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104 articles for “machine learning algorithms”
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Use of Machine Learning Algorithms in Power System Load Forecasting: A review
Abstract: The electrical load forecasting has become one of the most important fields of research for secured, efficient, accurate, reliable power dispatch and management. The main aim of load demand forecasting is to predict the load demand for accurate generation scheduling, system security and economic dispatch of load at any time. Many Authors have done research on the evaluation of load forecasting methods, to improve the accuracy of prediction. In load …
Published in International Journal of Microwave Engineering and Technology · Vol. 7, Issue 1, 2021 · pp. 23–30 Read article
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Breast Tumor Classification Using Machine Learning Algorithm
Abstract: Breast cancer is characterized by genetic mutations, periodic pain, changes in the length, color (redness) and texture of the breast skin. The categories of most types of breast cancer led the pathologist to a systematic and objective prognostic analysis. In general, the most common category is binary (benign/malignant). Today, Learning Gadget (ML) strategies are widely used in breast cancer classification problems. Offers extreme accuracy and powerful diagnostic technology. It kills …
Published in International Journal of Microwave Engineering and Technology · Vol. 8, Issue 1, 2022 · pp. 35–40 Read article
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House Price Prediction using Machine Learning Algorithms
Abstract: House Prices depend on various factors such as location, features of the house, construction and so on. To factor all these aspects and predict an accurate price of the house can be very tricky. The following paper proposes a system that considers every aspect of a house that effects its pricing and gives an accurate prediction of the house. The system accomplishes this utilising Gradient Boosting, Random Forest, and Decision …
Published in International Journal of Digital Communication and Analog Signals · Vol. 8, Issue 1, 2022 · pp. 23–29 Read article
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Machine Learning Approaches for Customer Churn Prediction in Telecommunications
Abstract: Customer churn prediction is a critical challenge for companies in the telecommunications industry. The competition is intense, and acquiring new customers can be costly. Predicting when existing customers might leave (churn) helps companies take proactive measures to retain them, reducing churn rates and costs. By analyzing historical customer data, including demographics, service usage, billing, and customer service interactions, this study aims to identify customers at risk of leaving their current …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 10, Issue 2, 2024 · pp. 1–7 Read article
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TCP Security Action Prediction Algorithm based on Machine Learning: A Review
Abstract: The growing range of applications available on the Internet and continuous technological improvements have led to an increase in network security incidents and cyber-attacks. Consequently, computer network security is becoming more and more important. Network security can be allowed or prohibited by a TCP firewall; a device used for computer network security. When utilising classic firewalls, network managers must periodically choose which packets to admit and prohibit to keep computer …
Published in International Journal of Digital Communication and Analog Signals · Vol. 9, Issue 1, 2023 · pp. 21–26 Read article
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A Role of Machine Learning for Students' Academic Success Prediction
Abstract: This research paper aims to identify early predictions of students’ academic success with the help of different indicators. One of the crucial parts of the study is identifying additional indicators that play an essential role in defining students' academic success. Early prediction of success will be helpful for various stakeholders such as students, parents, educators/teachers, institutions, universities, and the government. Machine Learning is a part of Artificial Intelligence (AI) and …
Published in International Journal of Computer Aided Manufacturing · Vol. 10, Issue 1, 2024 · pp. 1–6 Read article
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Predicting User Engagement on Social Media: A Comparative Study of Machine Learning-based Modeling Approaches
Abstract: Abstract Even while mobile social apps are becoming more and more important in people's daily lives, little is known about the elements that motivate users to interact with these apps. The goal of this work is to analyze and define the transition patterns of individual users' in-app actions as a temporally changing action graph. According to our investigation, action graphs are a useful tool for characterizing user behaviour patterns and …
Published in International Journal of Computer Aided Manufacturing · Vol. 11, Issue 2, 2025 · pp. 41–62 Read article
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Brain Tumor Detection using Machine Learning Methods-KNN, SVM, DT, RF
Abstract: Brain tumor is a major contributor to illness and death worldwide, and timely diagnosis is essential for successful treatment and improved outcomes Recent research has looked into the possibility of machine learning algorithms for detecting and classifying brain tumours in medical pictures. In this study, four commonly used machine learning algorithms (K-Nearest Neighbours, Decision Trees, Support Vector Machines, and Random Forests) were evaluated for their effectiveness in brain tumor detection. …
Published in International Journal of Chemical Engineering and Processing · Vol. 9, Issue 2, 2023 · pp. 48–59 Read article
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Fake News Detection Based on 3-HAN Architecture Using Deep Learning Techniques
Abstract: Fake news spreading is a common scenario we see nowadays in this modern era of social media and smart phones. According to the New York Times, fake news is described as “a made-up story with the intention of misleading, frequently with financial gain as the motive.” The problem is complex, given its varied interpretations across the globe. Hence, an effective system is needed to detect whether the given news is …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 9, Issue 2, 2023 · pp. 21–31 Read article
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Securing Smart Electrical Systems through Comparative Analysis of Machine Learning Models for Classification
Abstract: In the realm of cybersecurity, the intersection of technology and security measures has spurred significant advancements, particularly in safeguarding electrical systems against cyber threats. This research delves into the evolving landscape of cybersecurity within electrical systems, leveraging machine learning techniques to mitigate challenges. By incorporating cybersecurity protocols with machine learning algorithms, this study demonstrates enhanced security measures tailored for electrical infrastructures, pivotal in ensuring efficiency and resilience. Through meticulous examination, …
Published in International Journal of Electrical Power System and Technology · Vol. 12, Issue 2, 2026 Read article
