Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Maxwell-Boltzmann Distribution: Problem Solving01:20

Maxwell-Boltzmann Distribution: Problem Solving

1.6K
Individual molecules in a gas move in random directions, but a gas containing numerous molecules has a predictable distribution of molecular speeds, which is known as the Maxwell-Boltzmann distribution, f(v).
This distribution function f(v) is defined by saying that the expected number N (v1,v2) of particles with speeds between v1 and v2 is given by
1.6K
Light Acquisition02:16

Light Acquisition

8.5K
In order to produce glucose, plants need to capture sufficient light energy. Many modern plants have evolved leaves specialized for light acquisition. Leaves can be only millimeters in width or tens of meters wide, depending on the environment. Due to competition for sunlight, evolution has driven the evolution of increasingly larger leaves and taller plants, to avoid shading by their neighbors with contaminant elaboration of root architecture and mechanisms to transport water and nutrients.
8.5K
Precipitation Processes01:12

Precipitation Processes

511
The experimental conditions in a gravimetric analysis should be optimized to maximize the particle size and purity of the obtained precipitate. Ideally, the concentration of the precipitating reagent should be low with effective stirring to maintain low relative supersaturation for the growth of large crystals. In homogeneous precipitation, the precipitant is slowly generated by a chemical reaction in the solution to avoid local reagent excesses. For example, urea decomposes gradually to...
511
Precipitation and Co-precipitation01:17

Precipitation and Co-precipitation

1.9K
Precipitation and coprecipitation methods can be used to separate a mixture of ions in a solution. In qualitative inorganic analysis, ions that form sparingly soluble precipitates with the same reagent are separated based on the differences in solubility products. For example, consider the separation of Cu(II) and Fe(II) ions by precipitation as insoluble sulfides. First, copper(II) sulfide is precipitated by the addition of acidic H2S, where the dissociation of H2S is suppressed. Adding H2S...
1.9K
What is Weather?01:07

What is Weather?

18.4K
Overview
18.4K
Generating Electromagnetic Radiations01:10

Generating Electromagnetic Radiations

3.3K
The German physicist Heinrich Hertz (1857–1894) was the first to generate and detect certain types of electromagnetic waves in the laboratory. Starting in 1887, he performed a series of experiments that confirmed the existence of electromagnetic waves and verified that they travel at the speed of light. Hertz used an alternating-current RLC (resistor-inductor-capacitor) circuit that resonated at a known frequency and connected it to a loop of wire. High voltages induced across the gap in...
3.3K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

ITGA5 is overexpressed and promotes tumor progression through SNAI2 in OSCC.

Frontiers in cell and developmental biology·2026
Same author

HFB301001, an OX40-based immunotherapy, drives Treg clearance and CTL activation through optimized OX40 receptor clustering.

Journal for immunotherapy of cancer·2026
Same author

Immunogenic tumor cell death and T-cell-derived IFN-γ elicit tumoricidal macrophages to potentiate OX40 immunotherapy.

Cell reports. Medicine·2026
Same author

Structural optimization and biological evaluation of 5-fluoro-7H-pyrrolo[2,3- d]pyrimidine derivatives as potent FAK inhibitors for the treatment of triple negative breast cancers (TNBC).

European journal of medicinal chemistry·2025
Same author

Evaluation of anti-liver cancer activity and anticancer mechanism of one novel small molecule compound (THY-10A62) targeting FAK pathway.

Frontiers in oncology·2025
Same author

Weakly supervised deep learning for multimodal MRI-TRUS registration: Toward assisting prostate biopsy guidance.

Digital health·2025
Same journal

RETRACTED: Zhang et al. A Novel Framework for Reconstruction and Imaging of Target Scattering Centers via Wide-Angle Incidence in Radar Networks. <i>Sensors</i> 2025, <i>25</i>, 6802.

Sensors (Basel, Switzerland)·2026
Same journal

Enhancing Unsupervised Multi-Source Domain Adaptation for Person Re-Identification via Mixture of Experts and Graph-Based Relation.

