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45 articles for “Time series analysis”
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Time-Series Analysis of Uber Ride Trends
Abstract: This article provides an in-depth analysis of Uber's data analytics, clarifying its crucial role in revolutionizing the transportation industry. It provides vital insights for stakeholders by carefully examining rider patterns, driving behaviors, and market dynamics. This study provides a thorough knowledge of Uber's impact on urban transportation and socio-economic landscapes by combining existing research and proposing fresh approaches. Uber is a digital company that has made multiple attempts to leverage …
Published in Current Trends in Signal Processing · Vol. 14, Issue 1, 2024 · pp. 34–38 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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Forecasting Commodity Prices Using Deep Learning Techniques: An Empirical Evidence from India
Abstract: Commodity price forecasting is instrumental in financial markets, providing framework for investment choices and risk management practices. Traditional models, including statistical and machine learning approaches, have limitations in capturing the nonlinear and volatile nature of commodity prices. Deep learning (DL) techniques have emerged as promising alternatives, leveraging advanced neural networks to enhance predictive accuracy. This study presents a thorough and comprehensive examination of deep learning applications in commodity price prediction, …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 08–12 Read article
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Signal Drift Compensation in Polymer-Based Wearable Biosensors Using Data Processing Techniques
Abstract: Polymer-based wearable biosensors have emerged as promising platforms for continuous physiological monitoring due to their mechanical flexibility, low operating voltage, and compatibility with soft biological interfaces. However, their long-term deployment remains challenging because of signal drift caused by polymer ageing, hydration–dehydration cycles, ionic trapping, and environmental variations. These effects introduce baseline fluctuations and sensitivity degradation, which compromise the reliability and interpretability of physiological measurements. This study proposes a data-processing–driven framework …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 197–207 Read article
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Rainwater Measuring Algorithm in O(1) Time Complexity
Abstract: The Rain Terraces Time Complexity Data Structure Algorithm (RTTCDSA) introduces a novel method for managing temporal data efficiently, inspired by the natural flow of rainwater on terraced landscapes. This study presents the conceptual framework and implementation details of RTTCDSA, which leverages principles of temporal dynamics and landscape morphology to organize and query temporal data with optimal time complexity. RTTCDSA employs a hierarchical structure akin to terraced landscapes, facilitating rapid traversal …
Published in International Journal of Data Structure Studies · Vol. 2, Issue 1, 2024 · pp. 26–32 Read article
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Study of a Western Disturbance of 2023 Using Satellite-Based Observation, Reanalysis Data, and Numerical Simulation
Abstract: Western Disturbances (WDs) are synoptic-scale, extratropical storm systems that influence winter precipitation across northwest India. This study focuses on a specific WD event that occurred from 24– 25 March 2023, affecting Jammu & Kashmir, Himachal Pradesh, Uttarakhand, and Punjab. The analysis integrates satellite observations, ERA-5 reanalysis data, and simulations from the Weather Research and Forecasting (WRF) model to evaluate the model's performance. The novelty of this study lies in its …
Published in Journal of Remote Sensing & GIS · Vol. 16, Issue 3, 2025 · pp. 16–38 Read article
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Topology and Geometry in Data Science: Persistent Homology and Beyond
Abstract: In recent years, the interplay between topology, geometry, and data science has gained substantial momentum, offering powerful frameworks to analyze and interpret complex datasets. Traditional statistical and machine learning methods often rely on linear or metric- based assumptions, which may fail to capture the intrinsic structure of high-dimensional or nonlinear data. In contrast, topological and geometric methods provide shape-oriented, scale- invariant tools that focus on the continuity, connectivity, and global …
Published in Recent Trends in Mathematics · Vol. 1, Issue 2, 2024 · pp. 21–27 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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Stock Market Analysis Using Data Science
Abstract: Stock market prediction using data science has become a popular area of research and application in recent years. This is because the stock market is a complex system with many variables and factors that affect its behavior, making it difficult to predict with certainty. The stock market has always been the aggression of buyers and sellers of stocks, therefore in the global finance market, stock trading is one of the …
Published in E-Commerce for Future & Trends · Vol. 11, Issue 1, 2024 · pp. 1–4 Read article
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Sky Scanners: Using satellite remote sensing to figure out what Earth is like
Abstract: Satellite remote sensing has changed the way we look at, study, and learn about the Earth changing systems. Orbiting sensors take data from many different spectral bands, giving us constant, large-scale information about land, oceans, and the atmosphere. This study discusses the fundamental concepts of satellite remote sensing, including the various types of sensors, methods for data acquisition, and techniques for interpreting images. It talks about important uses like monitoring …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 1, 2026 · pp. 22–33 Read article
