-Driven Life Prediction of Fiber-Reinforced Polymer Composites Using IoT Sensing and Machine Learning Algorithms
Abstract: The accurate prediction of fatigue life in fiber-reinforced polymer (FRP) composites remains a major challenge due to their nonlinear, multi-mechanism degradation behavior under variable loading conditions. This study presents a data-driven framework, H-LiProNet, which combines real-time IoT sensing with hybrid machine learning to estimate remaining useful life (RUL) in FRP composites. The proposed system integrates embedded Fiber Bragg Grating (FBG) and acoustic emission (AE) sensors to capture strain and damage …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 116–130 Read article
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Smart City Solutions for Waste Management and Pollution Control
Abstract: Recent trends in the role of artificial intelligence, IoT, and other smart technologies have a critical role toward addressing urban environmental challenges related to air quality and waste management in the context of a smart city. This changes the scope of managing air quality as, with the integration of IoT sensors, big data, and AI, they are able to predict pollution levels through real time monitoring and analysis. These technologies …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 3, Issue 1, 2025 · pp. 11–22 Read article
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Advancements in Battery Storage Technology for Renewable Energy Systems: Improving Reliability and Efficiency of Sustainable Energy
Abstract: Advances in battery storage technology are critical to improved reliability and efficiency of renewable energy systems, underpinning a sustainable energy future. Innovations exist in many different kinds of battery technologies- being developed and tested, and the leading contenders include innovations such as lithium-ion and sodium-ion, and much newer entrants like the solid-state and lithium-sulfur batteries. These developments respond to growing needs for sustainable solutions towards better integration of intermittent renewable …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 17, Issue 2, 2026 Read article
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The Impact of Bacteria and Biostimulants on Crude Oil Breakdown in Loamy Soil
Abstract: This study investigates the influence of bacteria and biostimulants—specifically Bryophyllum pinnatum leaves soaked in both water and ethanol—on the degradation of crude oil in loamy soil. A laboratory-scale bioremediation setup was employed using a batch reactor model and first-order degradation kinetics to assess total petroleum hydrocarbon (TPH) breakdown under controlled conditions. Various analytical tools and procedures, including gas chromatography (Agilent 6890) and microbial media such as nutrient agar and mineral …
Published in International Journal of Pollution: Prevention & Control · Vol. 3, Issue 2, 2025 · pp. 15–22 Read article