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55 articles for “machine learning (ML)”
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Climate Change Modeling Using Machine Learning and Big Data
Abstract: Climate change is now one of the biggest issues that affect the world today and studying its impacts for it is very significant in enabling the formulation of social policies. This paper also discusses how climate sciences, machine learning, and big data analytics can greatly help in the improvement of the current capacities in climate modeling. Explaining the methods of climate modeling, we look at how the big data offers …
Published in International Journal of Software Computing and Testing · Vol. 11, Issue 1, 2025 · pp. 6–11 Read article
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Blood Cell Subtype Classification Using Deep Learning
Abstract: A vital component of human bodies is blood. Despite making up only 1% of the human body, blood cells have a greater impact on disease and infection detection. These blood cell subtype classifications also aid in ensuring that patients receive the quickest-acting medical treatment and recover swiftly. To get the findings, many machine learning techniques are used, including the Feature Extraction methods (K* classifier and Decision table) and the Image …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 9, Issue 1, 2023 · pp. 37–45 Read article
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Integrating Machine Learning with Edge Computing for Real Time Data Analytics
Abstract: Smart devices such as mobile phones, sensors, cameras, etc., are producing a huge amount of data every second. This data is normally sent to cloud servers for processing. This approach is normally slow and expensive, and it also raises a lot of privacy issues as data is sent over the internet, which takes a lot of time to return with results. This study aims to address the issue through the …
Published in International Journal of Distributed Computing and Technology · Vol. 12, Issue 2, 2026 Read article
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Optimizing Internal Combustion Engine Performance and Fleet Fuel Economy through Machine Learning and AI using Big Data Analytics
Abstract: Abstract This paper presents a software-defined operational intelligence approach for optimizing internal combustion engine performance and fleet fuel economy using Big Data Analytics combined with Machine Learning and Artificial Intelligence. Real-world vehicle data is transformed into engineered features and virtual sensing outputs to estimate fuel consumption, driver behaviour, and component health without additional hardware. The proposed system integrates fuel optimization, predictive maintenance, driver assistance, and sustainability assessment into a unified …
Published in International Journal of I.C. Engines and Gas Turbines · Vol. 12, Issue 1, 2026 · pp. 1–7 Read article
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Prediction of Adsorption Energies using Machine Learning
Abstract: In this article, we have a much more comprehensive method that promotes the exploration of automated descriptors. Primary component analysis (PCA) with varimax rotation is used to find the strongest minimum range of adsorption energies that can be used as metal descriptors for a given data set. Our findings demonstrate that the mixture of descriptors produced by this method outperforms conventional descriptors such as nuclear carbon, hydrogen and oxygen adsorption …
Published in International Journal of Electrical Power System and Technology · Vol. 6, Issue 2, 2020 · pp. 38–46 Read article
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Modeling of Material Removal Rate in Micro EDM Using Neural Network
Abstract: In micro-electrical discharge machining (Micro EDM) machining, material removal rate (MRR) is the particular main output parameter. Here we will discover various machining parameters get an effect on the particular MRR. For production industries, to maximize the results from Micro EDM, appropriate predictive designs for MRR must end up being constructed. This particular report utilizes neural network modeling to predict MRR over the particular machining time for assortment of cutting …
Published in International Journal of Microelectronics and Digital integrated circuits · Vol. 4, Issue 1, 2018 · pp. 30–39 Read article
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Optimizing Internal Combustion Engine Performance and Fleet Fuel Economy through Machine Learning and AI using Big Data Analytics
Abstract: This paper presents a software-defined operational intelligence approach for optimizing internal combustion engine performance and fleet fuel economy using Big Data Analytics combined with Machine Learning and Artificial Intelligence. Real-world vehicle data is transformed into engineered features and virtual sensing outputs to estimate fuel consumption, driver behaviour, and component health without additional hardware. The proposed system integrates fuel optimization, predictive maintenance, driver assistance, and sustainability assessment into a unified one-stop …
Published in International Journal of I.C. Engines and Gas Turbines · Vol. 12, Issue 1, 2026 · pp. 35–51 Read article
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A Review on Property Price Tracking Using ML Model
