Recent advancements and challenges of AIoT application in smart agriculture: A review
As the most popular technologies of the 21st century, artificial intelligence (AI) and the
internet of things (IoT) are the most effective paradigms that have played a vital role in …
internet of things (IoT) are the most effective paradigms that have played a vital role in …
A systematic literature review on identifying patterns using unsupervised clustering algorithms: A data mining perspective
Data mining is an analytical approach that contributes to achieving a solution to many
problems by extracting previously unknown, fascinating, nontrivial, and potentially valuable …
problems by extracting previously unknown, fascinating, nontrivial, and potentially valuable …
Data-driven multi-step prediction and analysis of monthly rainfall using explainable deep learning
Monthly rainfall prediction is a crucial topic for the management of water resources and
prevention of hydrological disasters. To make a multi-step monthly rainfall prediction and …
prevention of hydrological disasters. To make a multi-step monthly rainfall prediction and …
A safe path towards carbon neutrality by 2050: Assessing the impact of oil and gas efficiency using advanced quantile-based approaches
In the present era, we are confronted with a dilemma: how can economic prosperity be
attained while addressing the ecological challenges associated with energy resource …
attained while addressing the ecological challenges associated with energy resource …
Enhanced multi-step streamflow series forecasting using hybrid signal decomposition and optimized reservoir computing models
This study evaluates the use of different time series decomposition methods in association
with echo state networks (ESNs), deep echo state networks (DeepESNs), and next …
with echo state networks (ESNs), deep echo state networks (DeepESNs), and next …
An intelligent early flood forecasting and prediction leveraging machine and deep learning algorithms with advanced alert system
Flood disasters are a natural occurrence around the world, resulting in numerous casualties.
It is vital to develop an accurate flood forecasting and prediction model in order to curb …
It is vital to develop an accurate flood forecasting and prediction model in order to curb …
A novel interval decomposition correlation particle swarm optimization-extreme learning machine model for short-term and long-term water quality prediction
S Huan - Journal of Hydrology, 2023 - Elsevier
Water quality prediction plays a crucial role in pollution treatment. However, inaccurate long-
term prediction resulting from complex information patterns and insufficient feature extraction …
term prediction resulting from complex information patterns and insufficient feature extraction …
Assessing the sustainability of natural resources using the five forces and value chain combined models: the influence of solar energy development
Utilizing natural resources may assists India in overcoming its prevailing energy crises.
However, the instability of natural resources hinders its capacity to overcome these crises …
However, the instability of natural resources hinders its capacity to overcome these crises …
Unleashing the influence of industrialization and trade openness on renewable energy intensity using path model analysis: A roadmap towards sustainable …
In the globalized world, the complicated relationship between macroeconomic variables has
resulted in several challenges that have a diversified influence on renewable energy …
resulted in several challenges that have a diversified influence on renewable energy …
RfGanNet: an efficient rainfall prediction method for India and its clustered regions using RfGan and deep convolutional neural networks
Early rainfall prediction is very important to ensure the economic balance of any agriculture-
dominated country, such as India. Deep learning has recently received considerable …
dominated country, such as India. Deep learning has recently received considerable …