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11 articles for “Financial time series”
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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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Stock Market Prediction Using Machine Learning: Techniques, Challenges, and Future Directions
Abstract: The continuous advancement of machine learning (ML) technologies has significantly transformed the field of financial forecasting, particularly in the area of stock market prediction. The ability to accurately forecast stock price movements and market trends plays a crucial role in supporting informed investment strategies and effective risk management. This paper provides a comprehensive review of recent developments in the application of ML techniques for predicting stock market behavior. It classifies …
Published in E-Commerce for Future & Trends · Vol. 13, Issue 1, 2026 · pp. 10–16 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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Time Series Forecasting Based on PyAF and fbProphet
Abstract: Time series forecasting is the technique of predicting future events using previous data. Time series data includes information that is collected and recorded at regular intervals, such as daily stock prices, monthly sales figures, or hourly temperature readings. The purpose of time series forecasting is to use previous data to create accurate forecasts about the future values of a given variable. This can be beneficial for a range of applications, …
Published in International Journal of Information Security Engineering · Vol. 1, Issue 1, 2023 · pp. 32–36 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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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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New Design Formulae for Safety and Precision in the Fatigue Engineering of Mechanical Components and Structures
Abstract: This paper introduces two new formulae, termed the Nori Fatigue Formulae, for determining the maximum allowable fatigue stress in mechanical components and structures with significant stress concentrations. These formulae will eliminate the usage of code-sensitive safety factors along with other factored values from the entire mechanical design engineering work, ranging from a safety pin to spacecraft. The first formula gives the maximum allowable fatigue stress in tension, and the second …
Published in Trends in Mechanical Engineering & Technology · Vol. 16, Issue 1, 2026 · pp. 6–24 Read article
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A Study of climate change and its impact on tourism
Abstract: Tourism is clearly linked to climate, as vacationers wish spending time in open-air and travel to delight in the sky or countryside. It is then amazing that the tourism works pays slight thoughtfulness to climate and climatic transformation. Numerous of investigations on tourism and climate change is, still, beginning to raise. Though it is a generally known statement that climate change can adversely effect on tourism sector and shake the …
Published in International Journal of Environmental Planning and Development Architecture · Vol. 2, Issue 1, 2024 · pp. 1–10 Read article
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A Study to Assess the Prevalence of Self-medication and Its Associated Factors Among Pregnant Women in Selected Tertiary Care Teaching Hospital at Kuppam, Chittoor District, Andhra Pradesh
Abstract: Self-medication, the practice of using medications without a doctor's prescription, is a growing global public health issue, particularly in resource-limited settings. In pregnancy, self-medication can pose serious risks, including misdiagnosis, incorrect dosages, drug interactions, and prolonged use. This study aimed to assess the prevalence of self-medication, and the factors associated with it among pregnant women at a tertiary care teaching hospital in Kuppam, Chittoor district, Andhra Pradesh. A descriptive cross-sectional …
Published in International Journal of Midwifery Nursing And Practices · Vol. 2, Issue 2, 2024 · pp. 41–48 Read article
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Innovations in Sericulture: A Review of IoT and AI-Based Monitoring Systems
Abstract: Sericulture is a science which deals with the rearing of silkworms and production of silk. In India most of the rural livelihood is sericulture and is the base for financial, social, political, and intellectual advancements and upliftment since. Silk is called the queen of textiles due to its glittering luster, softness, elegance, durability, and tensile properties. There exist several commercial species of silkworms, yet the commonly used one is bombyx …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 3, Issue 1, 2025 · pp. 14–18 Read article
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Literature of Green Architecture
Abstract: The term green architecture implies the use of environmental principles as the basis when designing buildings. In this perspective, the architecture of the future aims at synthesizing nature, technology, science, and even the imagination in the construction industry. The following paper explores green architecture on a generalized basis, which discusses its basic features, practices and the repercussions of green design on environmental sustainability. A key component of eco-architecture is to …
Published in International Journal of Urban Design and Development · Vol. 2, Issue 1, 2024 · pp. 47–53 Read article