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293 articles for “Automated machine learning”
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Automated Machine Learning System for Model Selection and Hyperparameter Optimization
Abstract: The proliferation of machine learning applications in various scientific and industrial domains has given rise to an urgent need for developing principled, automated techniques for optimal architecture selection and hyperparameter tuning for machine learning models without human expert intervention. In this paper, we introduce the Automated Machine Learning System for Model selection and hyperparameter Optimization (AMLSMO)—a state-of-the-art, all-encompassing AutoML system that combines the power of meta-learning-based warm-starting, Bayesian Optimization with …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 · pp. 15–23 Read article
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Cybersecurity in Web Automation: A Machine Learning Approach to Lightweight Intrusion Detection
Abstract: Launch-Attack is a lightweight and practical threat-detection framework designed specifically for smaller web-automation environments, including setups that rely on tools such as Selenium. Rather than aiming to replace large enterprise-grade security platforms, the framework focuses on offering an accessible option for developers, testers, and researchers who need real-time monitoring without the heavy resource demands of traditional systems. The model relies on machine-learning techniques implemented through Scikit-learn, enabling it to detect …
Published in Journal of Web Engineering & Technology · Vol. 13, Issue 1, 2026 · pp. 34–40 Read article
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Automated Intelligence, Machine Learning, and Big Data in Education: A Practical Framework, Synthetic Demonstration, and Deployment Guidance
Abstract: Artificial intelligence (AI), machine learning (ML), and big-data methods are increasingly used to improve educational decision making through personalization, early-warning systems, scalable feedback, and operational analytics. This manuscript proposes a practical end-to-end framework for educational AI/ML projects, covering problem definition, data engineering, modeling, evaluation, intervention design, and responsible governance. To provide a complete and reproducible template without exposing sensitive student data, we present a synthetic demonstration study that mirrors typical …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 Read article
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Machine Learning Pipelines: A Survey on Automation, Scalability, and Deployment Strategies
Abstract: Machine learning (ML) has become a critical enabler of intelligent applications across domains, requiring robust, efficient, and scalable deployment workflows. This review paper provides an in-depth overview of machine learning pipelines, emphasizing three key dimensions: automation, scalability, and deployment methodologies. It begins by exploring automation techniques that reduce manual effort in data ingestion, preprocessing, model selection, and hyperparameter tuning. Tools such as AutoML, TFX, and workflow orchestration platforms are examined …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 2, 2025 · pp. 17–28 Read article
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Automating Compiler Optimization: A Machine Learning Approach
Abstract: This study reports on an ML-based approach to compiler optimization, complementing traditional optimization methods that rely strongly on hand-tuned settings. Compiler optimization plays a key role in performance-speedup and energy optimization of complex contemporary software systems. However, the traditional approach to optimizer settings involves laborious, error-prone, and scale-insensitive human-in-the-loop intervention, especially in the complex and high-demand environments in which today's computing application thrives. By integrating RL and GA, we can …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 1, 2025 · pp. 12–16 Read article
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Enhanced Multimodal Disease Prediction Using Hybrid Ensemble Learning and AutoML Techniques
Abstract: The integration of hybrid ensemble learning and automated machine learning (AutoML) is revolutionizing disease prediction by addressing the complexity, imbalance, and high dimensionality inherent in medical datasets. This paper proposes an advanced pipeline that combines diverse ensemble learning models with AutoML-based optimization to predict chronic diseases such as kidney diseas-e, Parkinson’s disease, and lung cancer. Publicly available datasets from UCI and PhysioNet repositories were preprocessed using outlier removal, normalization, and …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 · pp. 10–20 Read article
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IoT and Machine Learning in Green Smart Home Automation and Green Building Management
Abstract: AbstractInternet of things (IoT) is a developing concept, which aims to associate billions of devices with each other. The IoT devices sense, assemble, and transfer important information from their environments. This exchange of very large amount of information among billions of devices makes an enormous energy need. The radical growth in urbanization over the last few years needs sustainable, proficient, and smart clarifications for transport, governance, environment, quality of life, …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 10, Issue 3, 2019 · pp. 8–36 Read article
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A Review of Automated Pomegranate Disease Detection and Classification Using Machine Learning
Abstract: The abstract outlines a research study focused on developing an automated system for detecting and classifying diseases that affect pomegranate fruits. Pomegranates, like many other crops, are vulnerable to several types of diseases that appear as visible colored spots on the fruit’s surface. These visible symptoms, such as lesions or discoloration, can significantly impact the fruit’s quality, market value, and yield. Therefore, timely and accurate identification of such diseases is …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 1, 2026 · pp. 01–13 Read article
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Machine Learning Based Smart Aquaponics Farming System
Abstract: For many years, researchers have been studying nutrient management in aquaponic systems. Most have concentrated on adequate nutrition control in an aquaponic setup, but there has been relatively little study on commercial scale applications. For plant growth, it is necessary to measure the level of nutrients present in the soil mixture. In our model, the input data was sourced on some interval of time basis from three commercial aquaponic farms. …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 10, Issue 1, 2022 · pp. 30–37 Read article
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Automatic Chest X-ray Report Generation Using Machine Learning
Abstract: In this study, a deep neural network is suggested for the automatic creation of precise radiologist reports from chest X-ray pictures. The proposed network responds to the need for medical image captioning by learning to extract key features from the image and creating tag embeddings for each patient's X-ray images. Medical image captioning demands coherence and high accuracy in identifying abnormalities and extracting information. For a finer representation, the network …
