Mandeep Kaur Saggi

TL;DR: This article presents a comprehensive, well-informed examination, and realistic analysis of deploying big data analytics successfully in companies and presents a methodical analysis for the usage of Big Data Analytics in various applications such as agriculture, healthcare, cyber security, and smart city.

TL;DR: H2O model framework is presented to determine the daily ET o for Hoshiarpur and Patiala districts of Punjab to gain insights into a state-of-the-art big data application in smart farming.

TL;DR: A comprehensive review is conducted to recognize the feasibility of EC models and their potential in simulating ETo in a wide range of environments and several possible future research directions are proposed for the investigations of ETo using EC.

TL;DR: In this paper, the authors proposed a new model for predicting evaporation losses from reservoirs, which is an essential component of reservoir management and operation, and demonstrated that the model has a better prediction performance than conventional models.

TL;DR: Novel WS prediction models based on the multivariate empirical mode decomposition (MEMD), random forest (RF) and Kernel Ridge Regression (KRR) were constructed in this paper for better accuracy in WS prediction and indicated that the MEMD-PSO-RF model has a remarkable performance in predicting WS and can be considered for practical applications.