A comprehensive review and analysis of solar forecasting techniques
In the last two decades, renewable energy has been paid immeasurable attention to toward
the attainment of electricity requirements for domestic, industrial, and agriculture sectors …
the attainment of electricity requirements for domestic, industrial, and agriculture sectors …
An accurate GRU-based power time-series prediction approach with selective state updating and stochastic optimization
Accurate power time-series prediction is an important application for building new
industrialized smart cities. The gated recurrent units (GRUs) models have been successfully …
industrialized smart cities. The gated recurrent units (GRUs) models have been successfully …
A CNN‐BiLSTM based deep learning model for mid‐term solar radiation prediction
The penetrations of solar power plants are increasing their presence worldwide. The solar
power plants have uncertain power output as its output depends on solar radiation, which is …
power plants have uncertain power output as its output depends on solar radiation, which is …
Regression and generalized additive model to enhance the performance of photovoltaic power ensemble predictors
A Sundararajan, B Ollis - IEEE Access, 2021 - ieeexplore.ieee.org
Photovoltaic (PV) power prediction has a constantly evolving solutions landscape with a
myriad of data-driven techniques. Each technique leverages a self-adaptive algorithm that …
myriad of data-driven techniques. Each technique leverages a self-adaptive algorithm that …
An investigation of the short-term meteorological drought variability over Asir Region of Saudi Arabia
Abstract Changes in precipitation as a result of climate change are becoming a widespread
issue all around the world. A lack of rainfall causes a meteorological drought. The short-term …
issue all around the world. A lack of rainfall causes a meteorological drought. The short-term …
RETRACTED ARTICLE: ANN and fuzzy based household energy consumption prediction with high accuracy
K Balachander, D Paulraj - Journal of Ambient Intelligence and …, 2021 - Springer
Timeline Data is gathered according to different time intervals, which are day after day after
week or month after month, for updating properties and rationing institutional resilience it is …
week or month after month, for updating properties and rationing institutional resilience it is …
[HTML][HTML] Solar photovoltaic power prediction using big data tools
Solar photovoltaic (PV) installation has been continually growing to be utilized in a grid-
connected or stand-alone network. However, since the generation of solar PV power is …
connected or stand-alone network. However, since the generation of solar PV power is …
A comparative study of different deep learning models for mid-term solar power prediction
Solar energy is an abundant and renewable form of energy that is the answer to the
increasing energy requirements of today's world. Since the prediction of solar radiation …
increasing energy requirements of today's world. Since the prediction of solar radiation …
Color image design based on machine learning and SVM algorithm
L Bo - Journal of Intelligent & Fuzzy Systems, 2021 - content.iospress.com
In today's society, graphic design, as a popular image processing technology, plays an
increasingly important role in people's lives. In the specific operation process of graphic …
increasingly important role in people's lives. In the specific operation process of graphic …
Analysis of GHI forecasting using seasonal ARIMA
A Kumar Barik, S Malakar, S Goswami… - … Analytics and Innovation …, 2021 - Springer
A precise understanding of solar energy generation is important for many reasons like
storage, delivery, and integration. Global Horizontal Irradiance (GHI) is the strongest …
storage, delivery, and integration. Global Horizontal Irradiance (GHI) is the strongest …