Precision agriculture using IoT data analytics and machine learning
نویسندگان
چکیده
منابع مشابه
IoT Data Analytics Using Deep Learning
Xiaofeng Xie, Di Wu, Siping Liu, Renfa Li Abstract: Deep learning is a popular machine learning approach which has achieved a lot of progress in all traditional machine learning areas. Internet of thing (IoT) and Smart City deployments are generating large amounts of time-series sensor data in need of analysis. Applying deep learning to these domains has been an important topic of research. The...
متن کاملData Distillation , Analytics , and Machine Learning
In this paper we first provide a brief overview on latent variables modeling methods for process data analytics and the related objectives to distill desirable components or features from a mixture of measured variables. These methods are then extended to modeling high dimensional time series data to extract the most dynamic latent variables one after another, which are referred to as principal...
متن کاملCognitive Analytics: Going Beyond Big Data Analytics and Machine Learning
This chapter defines analytics and traces its evolution from its origin in 1988 to its current stage—cognitive analytics. We discuss types of learning and describe classes of machine learning algorithms. Given this backdrop, we propose a reference architecture for cognitive analytics and indicate ways to implement the architecture. A few cognitive analytics applications are briefly described. T...
متن کاملUsing Big Data for Machine Learning Analytics in Manufacturing
Ajit has over 10 years of experience in manufacturing operations and consulting. His functional expertise comprises Industrial Operations, Supply Chain, and Quality and Manufacturing Analytics. He has successfully executed various cost saving, process improvement and business intelligence (BI) projects for leading manufacturing companies. Saurabh has over three years of industry experience in t...
متن کاملMachine Learning Models for Housing Prices Forecasting using Registration Data
This article has been compiled to identify the best model of housing price forecasting using machine learning methods with maximum accuracy and minimum error. Five important machine learning algorithms are used to predict housing prices, including Nearest Neighbor Regression Algorithm (KNNR), Support Vector Regression Algorithm (SVR), Random Forest Regression Algorithm (RFR), Extreme Gradient B...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of King Saud University - Computer and Information Sciences
سال: 2021
ISSN: 1319-1578
DOI: 10.1016/j.jksuci.2021.05.013