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Algorithmic Approaches for Data Mining and Machine Learning
Abstract: ABSTRACTTrends and technology always innovative and comes with some new. Sometimes technologies are introduces in more user friendly environment. In such version of technology advancement are also incorporated. Data mining is a best widespread knowledge attainment approach for knowledge discovery. The naval trends Machine learning also have a big interfere of data mining. Infect most of the data mining algorithm and methods are utilized for machine learning with minor amendment …
Published in International Journal of Distributed Computing and Technology · Vol. 6, Issue 2, 2020 · pp. 24–29 Read article
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Face and Speech Emotion Recognition
Abstract: The study “faces and speech recognition” underscores the critical role of speech emotion recognition (SER) and its diverse applications across various fields, such as medicine, human-computer interaction, and customer service. SER has gained significant importance in cognitive psychology due to its potential to enhance user experience, improve patient care, and optimize the interaction between users and products. The process involves the identification and extraction of essential features from speech signals, …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 10, Issue 2, 2024 · pp. 35–43 Read article
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Maculopathy Detection and Recommendation using Machine Learning
Abstract: Maculopathies, a diverse group of eye diseases affecting the central portion of the retina, the macula, are a leading cause of vision loss globally. Early detection and accurate diagnosis are critical for timely intervention and preventing irreversible vision loss. However, traditional methods such as manually detecting the disease are time-consuming, tiring, and often lack sensitivity and specificity, hindering optimal patient care. Here we delve into the applications of machine learning …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 10, Issue 1, 2024 · pp. 10–16 Read article
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Health Care System Analysis Using Different Datasets
Abstract: In this research work, we have discussed data science and various machine learning algorithms like KNN, Support Vector Machine, Artificial neural network, Random forest etc. and the results obtained from these algorithms which can be used for the prediction of heart disease, cancer and in many other fields of medical science. Requirement of data cleaning along with various methods of data cleaning are mentioned here, along with these various issues …
Published in International Journal of Distributed Computing and Technology · Vol. 8, Issue 2, 2022 · pp. 29–37 Read article
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Leveraging Prediction Strategies to Enhance Milk Quality and Promote Dairy Sustainability
Abstract: In the Dairy industry, ensuring high-quality milk production is vital. This research paper focuses on employing machine learning methods to predict milk quality based on diverse parameters including pH levels, temperature, fat content, and colour. By harnessing data encompassing these factors along with established quality markers, the study aims to construct a predictive model. This model seeks to anticipate variations in milk quality, providing insights into potential fluctuations in fat …
Published in International Journal of Green Chemistry · Vol. 9, Issue 2, 2023 · pp. 38–47 Read article
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Forecasting Trends in the Stock Market by Using Deep Learning Approaches
Abstract: Accurately predicting stock market trends remains a significant challenge in the field of finance. Deep learning, a subset of machine learning, has emerged as a powerful tool for capturing complex relationships within data. What sets deep learning apart is its ability to handle vast amounts of data, recognize intricate features, and adapt to evolving patterns, all while uncovering hidden insights. At its core, deep learning uses artificial neural networks that …
Published in International Journal of Software Computing and Testing · Vol. 10, Issue 2, 2024 · pp. 22–30 Read article
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Discovery of Materials through Applied Machine Learning and General Machine Learning Architecture
Abstract: Advances in artificial intelligence technologies, especially machine learning, have generated possibilities in the material sciences to facilitate material exploration and to achieve a profound understanding of the relationship between the constituent elements of the material and the properties represented by the material. The application of machine learning to the exploration of experimental materials is sluggish due to the monetary and temporal costs of experimental data, however parallel methods, such as …
Published in International Journal of Analog Integrated Circuits · Vol. 6, Issue 2, 2020 · pp. 48–57 Read article
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Review of Anomaly Detection Techniques in MANETs: AMachine Learning Approach to Intrusion Detection, Attack Prediction, and Routing Security
Abstract: Mobile Ad hoc Networks (MANETs) are decentralized, self-organizing networks that offer flexibility and scalability for a variety of applications. However, their dynamic topology and limited resources make them highly susceptible to security threats. Traditional security measures often struggle to address the complexities of evolving and sophisticated attacks within such networks. This paper reviews the role of machine learning (ML) techniques in enhancing anomaly detection capabilities in MANETs, focusing on their …
Published in International Journal of Broadband Cellular Communication · Vol. 11, Issue 2, 2026 · pp. 1–5 Read article
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A study on additive manufacturing with optimization of artificial intelligence
Abstract: Abstract The process of producing a three dimensional product layer by layer is called additive manufacturing. This process not the same as a traditional machining procedure. Chips are taken out of the raw material to create a component in traditional machining. three dimensional printing is another name for additive manufacturing. The benefit of three dimensional printing is that it can create any complex three dimensional item. The culinary, chemical, aerospace, …
Published in International Journal of Computer Aided Manufacturing · Vol. 11, Issue 2, 2025 · pp. 19–40 Read article
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Development of Smart Fire Extinguishing
Abstract: The invention of smart fire extinguishing agents, which satisfy the growing need for efficient, eco-friendly, and adaptable fire suppression systems, is a significant advancement in fire safety. Traditional fire extinguisher chemicals, such as water, foam, and chemical powders, are effective, but they often have disadvantages, including toxicity, negative environmental effects, and inefficiency in difficult situations. Conversely, smart extinguishing agents maximize fire suppression through intelligent, tailored responses by utilizing advancements in …
Published in International Journal of Environmental Chemistry · Vol. 11, Issue 2, 2025 · pp. 1–19 Read article