Abstract: The very common reason for an investment is to get benefits in future. Different legal and illegal utilization leads to cost fluctuation. It is therefore important to well manage the [exploitative] of the property, and an application like price predictor is well equipped with optimal solution. However, such price prediction methods require an appropriate knowledge and experience regarding this domain. By utilising machine learning techniques and algorithms, the price of …
Published in International Journal of Analog Integrated Circuits · Vol. 8, Issue 2, 2022 · pp. 11–20 Read article
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Employing ML and DL to Optimize an ElectrochemicalBiosensor
Abstract: A major field of study in science, that have made the understanding of the world and made homo sapiensthe dominant species on the planet is our understanding of medicine. Under this vast umbrella is thedetection and classification of microorganisms. Electrochemical biosensors have emerged aspromising tools in this regard due to their high sensitivity, selectivity, and potential for miniaturization.By integrating a Machine Learning & Deep Learning model for the detection of …
Published in International Journal of Chemical Separation Technology · Vol. 10, Issue 1, 2024 · pp. 33–38 Read article
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Future Trends in Web Analytics: A Comprehensive Review
Abstract: This review paper explores future trends in web analytics, focusing on their impact on business and technological advancements. The paper discusses critical areas such as advanced data analytics, mobile analytics, offline and online data integration, privacy protection, and data visualisation. Drawing upon scientific literature, the paper highlights the significance of artificial intelligence, machine learning, and sentiment analysis in deepening data insights. Integrating offline and online data and the growing importance …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 9, Issue 1, 2023 · pp. 12–17 Read article
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An Efficient Machine Learning System forPrediction of Water Quality with Explainable AI
Abstract: Abstract Water availability and quality have been issues globally, especially in developing nations. Unchecked urbanization and industrialization contaminate natural water supplies and aquifers, potentially introducing physical, chemical, and biological contaminants. Over 80% of illnesses are caused by drinking tainted water, according to a WHO assessment. As clean water sources become more at risk, water quality protection has become of human, environmental, and economic importance worldwide. These water sources, crucial for …
Published in International Journal of Water Resources Engineering · Vol. 11, Issue 1, 2025 · pp. 33–42 Read article
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Detection of Phishing Sites Using Machine Learning
Abstract: The content of phishing websites and online-based material provides a variety of indicators. One of the criminal attacks that are successful in the online world is phishing sites that direct users to a phishing website that looks and acts like a legitimate website in order to steal the victim's personal and sensitive information. The Extreme Learning Machine-based version that was suggested was excellent at spotting phishing websites. Internet page types …
Published in International Journal of Software Computing and Testing · Vol. 9, Issue 1, 2023 · pp. 33–39 Read article
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Advancing Maize Leaf Disease Detection: A Machine Learning Approach
Abstract: Every day, countless grains and fruits are cultivated around the world. To keep up with the growing population’s needs, farmers are constantly adopting new and advanced techniques. Furthermore, the development and application of new technologies enable the quick and simple detection of plant diseases. Identifying plant diseases at an early stage is crucial to minimizing their effects on crop productivity and quality. Traditional diagnostic methods often rely on expert knowledge …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 11, Issue 1, 2025 · pp. 17–25 Read article
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ML Based Agro Solution
Abstract: Nowadays, in India, the climatic conditions change rapidly. Sometimes the climate is cold, sometimes it turns out to be humid. In such drastic conditions, farmers are unable to decide which crop we must grow in that particular season according to that climate. This becomes a tedious task for the farmers during decision making. Also, it becomes difficult for the farmers to detect what kind of disease has happened to the …
Published in International Journal of Agrochemistry · Vol. 8, Issue 1, 2022 · pp. 1–5 Read article
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Comparative Analysis of Air Quality Indices Across Five Eastern States of India Using ML Models and Pollutant Based Insights
Abstract: This paper presents a comparative study of Air Quality Index (AQI) levels in five eastern Indian states–Arunachal Pradesh, Assam, Meghalaya, Nagaland, and Tripura. Using historical data, the study explores the concentration of key pollutants, including PM2.5, PM10, NO2, SO2, CO, and Ozone, highlighting regional variations in air quality. Assam, with its higher levels of urbanization and industrial activity, shows elevated AQI levels, especially for pollutants like PM10 and NO2. In …
Published in International Journal of Distributed Computing and Technology · Vol. 11, Issue 1, 2025 · pp. 31–42 Read article