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182 articles for “ML algorithms”
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A Survey of Several Machine Learning (ML) Algorithms for Security Solution in Internet of Things (IoT) Networks
Abstract: The Internet of Things (IoT) refers to the integration of physical objects with the Internet, allowing for connectivity and monitoring. This idea has garnered immense attention from researchers and users alike, driven by the widespread accessibility of the Internet. It spans a wide range of devices, including smart versions of conventional appliances, innovative tools tailored for Internet-enabled ecosystems, and sensors that leverage connectivity to revolutionize industries such as manufacturing, healthcare, …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 1, 2025 · pp. 1–11 Read article
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Mean based Load Adaptation Algorithms (MLAA) for Energy Saving in FiWi Access Networks
Abstract: AbstractFiber Wireless (FiWi) network has been evolving as a promising broadband access network. It provides high data rate, flexibility and stability to the users. Exponential growth in broadband access networks has opened many research challenges. Energy conservation is one of them. In FiWi network, among all the components, optical network unit (ONU) consumes most of the power of the network. Hence, to keep ONU in low power state while ensuring …
Published in Trends in Opto-electro & Optical Communication · Vol. 6, Issue 3, 2016 · pp. 23–32 Read article
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IoT Sensors to Monitor Pipeline Pressure and Flow Rate Combined with ML-Algorithms to Detect Leakages
Abstract: In the field of fluid mechanics, pipelines are the lifeblood of industries, transporting everything from natural gas and oil to water and chemicals. Maintaining their integrity is paramount for safety, economic efficiency, and environmental protection. Traditional leak detection methods explained in fluid mechanics can be slow, expensive, and sometimes fail to identify small leaks early enough to prevent significant damage. However, the convergence of Internet of Things (IoT) and Machine …
Published in Recent Trends in Fluid Mechanics · Vol. 12, Issue 2, 2025 · pp. 40–48 Read article
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Alzheimer’s Disease Detection Using ML Algorithm
Abstract: A degenerative neurological state of affairs, Alzheimer's disease (AD) gradually impairs cognitive and functional capacities, especially in people over 65. Early AD detection is crucial for efficient management and treatment prep. This study delves into novel approaches for the early detection of AD using non-invasive methods. We've implemented a blend of neuroimaging data analysis and machine learning algorithms to pinpoint markers indicative of the disease during its initial phases. Our …
Published in Journal of Experimental & Applied Mechanics · Vol. 15, Issue 3, 2024 · pp. 53–57 Read article
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Customer Churn Prediction Using ML Algorithms
Abstract: Comprehending customer churn is essential for businesses aiming to enhance and sustain customer relationships. This study introduces a machine learning approach aimed at forecasting customer churn by leveraging demographic and behavioral data. Our research involved developing predictive models using support vector machines (SVM), random forests, and decision trees, evaluating their efficacy using real-world data from the telecom industry. Our findings underscore that random forests consistently outperform SVM and decision trees …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 2, 2024 · pp. 70–75 Read article
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Abnormal Crowd Behavior Detection System
Abstract: Abnormal crowd behavior system is designed for security purpose in public sector. The system is developed using ML algorithms such as CNN and Image processing. It performs the functions to detect the abnormality in the crowd by detecting abnormal actions such as fighting, running, etc. where there is threshold value set for different places. This system can be used to reduce human work considering the accuracy and effectiveness of the …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 8, Issue 1, 2021 · pp. 23–28 Read article
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Data Handling Algorithms for the Healthcare System for the Prediction of Diabetes in Health Data Science (HDS): A Review Report
Abstract: In recent years, diabetes has become the biggest disease in different countries around the world. This disease is caused by adulteration in food ingredients, unhealthy food habits, a lack of physical exercise, and changing the lifestyle every time without a routine chart. The main objective of this review paper is to provide a proper understanding of the machine learning algorithm used in the healthcare system to handle diabetic patients' data. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 1–10 Read article
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Visualizing Complexity: Navigating Algorithms with Algorithm Visualizer
Abstract: We think that studying algorithms may be amusing and exciting. Many students are currently struggling, but we hope to change that. Our strategy is to emulate gaming while learning. We're building hands-on learning exercises, such as mazes and patterns, to convey key concept. To help students understand how algorithms function in practice, we also use some stunning visualizations. Three major categories of algorithms are under our purview: sorting, pathfinding, CPU …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 2, Issue 1, 2024 · pp. 21–26 Read article
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A Comprehensive Study of Natural Language Processing Systems Using Modern Programming Languages: Techniques, Architectures, Experimental Evaluation and Applications
Abstract: Natural language processing is a key field of study within artificial intelligence that focuses on enabling machines to understand and work with human language. This is because there is much digital text data everywhere. Natural Language Processing is what this study is about. It looks at new ways of doing Natural Language Processing. The old ways are like machine learning, and the new ways are like learning. This study compares …
Published in Recent Trends in Programming languages · Vol. 13, Issue 1, 2026 · pp. 12–23 Read article
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Traffic Detection Algorithms Analysis using ML
Abstract: It is difficult to watch traffic on crowded roads. Traffic monitoring procedures are time-consuming, expensive, labor-intensive, and require human operators. The limited accessibility hindered the storing and processing of large-scale video streams. Nonetheless, it is now possible to employe video feeds from traffic monitoring systems for number plate recognition, object tracking, traffic behavior analysis, and surveillance. Static image recognition and vehicle identification in a traffic surveillance system are very useful …