Sensors (Basel, Switzerland)·2026
Same journal

Development of an Instrumented Glove for Palmar Pressure Assessment in Kayakers.

Sensors (Basel, Switzerland)·2026
Same journal

Development and Experimental Validation of an Autonomous IoT-Based Monitoring System for Real-Time Water Quality Assessment in the Amazon River.

Sensors (Basel, Switzerland)·2026
Same journal

Semi-Supervised Adversarial Learning Framework for Controller Area Network Bus Intrusion Detection.

Sensors (Basel, Switzerland)·2026
Same journal

Smart Optimization Method for Safety Signs in Innovative Manufacturing Environments Integrating Industrial Field IoT Sensors and Knowledge Graphs.

Sensors (Basel, Switzerland)·2026
See all related articles

Related Experiment Video

Updated: Aug 7, 2025

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
10:46

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

Published on: December 9, 2015

10.7K

A Solar Irradiance Forecasting Framework Based on the CEE-WGAN-LSTM Model.

Qianqian Li1,2, Dongping Zhang1,2, Ke Yan1,2

  • 1Key Laboratory of Electromagnetic Wave Information Technology and Metrology of Zhejiang Province, College of Information Engineering, China Jiliang University, Hangzhou 310018, China.

Sensors (Basel, Switzerland)
|March 11, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces a novel method for solar power forecasting using Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), Wasserstein Generative Adversarial Networks (WGAN), and Long Short-Term Memory (LSTM) networks. The approach significantly improves solar energy generation prediction accuracy.

Keywords:
deep learningsignal decompositionsolar irradiancetime-series forecasting

More Related Videos

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation
08:47

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation

Published on: February 9, 2024

1.5K
Leaf Area Index Estimation Using Three Distinct Methods in Pure Deciduous Stands
09:04

Leaf Area Index Estimation Using Three Distinct Methods in Pure Deciduous Stands

Published on: August 29, 2019

13.6K

Related Experiment Videos

Last Updated: Aug 7, 2025

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
10:46

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

Published on: December 9, 2015

10.7K
Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation
08:47

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation

Published on: February 9, 2024

1.5K
Leaf Area Index Estimation Using Three Distinct Methods in Pure Deciduous Stands
09:04

Leaf Area Index Estimation Using Three Distinct Methods in Pure Deciduous Stands

Published on: August 29, 2019

13.6K

Area of Science:

  • Renewable Energy Systems
  • Artificial Intelligence in Energy
  • Time Series Forecasting

Background:

  • Accurate solar power generation forecasting is crucial for intelligent grid systems due to the rapid expansion of solar energy plants.
  • Existing forecasting methods face challenges in accurately predicting solar output, especially with complex data patterns.

Purpose of the Study:

  • To propose an effective and robust decomposition-integration method for improving two-channel solar irradiance forecasting accuracy.
  • To develop a hybrid model combining CEEMDAN, WGAN, and LSTM for enhanced solar power prediction.

Main Methods:

  • Utilizing Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) to decompose solar output signals into simpler subsequences.
  • Employing Wasserstein Generative Adversarial Network (WGAN) for high-frequency subsequence prediction and Long Short-Term Memory (LSTM) for low-frequency subsequence prediction.
  • Integrating predicted subsequence values to obtain the final solar power generation forecast.

Main Results:

  • The developed CEEMDAN-WGAN-LSTM model demonstrated superior accuracy in solar output prediction compared to traditional methods and other decomposition-integration models.
  • Experimental results showed significant reductions in Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and Root Mean Square Error (RMSE) across all seasons.
  • Specifically, MAE, MAPE, and RMSE decreased by 3.51%, 6.11%, and 2.25%, respectively, compared to a suboptimal model.

Conclusions:

  • The proposed decomposition-integration method effectively enhances solar irradiance forecasting accuracy by leveraging advanced machine learning and deep learning techniques.
  • The hybrid CEEMDAN-WGAN-LSTM model offers a robust solution for accurate solar power prediction in intelligent grid applications.
  • This approach successfully identifies complex dependencies and network topologies for reliable energy forecasting.