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712 articles for “data patterns”
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Research Survey of Data Mining with Processing in Different fields for Next Research Directions
Abstract: Data mining (DM) is a method used for mines the different category of related data in different research fields. This is a set of different techniques like classification, clustering, prediction, outlier analysis; decision making, regression etc used for gain the knowledge for intelligence computing. In this review, explain the different research papers, architecture with components of DM, processing of DM and applications of DM in various fields for next research …
Published in Journal of Computer Technology & Applications · Vol. 11, Issue 2, 2020 · pp. 5–9 Read article
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Big Data, Big Impact: The Role of Analytics in Modern Business
Abstract: In modern business, “Big Data” signifies the vast amount of data collected from various sources, and “Big Data Analytics” refers to the process of analyzing this data to extract valuable insights, enabling companies to make data-driven decisions, optimize operations, better understand customers, and ultimately gain a competitive edge by identifying trends, patterns, and opportunities that might otherwise be missed. This study analyzes large datasets, by which businesses can gain deeper …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 2, 2025 · pp. 01–11 Read article
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Enhancing Healthcare Record Modeling Through Graph Convolutional Networks: Overcoming Challenges and Advancing Data Management and Analysis
Abstract: Modeling healthcare records data as a graph database presents various challenges due to the complex nature of healthcare information and its interconnectedness. In this research endeavor, our primary objective is to pinpoint the major obstacles within this field and present potential remedies to tackle them effectively. By leveraging machine learning techniques, we aim to enhance the efficiency and accuracy of healthcare record modeling, facilitating better data management and analysis. One …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 10, Issue 2, 2023 · pp. 39–50 Read article
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From Trace to Truth: Integrating Forensic Science, Analytical Chemistry, Medical Evidence and Artificial Intelligence in Modern Criminal Investigation
Abstract: Modern criminal investigations are inherently interdisciplinary, integrating medical research, forensic science, analytical chemistry, and artificial intelligence (AI) to transform hazy traces into reliable, legally recognised evidence. This study examines the ways in which different domains collaborate across the whole investigation process, ranging from judicial review, laboratory analysis, and computer processing to crime scene management and evidence retrieval. This research is based on a thorough review of scholarly literature and a …
Published in Research and Reviews: A Journal of Toxicology · Vol. 16, Issue 2, 2026 Read article
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Improving Supply Chain Resilience through Predictive Analytics and Real-Time Data Integration
Abstract: Demand forecasting has under gone major changes because to the incorporation of automated analytics into supply chain management (SCM), which has improved company productivity, accuracy, and responsiveness. Central to this transformation is the application of machine learning (ML), which enables the analysis of large and complex datasets to identify patterns, detect trends, and generate precise forecasts. Conventional methods for predicting frequently rely on linear models and historical sales data, which …
Published in International Journal of Industrial and Product Design Engineering · Vol. 3, Issue 2, 2025 · pp. 8–17 Read article
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A Latest Approach for Crime Rate Prediction and Analysis by Using the Clustering and Machine Learning Algorithm
Abstract: In our daily life, the collection and analysis of crime-related data is uncertain from a security perspective. Crime rate forecasting and analysis is a way of identifying and analyzing crime patterns in crime data contained in a crime database. Our system predicts what criminal activity occurs in everyday life in various parts of the world. Through the utilization of machine learning and data mining algorithms, it is possible to forecast …
Published in Journal Of Network security · Vol. 11, Issue 2, 2023 · pp. 32–42 Read article
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Effective Road Safety for Future Cities: Case Study Using GIS and Remote Sensing for Accident Analysis in Navi Mumbai
Abstract: Urban transportation systems face significant challenges due to rapid population growth and development. This study delves into the enhancement of road safety in Navi Mumbai by employing Geographic Information System (GIS) and Remote Sensing (RS) techniques. The escalating rate of vehicular accidents in Navi Mumbai presents a pressing concern. This research investigates accident data and traffic patterns, identifying vulnerable areas prone to accidents and congestion. By conducting spatial analysis using …
Published in Journal of Remote Sensing & GIS · Vol. 14, Issue 3, 2023 · pp. 9–21 Read article
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An Overview on AI-Driven IoT Based Decision Making in Climate change Study: KSK approach in Climate Change Study
Abstract: As the Earth’s climate enters a state of unprecedented volatility, the traditional methods of ecological observation—characterized by delayed reporting and fragmented data—are no longer sufficient. This study investigates the paradigm shift toward AI-driven IoT (KSK Approach)-based decision-making frameworks as the primary frontier in climate science. By deploying a "planetary nervous system" of interconnected sensors—measuring everything from soil moisture in the Sahel to glacial melt rates in the Arctic—we generate a …
Published in International Journal of Climate Conditions · Vol. 3, Issue 1, 2026 · pp. 1–10 Read article
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A Survey on Different Clustering Algorithms with Their Major Features
Abstract: Data mining techniques make it possible to search large amounts of data for characteristic rules and patterns. Clustering is used to organize data for efficient retrieval. The aim is to create homogeneous subgroups of examples. The individuals in the same subgroup are similar; the individuals in different subgroups are as different as possible. One of the problems in clustering is the identification of clusters in given data. A popular technique …
Published in Journal of Web Engineering & Technology · Vol. 1, Issue 3, 2014 · pp. 19–24 Read article
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A Comprehensive Review of Machine Learning and Explainable AI Techniques for Disease Prediction Systems
