Big Data Analytics Using Artificial Intelligence

In this thought-provoking guide, readers will embark on a journey through the fascinating realm of big data analytics, discovering how vast volumes of data can be collected, processed, and analyzed with remarkable precision. Through the lens of artificial intelligence, the reprint delves into the realm of machine learning, neural networks, natural language processing, and computer vision, demonstrating how these AI techniques can be leveraged to extract valuable insights and patterns from massive datasets. Key features of "Big Data Analytics Using Artificial Intelligence" include Comprehensive Coverage. Real-World Applications, Practical Guidance, Ethical Considerations, and Future Trends. Whether you are a data scientist, business analyst, or simply curious about the transformative power of big data and AI, "Big Data Analytics Using Artificial Intelligence" is your comprehensive guide to unlocking the potential of these technologies. Dive into this illuminating reprint and discover how the synergy of big data and AI can propel your understanding, decision-making, and innovation to new heights. About the Editors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii Abdelazim G. Hussien, Laith Abualigah, Raed Abu Zitar, Fatma A. Hashim, Mohamed Amin, Abeer Saber, et al. Recent Advances in Harris Hawks Optimization: A Comparative Study and Applications Reprinted from: Electronics 2022, 11, 1919, doi:10.3390/electronics11121919 . . . . . . . . . . . . . 1 Manisha Singh, Gurubasavaraj Veeranna Pujar, Sethu Arun Kumar, Meduri Bhagyalalitha, Handattu Shankaranarayana Akshatha, Belal Abuhaija, et al. Evolution of Machine Learning in Tuberculosis Diagnosis: A Review of Deep Learning-Based Medical Applications Reprinted from: Electronics 2022, 11, 2634, doi:10.3390/electronics11172634 . . . . . . . . . . . . . 51 Mohammad H. Nadimi-Shahraki, Shokooh Taghian, Seyedali Mirjalili, Laith Abualigah, Mohamed Abd Elaziz and Diego Oliva EWOA-OPF: Effective Whale Optimization Algorithm to Solve Optimal Power Flow Problem Reprinted from: Electronics 2021, 10, 2975, doi:10.3390/electronics10232975 . . . . . . . . . . . . . 75 Mohammad H. Nadimi-Shahraki, Saeed Mohammadi, Hoda Zamani, Mostafa Gandomi and Amir H. Gandomi A Hybrid Imputation Method for Multi-Pattern Missing Data: A Case Study on Type II Diabetes Diagnosis Reprinted from: Electronics 2021, 10, 3167, doi:10.3390/electronics10243167 . . . . . . . . . . . . . 99 Mohammad Kamel Daradkeh A Hybrid Data Analytics Framework with Sentiment Convergence and Multi-Feature Fusion for Stock Trend Prediction Reprinted from: Electronics 2022, 11, 250, doi:10.3390/electronics11020250 . . . . . . . . . . . . . 119 Noor Saleh Alfaiz and Suliman Mohamed Fati Enhanced Credit Card Fraud Detection Model Using Machine Learning Reprinted from: Electronics 2022, 11, 662, doi:10.3390/electronics11040662 . . . . . . . . . . . . . 139 Mona A. S. Ali, Kishore Balasubramanian, Gayathri Devi Krishnamoorthy, Suresh Muthusamy, Santhiya Pandiyan, Hitesh Panchal, et al. Classification of Glaucoma Based on Elephant-Herding Optimization Algorithm and Deep Belief Network Reprinted from: Electronics 2022, 11, 1763, doi:10.3390/electronics11111763 . . . . . . . . . . . . . 155 Fathimathul Rajeena P. P., Rasha Orban, Kogilavani Shanmuga Vadivel, Malliga Subramanian, Suresh Muthusamy, Diaa Salam Abd Elminaam, et al. A Novel Method for the Classification of Butterfly Species Using Pre-Trained CNN Models Reprinted from: Electronics 2022, 11, 2016, doi:10.3390/electronics11132016 . . . . . . . . . . . . . 173 Mohammad Daradkeh, Laith Abualigah, Shadi Atalla andWathiq Mansoor Scientometric Analysis and Classification of Research Using Convolutional Neural Networks: A Case Study in Data Science and Analytics Reprinted from: Electronics 2022, 11, 2066, doi:10.3390/electronics11132066 . . . . . . . . . . . . . 193 Mona A. S. Ai, Anitha Shanmugam, Suresh Muthusamy, Chandrasekaran Viswanathan, Hitesh Panchal, Mahendran Krishnamoorthy Real-Time Facemask Detection for Preventing COVID-19 Spread Using Transfer Learning Based Deep Neural Network Reprinted from: Electronics 2022, 11, 2250, doi:10.3390/electronics11142250 . . . . . . . . . . . . . 215 v Imran Mir, Faiza Gul, Suleman Mir, Mansoor Ahmed Khan, Nasir Saeed, Laith Abualigah, et al. A Survey of Trajectory Planning Techniques for Autonomous Systems Reprinted from: Electronics 2022, 11, 2801, doi:10.3390/electronics11182801 . . . . . . . . . . . . . 237 Shadi AlZu’bi, Raed Abu Zitar, Bilal Hawashin, Samia Abu Shanab, Amjed Zraiqat, Ala Mughaid, et al. A Novel Deep Learning Technique for Detecting Emotional Impact in Online Education Reprinted from: Electronics 2022, 11, 2964, doi:10.3390/electronics11182964 . . . . . . . . . . . . . 263 Muneer Nusir, Ali Louati, Hassen Louati, Usman Tariq, Raed Abu Zitar, Laith Abualigah and Amir H. Gandomi Design Research Insights on Text Mining Analysis: Establishing the Most Used and Trends in Keywords of Design Research Journals Reprinted from: Electronics 2022, 11, 3930, doi:10.3390/electronics11233930 . . . . . . . . . . . . . 287 Debabrata Swain, Utsav Mehta, Ayush Bhatt, Hardeep Patel, Kevin Patel, Devanshu Mehta, et al. A Robust Chronic Kidney Disease Classifier Using Machine Learning Reprinted from: Electronics 2023, 12, 212, doi:10.3390/electronics12010212 . . . . . . . . . . . . . 309 Amir H. Gandomi, Fang Chen and Laith Abualigah Big Data Analytics Using Artificial Intelligence Reprinted from: Electronics 2023, 12, 957, doi:10.3390/electronics12040957 . . . . . . . . . . . . . 323 vi