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3 articles for “data cleaning automation”
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Improving Dataset Integrity Through Automated Data Cleaning Techniques
Abstract: High-quality data is a fundamental requirement in data science for producing trustworthy analytical insights and effective machine learning models. Problems, including incomplete records, inconsistent entries, duplicate observations, and anomalous values, can severely reduce the accuracy and robustness of predictive systems. As modern datasets continue to expand in both volume and structural complexity, relying on manual data cleaning methods become time-consuming and error-prone, highlighting the growing importance of automated data preprocessing …
Published in International Journal of Data Structure Studies · Vol. 4, Issue 1, 2026 · pp. 40–45 Read article
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Assessment of Cleaning Methods for Solar PV Modules: A Review of Current Practices
Abstract: This study looks at how well solar panel cleaning technologies work to increase energy output, lower maintenance costs, and lengthen the life of solar panel systems. The necessity for efficient and economical maintenance of solar panels is growing in importance due to the rising demand for solar energy. Systems for cleaning solar panels have become a viable way to address the problem of maintaining clean and efficient solar panels. Our …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 1, Issue 1, 2023 · pp. 23–28 Read article
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The Role of IoT and AI in Advancing Wastewater Treatment Plant Efficiency
Abstract: Wastewater treatment facilities, or WWTPs, are essential for protecting the environment and human health because they clean wastewater before it is released into natural water bodies. The operational effectiveness and efficiency of WWTPs have undergone a significant transformation as a result of the integration of smart technology for real-time monitoring and control. This review looks at new developments in smart technologies that are being used in WWTPs, including data analytics, …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 2, Issue 1, 2024 · pp. 28–33 Read article