Abstract: Large amounts of diverse medical data have been produced because of the quick development of digital healthcare systems, offering substantial chances to use machine learning methods for clinical decision support and illness prediction. By identifying intricate patterns in clinical data, machine learning-based models have shown great promise in early disease detection, risk assessment, and personalised healthcare. However, issues with transparency, interpretability, and reliability have been brought up by the growing …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 1, 2026 · pp. 20–28 Read article
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Implementation of B2C Mobile Shopping
Abstract: With the improvement of web innovation, system assumes an indispensable part in individuals' day by day life. In not so distant future, People's life and work will be exceptionally subject to data innovation. E-business is currently motivating nearer to individuals' life on everyday premise as the development of data innovation. Experiencing web history and its present development patterns, we can trust data innovation significantly changed our life and the method …
Published in E-Commerce for Future & Trends · Vol. 3, Issue 2, 2016 · pp. 18–20 Read article
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Review on Weather Events Forecasting Using Data Mining Algorithms
Abstract: Weather events forecasting is the most imperious and stimulatingfunctioning responsibilities supported by meteorological departments worldwide. Amongst all weather events, rainfall plays the most authoritative role in the life of human beings. Human society to a great level depends upon its frequency at various scales. Data mining is a process that mechanically abstracts useful patterns from a given data set. Thecommon algorithms and techniques for rain forecasting like Artificial Neural Networks …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 5, Issue 1, 2018 · pp. 12–22 Read article
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A Review of AI-Based Intrusion Detection Systems for Mobile Ad Hoc Networks (MANETs)
Abstract: Mobile Ad Hoc Networks (MANETs) comprise wireless networks that lack any conventional infrastructure . Their chief features include highly changing network topologies, lack of centralized administration, and open nature of communication, which collectively result in making MANETs of the wireless kind very susceptible to a diverse range of cyber-attacks like blackhole, greyhole, wormhole, flooding, Sybil and denial-of-service (DoS) among others. Conventionally, Intrusion Detection Systems (IDS) relying on static rule-based methods …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article
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Remote Sensing and GIS-Based Approaches for Soil Salinization Assessment: A Comprehensive Review
Abstract: Soil salinization, a critical environmental challenge, significantly impacts land productivity, agricultural yields, and contributes to desertification, particularly in arid and semi-arid regions. Early detection and effective management of soil salinity are essential for sustainable agriculture and land management. Remote sensing (RS) and geographic information systems (GIS) have emerged as indispensable tools for mapping, monitoring, and analyzing soil salinity over vast areas. RS provides multi-temporal and multi-spectral data that helps identify …
Published in Journal of Remote Sensing & GIS · Vol. 15, Issue 3, 2024 · pp. 29–38 Read article
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Artificial Intelligence for Tracking Cognitive Deviation in Aging Populations: A Comprehensive Review of Techniques, Challenges, and Ethical Concerns
Abstract: Population aging is accelerating worldwide, and with it the burden of cognitive health conditions such as mild cognitive impairment (MCI), Alzheimer’s disease (AD), and dementia. Detecting and monitoring cognitive change early is central to timely intervention, yet conventional diagnostic tools often miss the subtle signals that appear before overt symptoms. Artificial intelligence (AI) has emerged as a promising complement to clinical assessment because it can work through high-dimensional data and …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 2, 2026 · pp. 27–37 Read article
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APPLICATION OF ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY
Abstract: The application of artificial intelligence (AI) in medicine, especially through machine learning (ML), is revolutionizing new-age drug discovery research. AI is found as an efficient and powerful tool to narrow the gap between disease detection and developing and identifying potential therapeutic agents for a cure. This review provides a summary of the latest developments in AI and its potential application in drug discovery for untreatable diseases. The review also examines …
Published in Emerging Trends in Chemical Engineering · Vol. 12, Issue 3, 2025 · pp. 22–29 Read article
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Predictive Analytics and Adaptive Learning: A Machine Learning Framework for Reducing Learning Gaps
Abstract: Most contemporary digital learning environments encounter persistent challenges when it comes to accurately identifying students who are at-risk of academic underperformance. These challenges often arise due to limited visibility in learners’ engagement levels and gaps in conceptual understanding, particularly during the early stages of a course. To address this issue, the present study proposes an early prediction framework that leverages comprehensive student-related data through the application of machine learning techniques. …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 16–21 Read article
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Data Stream Mining
Abstract: A data stream can be considered as an ordered sequence of data items, where the elements of the series continuously arrive as time progresses. Data stream mining is the procedure of extracting knowledge structures from such continuous, rapid data records. Mining data streams nurtures new problems for the data mining community regarding how to mine continuous high-speed data items that you can only have one look at. Due to this …
Published in Recent Trends in Programming languages · Vol. 5, Issue 1, 2018 · pp. 1–5 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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House Price Estimation Using Linear Regression: A Machine Learning Perspective
Abstract: House price prediction plays a crucial role in the real estate industry, helping buyers, sellers, and investors make well-informed decisions. Accurate estimation of property values enables stakeholders to assess market trends, plan investments, and minimize financial risks. This study focuses on the application of linear regression, a fundamental and widely used machine learning algorithm, to predict house prices based on multiple influencing factors. These factors include location, property size, number …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 1, 2026 · pp. 21–29 Read article