Bøker av Ramesh Kumar Yadav

In the realm of technological advancement, Artificial Intelligence stands as an unparalleled frontier, revolutionizing the way we perceive, interact with, and shape the world. "Artificial Intelligence: Building Intelligent Systems" represents a comprehensive journey through the multifaceted landscape of AI, offering a holistic understanding and practical insights into constructing systems that simulate human intelligence. This book is an amalgamation of cutting-edge theories, methodologies, and real-world applications carefully crafted to serve as a guiding beacon for students, researchers, and professionals navigating the intricate domain of AI.In the pages that follow, readers will embark on a captivating exploration of AI's evolution, from its foundational principles to its intricate complexities. Through a meticulously curated blend of theoretical foundations and hands-on practices, this book aims not only to elucidate the inner workings of AI but also to empower enthusiasts to harness its potential. With a focus on fostering a deep comprehension of AI algorithms, ethical considerations, and innovative implementations, this book aspires to equip its readers with the tools and wisdom necessary to contribute meaningfully to the burgeoning field of Artificial Intelligence.

In this book, interannual variability of North-West India winter precipitation (NWIWP) has been examined. It has been found that the simultaneous relationship with ENSO and equatorial Indian Ocean SST relationship has strengthened and the North Atlantic Oscillation (NAO) relationship has weakened in the recent decades. The convective heating anomalies of the tropical atmosphere due to increased SST over equatorial Pacific and Indian Oceans during the excess NWIWP years increase the meridional temperature gradient, which in turn intensifies and shifts the sub-tropical westerly jet-stream to lower latitudes. The jet-stream over northern India plays an important role in modulating NWIWP. While, NAO intensifies subtropical high over North Atlantic and adjoining areas. This contributes to the synoptic forcing that helps to develop the trough over Caspian Sea and hence, excess NWIWP. Also, the simultaneous relationship between NWIWP and convective maximum over warm-pool region, increases the seasonal predictability of NWIWP. Of the three empirical seasonal forecast models developed for NWIWP, the Artificial Neural Network model with 6 predictors showed better skill.