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Study of Social Trends Prediction Using AI
Abstract: AI (Artificial Intelligence) has fundamentally changed the ability to analyze social trends by using large datasets to develop predictions about human behavior, public sentiment, and global events. Using methodologies such as Natural Language Processing (NLP), Time-Series Forecasting, and Graph-Based Social Network Analysis, AI is able to find hidden correlations in a variety of available datasets, from social media to economic indicators to public records, and fundamentally changes decision-making based on …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 19–29 Read article
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Time Series Methods in Meteorology: A Review of Predictive Models and Applications
Abstract: The accurate prediction of time series data holds substantial significance in various fields, enabling informed decision-making and resource optimization. In this study, temperature variations over time are predicted using the Autoregressive Integrated Moving Average (ARIMA) model. Reliable temperature projections are more important now than ever because of climate change and its effects. For time series prediction problems, the ARIMA model—which is well-known for its ability to capture temporal dependencies in …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 13, Issue 2, 2024 · pp. 35–46 Read article
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Development of Novel Polymeric Articulating Papers for Enhanced Occlusal Contact Assessment in Dentistry
Abstract: Traditional articulating papers, a mainstay in occlusal analysis, often exhibit limitations in consistency and difficulty with quantitative data analysis. This study explores the development of novel articulating papers utilizing advanced polymeric materials. These novel papers aim to address the shortcomings of traditional options by potentially improving: (1) sensitivity and resolution for capturing occlusal contacts, (2) consistency and reproducibility of contact readings, and (3) durability and reusability. The successful development of …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 1004–1011 Read article
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Impact of Urbanization on Biodiversity Hotspot: A Case of Bhubaneswar City
Abstract: Urbanization has contributed to pollution and generation of waste heat leading to changes in the urban heat balance thereby influencing its microclimate. Urban regions confront heightened heat wave conditions due to urban heat island (UHI) impact, which is a result of anthropogenic effects on both surface and atmospheric temperature patterns relative to the natural environment. The investigation was carried out in a 20-km radius around the city of Bhubaneswar. The …
Published in Journal of Remote Sensing & GIS · Vol. 15, Issue 3, 2024 · pp. 20–28 Read article
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AI-Driven Exam Grading, Percentile Calculation, and Plagiarism Detection System for Educational Integrity
Abstract: The influence of artificial intelligence (AI) on academic evaluation has become increasingly significant, particularly in areas such as automated grading, large-scale content analysis, and plagiarism detection. These technologies provide educators with rapid processing, consistent scoring, and timely feedback that can support both teaching and learning. However, alongside these advantages, serious concerns have emerged regarding the reliability and fairness of AI-driven assessments. The growing presence of AI-generated content has further complicated …
Published in Current Trends in Information Technology · Vol. 16, Issue 1, 2025 · pp. 07–12 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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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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Exploring GeoAlert: An IoT Approach to Weather Station Networks
Abstract: The innovative project "Geo-Alert: IoT Based Weather Station" uses Internet of Things, or IoT, technologies to monitor and respond to environmental circumstances, such as flood hazards, weather variations, and seismic events. This system sends real-time data to the Blynk IoT cloud, enabling seamless remote monitoring and analysis. It does this by utilising a combination of specialised sensors, such as vibration sensors for earthquake detection, DHT11 and MQ series sensors for …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 13, Issue 1, 2024 · pp. 27–36 Read article
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Database-Driven Energy Management in Electric Vehicles
Abstract: With the growing concern over environmental pollution, there is an increasing demand for sustainable and eco-friendly technologies. Among these, electric vehicles (EVs) have emerged as a promising alternative to conventional fossil-fuel-based transportation. However, as EV adoption accelerates, efficient energy management becomes critical to enhance vehicle performance, extend battery life, and ensure overall system reliability. This research presents a Database-Driven Energy Management System (DBEMS) that leverages real-time data from EV components …
Published in Journal of Automobile Engineering and Applications · Vol. 12, Issue 3, 2025 · pp. 19–24 Read article
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Development and Characterization of Rubber Composites using E-Waste Residue as Functional Filler
Abstract: In the present study, residue generated during the recycling of end-of-life printed circuit boards (PCBs) was utilized as a functional filler in natural rubber to fabricate eco-friendly composites using mixing and molding techniques. Chemical analysis of the residue revealed the presence of several metals, including copper, iron, lead, tin, and zinc. The presence of these metals highlights the need for proper recycling and safe management of PCB residues, as their …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 512–523 Read article