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 Experiment Video

Updated: Jan 13, 2026

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
06:45

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

Published on: October 28, 2022

2.1K

A Rapid Prediction Method for Underwater Vehicle Radiated Noise Based on Feature Selection and Parallel Residual

Fang Ji1, Ziming Li1, Weijia Feng1

  • 1China Ship Research and Development Academy, Beijing 100101, China.

Sensors (Basel, Switzerland)
|January 10, 2026
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Navigation System-Assisted vs Freehand Cannulated Screw Fixation for Femoral Neck Fractures: Protocol for a Multicenter Randomized Controlled Trial.

JMIR research protocols·2026
Same author

Early replication fragile sites are associated with cancer-related CNVs and SNVs in human embryonic stem cells.

Stem cell reports·2026
Same author

Melatonin Rescues Enamel Defects Induced by Maternal Circadian Disruption via Targeting the BMAL1-JNK3 Axis.

International dental journal·2026
Same author

Natural occurrence of ustiloxin A and D in rice in China.

Mycotoxin research·2026
Same author

Risk factors for atherosclerotic plaque formation in MASLD patients: insights from cross-sectional and Mendelian randomization analyses.

Nutrition, metabolism, and cardiovascular diseases : NMCD·2026
Same author

[Expression of Concern] lncRNA HOTTIP facilitates osteosarcoma cell migration, invasion and epithelial-mesenchymal transition by forming a positive feedback loop with c-Myc.

Oncology letters·2026

This study introduces ADE-PNN-ResNet, a novel model for predicting underwater vehicle radiated noise (URN). The data-driven approach achieves high accuracy and speed, offering a practical solution for warship stealth assessment.

Area of Science:

  • Naval Architecture and Marine Engineering
  • Acoustics
  • Artificial Intelligence

Background:

  • Accurate prediction of underwater vehicle radiated noise (URN) is vital for warship stealth.
  • Traditional physics-based models face challenges with complexity and limited prediction capabilities.

Purpose of the Study:

  • To develop a fast and high-precision data-driven model for URN prediction.
  • To overcome the limitations of conventional modeling methods in complexity and accuracy.

Main Methods:

  • Proposed ADE-PNN-ResNet model integrating Adaptive Differential Evolution (ADE) with a Parallel Residual Neural Network (PNN-ResNet).
  • Joint feature selection strategy using ADE for measurement points and frequency bands.
  • Constructed a Parallel Neural Network (PNN) combining Radial Basis Function Neural Network (RBFNN) and Multi-Layer Perceptron (MLP), cascaded via residual connections.
Keywords:
data-drivenfeature selectionneural networkunderwater radiated noise prediction

More Related Videos

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
07:15

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

7.4K

Related Experiment Videos

Last Updated: Jan 13, 2026

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
06:45

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

Published on: October 28, 2022

2.1K
Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
07:15

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

7.4K

Main Results:

  • Achieved absolute prediction error below 3 dB for 96% of 1/3-octave bands (100-2000 Hz) in lake experiments.
  • Demonstrated prediction inference time of only a few seconds.
  • Validated the model using vibration and noise data from a scaled underwater vehicle.

Conclusions:

  • ADE-PNN-ResNet offers a feasible intelligent solution for rapid URN prediction in engineering applications.
  • The model effectively balances prediction accuracy and computational efficiency.
  • This data-driven framework significantly reduces complexity compared to traditional methods.