Published in Journal of Instrumentation Technology & Innovations · Vol. 13, Issue 1, 2023 · pp. 29–39 Read article
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Machine Learning-Assisted Design and Optimization of Lightweight Polymer Composites for IoT-Enabled Automotive Applications
Abstract: This study aims to develop an integrated machine learning and optimization framework for the intelligent design of lightweight polymer composites suited for IoT-enabled automotive applications. The goal is to enhance material performance while satisfying multiple design constraints such as mechanical strength, thermal stability, and process compatibility. A curated dataset of polymer composite formulations was used to train a Random Forest Regression (RFR) model capable of predicting tensile strength, thermal conductivity, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 12–27 Read article
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Innovative Secure Public Ration Distribution Using Machine Learning
Abstract: The proposed system aids in controlling malpractices that are present in ration shops by replacing manual work with automatic systems based on machine learning. The ration distribution system is automated by using machine learning algorithms. Once the consumer is validated by password, the system will provide the customer information like how many people’s rations are permitted to their account, how many rations will be provided, and on which day the …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 12, Issue 3, 2024 · pp. 25–30 Read article
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Evaluation of Machine Learning Classifiers for Sentiment Analysis
Abstract: Sentiment in social media refers to users’ emotions and opinions through their posts and interactions. Sentiment analysis (SA) refers to relating and classifying the sentiments expressed as engagement and interactions between users. When analyzed, tweets frequently produce a large source of clustered data. These data help determine people’s opinions about a variety of motifs. Thus, this study presents an Automated Machine Learning (ML) Sentiment Analysis Model to detect media sentiment. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 141–154 Read article
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Combining Unstructured and Structured Clinical Data in a Hybrid Transformer Model to Enhance Cardiovascular Analytics and Clinical Decision- Making
Abstract: Since cardiovascular disease (CVD) continues to be a major global cause of morbidity and mortality, early and accurate risk prediction is essential for prompt intervention and individualized treatment. This study introduces a new hybrid transformer-based model that combines unstructured clinical narratives, structured data, and customized lifestyle characteristics. A comprehensive understanding of disease progression is made possible by the model's ability to capture contextual, temporal, and patient- specific insights through the …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 1, 2026 · pp. 30–37 Read article
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Answer Checking System Using Artificial Intelligence and Machine Learning: A Review
Abstract: Automatic answer checker software that evaluates and scores written responses in a manner comparable to that of a human. This software programme is designed to evaluate subjective responses provided in an online test and to award points to the user after the answer has been validated. For the sake of the system, you must save the initial response. The administrator is given access to this resource. The system's admin can …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 1, Issue 1, 2023 · pp. 8–13 Read article
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3D Printing for Polymer Science Visualization
Abstract: The burgeoning field of 3D printing offers exciting possibilities for various scientific disciplines. This paper explores the potential integration of 3D printing technology within the realm of polymer analysis. While the core focus of memory forensics investigations lies in digital forensics, the concept of 3D printing complex data structures presents intriguing possibilities for the visualization and communication of findings in polymer science. Here, we propose a future research avenue where …
Published in Journal of Polymer & Composites · Vol. 12, Issue 4, 2024 · pp. 96–101 Read article
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Designing Aspects and Recent Advances in Digital Holographic Microscopy
Abstract: Recent advances in Digital Holographic Microscopy have been discussed in this paper, besides throwing some light on the designing aspects of optical components like beam splitter and neutral density filter for the optimization of system performance. Some important related subtopics like spectral resolution of digital holograms, and Fourier-synthesis holography have been technically discussed. The optimization of acoustical holographic components for use in renewable energy production is presented in this study. …
Published in Research & Reviews : Journal of Physics · Vol. 14, Issue 2, 2025 · pp. 06–18 Read article
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Emerging Role of Drone Technologies in Environmental Research: Trends, Applications, and Future Directions
Abstract: Unmanned aerial vehicles (UAVs), commonly called drones, have rapidly transformed environmental research and management over the past decade. Their flexibility, improving sensor payloads, and ability to collect high-resolution spatial and temporal data make them powerful tools across disciplines — from biodiversity monitoring and precision agriculture to water quality assessment and disaster response. UAVs bridge the gap between ground-based surveys and satellite remote sensing by offering near-real-time, fine-scale data acquisition that …
Published in International Journal on Drones · Vol. 1, Issue 2, 2025 · pp. 34–42 Read article
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Electronic Resources of University Libraries: AI-Driven Management and Optimization
Abstract: In order to maximize accessibility, utilization, and efficiency, university libraries’ growing reliance on electronic resources (ER) has prompted the creation of sophisticated management techniques. The difficulty of handling enormous volumes of data has increased as educational institutions move from conventional physical collections to massive digital repositories. A key instrument in revolutionizing library operations, artificial intelligence (AI) offers creative ways to improve retrieval methods, manage digital resources more effectively, and customize …
Published in Journal of Advancements in Library Sciences · Vol. 12, Issue 3, 2025 · pp. 8–15 Read article
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Using Machine Learning for Key phrase Extraction in Digital Libraries
Abstract: Machine learning has revolutionized various aspects of information retrieval, including key phrase extraction in digital libraries. Key phrase extraction is crucial for summarizing and categorizing vast amounts of textual data, enabling efficient search and retrieval processes. This study explores the application of machine learning techniques for automatic key phrase extraction in digital libraries. We review various supervised and unsupervised learning algorithms, including deep learning models, that are employed to identify …
Published in International Journal of Cheminformatics · Vol. 1, Issue 2, 2023 · pp. 8–13 Read article