Published in Trends in Machine design · Vol. 11, Issue 2, 2024 · pp. 1–8 Read article
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Literature Review and Discussion of Machine Learning Algorithms for Predicting Chronic Kidney Disease
Abstract: Being one of the most serious and most occurring diseases in our era, chronic kidney disease requires a fast and correct diagnosis. The usage of machine learning in medicine has now grown to such a level that it could be a means of diagnosis. The doctor can be the first one to get the ailment by using machine learning classifier algorithms. This has been the data science sector’s new horizons, …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 3, 2024 · pp. 34–39 Read article
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A Comparison Study of Different Classification Algorithm on Brain Tumor Segmentation
Abstract: A brain tumor is a tissue mass caused by aberrant cell proliferation in the brain. It is a collection of tissues that causes hormonal alterations and eventually death. In order to save human lives, brain tumors prognosis and prevention is a difficult task. The use of modern medical image processing approaches has made the identification of brain tumors more flexible in recent years. Due to the absence of ionizing radiations, …
Published in Trends in Opto-electro & Optical Communication · Vol. 11, Issue 3, 2021 · pp. 1–7 Read article
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Harvestify: ML Based Tool for Home Gardening and Farming
Abstract: This study presents a cutting-edge application that will transform home gardening and agriculture practices using machine learning (ML) approaches. The main goal is to provide data-driven insights to home gardeners and farmers, enabling them to implement efficient and sustainable farming practices. Crop disease detection, fertiliser recommendation, and a community section for user engagement comprise the three main elements that make up the system's architecture. The Crop Disease Detection module analyses …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 2, Issue 2, 2024 · pp. 18–28 Read article
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A Correlative Study of Machine Learning Algorithms
Abstract: Machine learning (ML) is the term used to define a systematic reading of algorithms and mathematical models of computer structure used to perform a specific task without precise programming. Learning algorithms in many programs we use every day. Nowadays, one of the reasons an online search engine like Google performs so effectively is because the learning algorithm has mastered the art of rating web sites. Additional uses for these algorithms …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 9, Issue 2, 2022 · pp. 30–35 Read article
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An Overview of the Design and Optimization of Antennas Employing Machine Learning Algorithms and Methodologies
Abstract: This paper offers a comprehensive exploration of the integration of machine learning (ML) techniques in antenna design and optimization, reflecting the burgeoning interest and potential impact of ML in emerging technologies. The first segment conducts a detailed literature survey, elucidating conventional computational electromagnetic and numerical methods preceding an in-depth discussion on the core facets of ML, encompassing diverse learning categories and frameworks. Additionally, it provides a mathematical exposition on regression …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 10, Issue 3, 2023 · pp. 1–12 Read article
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Comparative Study of Machine Learning Techniques for Intelligent 6G Wireless Networks
Abstract: With exponential increase in the traffic and corresponding bandwidth demand, there is an immediate requirement to serve this traffic through the high-speed wireless communication networks. To fulfil requirements of the next-generation users, it will be mandatory to resort to use of advanced physical layer solutions, spectral bands at higher frequency, and efficient software enabled intelligent algorithms. In this regard, Machine Learning (ML) algorithms will play a key role in ensuring …
Published in Journal of Communication Engineering & Systems · Vol. 11, Issue 3, 2021 · pp. 1–10 Read article
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Timely Diabetes Possibility Prediction Using AI Techniques
Abstract: The fastest chronic life-threatening disease affecting more than 422 million people globally is diabetes. The primary causes of type 2 diabetes are lifestyle choices and environmental factors. It is a slowgrowing disease which starts to develop metabolic factors long before they evolve into a disease and is formally diagnosed by a fasting sugar test. There are records of indications related to diabetes from 520 patients in the dataset that was …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 9, Issue 2, 2022 · pp. 37–47 Read article
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Prediction of shear strength of reinforced concrete beams using Artificial Neural Network and evaluated by Finite Element Software
Abstract: ABSTRACTIn this paper, the Artificial Neural Network (ANN) and the Adaptive Neuro-Fuzzy Inference Framework (ANFIS) are utilized to foresee the shear quality of Reinforced Concrete (RC) shafts, and the models are contrasted and American Concrete Institute (ACI) and Iranian Concrete Institute (ICI) observational codes. The ANN display, with Multi-Layer Perceptron (MLP), utilizing a Back-Propagation (BP) algorithm, is utilizedto foresee the shear quality of RC pillars. Six vital parameters are chosen …
Published in Journal of Construction Engineering, Technology & Management · Vol. 8, Issue 1, 2018 · pp. 34–42 Read article
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The Role of Artificial Intelligence and Machine Learning in Redefining Global Healthcare Systems and Advancing Medical Innovation
Abstract: Health Services are being revolutionized with AI and ML through improved accuracy, efficiency and accessibility in the delivery of health care. With AI and ML, it is now possible for health care professionals to assess varying amounts of complex clinical data in a relatively short amount of time, therefore, creating opportunities for early detection of disease, increasing the odds of accurate diagnosis, and improving the ability to make informed clinical …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 1, 2026 · pp. 14–19 Read article
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AI Approaches in Gait and Posture Analysis: A Review
Abstract: This review synthesizes current research on the application of artificial intelligence (AI) in gait and posture analysis, focusing on methodologies, algorithms, and clinical applications. It examines the use of machine learning (ML) and deep learning (DL) techniques to extract relevant features from sensorderived data, offering objective, and automated assessments that surpass traditional methods. A systematic literature review was conducted, analyzing studies that utilized AI for gait and posture analysis with …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 3, 2025 · pp. 1–3 Read article