Artificial Intelligence of Things for Weather Forecasting and Climatic Behavioral Analysis by Rajeev Kumar Gupta (Editor); Arti Jain (Editor); John Wang (Editor); Ved Prakash Singh (Editor); Santosh Bharti (Editor)Weather forecasting and climate behavioral analysis have traditionally been done using complicated physics models and accompanying atmospheric variables. However, the traditional approaches lack common tools, which can lead to incomplete information about the weather and climate conditions, in turn affecting the prediction accuracy rate. To address these problems, the advanced technological aspects through the spectrum of artificial intelligence of things (AIoT) models serve as a budding solution. Further study on artificial intelligence of things and how it can be utilized to improve weather forecasting and climatic behavioral analysis is crucial to appropriately employ the technology. Artificial Intelligence of Things for Weather Forecasting and Climatic Behavioral Analysis discusses practical applications of artificial intelligence of things for interpretation of weather patterns and how weather information can be used to make critical decisions about harvesting, aviation, etc. This book also considers artificial intelligence of things issues such as managing natural disasters that impact the lives of millions. Covering topics such as deep learning, remote sensing, and meteorological applications, this reference work is ideal for data scientists, industry professionals, researchers, academicians, scholars, practitioners, instructors, and students.
Publication Date: 2022 Professor Wang is in the Department of Information Management and Business Analytics
Encyclopedia of Data Science and Machine Learning by John Wang (Editor)The Encyclopedia of Data Science and Machine Learning examines current, state-of-the-art research in the areas of data science, machine learning, data mining, and more. It provides an international forum for experts within these fields to advance the knowledge and practice in all facets of big data and machine learning, emphasizing emerging theories, principals, models, processes, and applications to inspire and circulate innovative findings into research, business, and communities. Covering topics such as benefit management, recommendation system analysis, and global software development, this expansive reference provides a dynamic resource for data scientists, data analysts, computer scientists, technical managers, corporate executives, students and educators of higher education, government officials, researchers, and academicians.
Publication Date: 2023 Professor Wang is in the Department of Information Management and Business Analytics