AIMC Topic: Computer Simulation

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A Simulation Study to Compare the Predictive Performance of Survival Neural Networks with Cox Models for Clinical Trial Data.

Computational and mathematical methods in medicine
BACKGROUND: Studies focusing on prediction models are widespread in medicine. There is a trend in applying machine learning (ML) by medical researchers and clinicians. Over the years, multiple ML algorithms have been adapted to censored data. However...

Displacement detection with sub-pixel accuracy and high spatial resolution using deep learning.

Journal of medical ultrasonics (2001)
PURPOSE: The purpose of this study was to detect two dimensional and sub-pixel displacement with high spatial resolution using an ultrasonic diagnostic apparatus. Conventional displacement detection methods assume neighborhood uniformity and cannot a...

Research on Classroom Online Teaching Model of "Learning" Wisdom Music on Wireless Network under the Background of Artificial Intelligence.

Computational and mathematical methods in medicine
This article uses a multimodal smart music online teaching method combined with artificial intelligence to address the problem of smart music online teaching and to compensate for the shortcomings of the single modal classification method that only u...

Plugin Framework-Based Neuro-Symbolic Grounded Task Planning for Multi-Agent System.

Sensors (Basel, Switzerland)
As the roles of robots continue to expand in general, there is an increasing demand for research on automated task planning for a multi-agent system that can independently execute tasks in a wide and dynamic environment. This study introduces a plugi...

The New Simulation of Quasiperiodic Wave, Periodic Wave, and Soliton Solutions of the KdV-mKdV Equation via a Deep Learning Method.

Computational intelligence and neuroscience
How to solve the numerical solution of nonlinear partial differential equations efficiently and conveniently has always been a difficult and meaningful problem. In this paper, the data-driven quasiperiodic wave, periodic wave, and soliton solutions o...

The Use of Digital Twins in Finite Element for the Study of Induction Motors Faults.

Sensors (Basel, Switzerland)
Induction motors play a key role in the industrial sector. Thus, the correct diagnosis and classification of faults on these machines are important, even in the initial stages of evolution. Such analysis allows for increased productivity, avoids unex...

Overcoming Challenges of Applying Reinforcement Learning for Intelligent Vehicle Control.

Sensors (Basel, Switzerland)
Reinforcement learning (RL) is a booming area in artificial intelligence. The applications of RL are endless nowadays, ranging from fields such as medicine or finance to manufacturing or the gaming industry. Although multiple works argue that RL can ...

Remaining Useful Life Estimation of Aircraft Engines Using a Joint Deep Learning Model Based on TCNN and Transformer.

Computational intelligence and neuroscience
The remaining useful life estimation is a key technology in prognostics and health management (PHM) systems for a new generation of aircraft engines. With the increase in massive monitoring data, it brings new opportunities to improve the prediction ...

A Novel Complete-Surface-Finding Algorithm for Online Surface Scanning with Limited View Sensors.

Sensors (Basel, Switzerland)
Robotised Non-Destructive Testing (NDT) has revolutionised the field, increasing the speed of repetitive scanning procedures and ability to reach hazardous environments. Application of robot-assisted NDT within specific industries such as remanufactu...

A Bio-inspired trajectory planning method for robotic manipulators based on improved bacteria foraging optimization algorithm and tau theory.

Mathematical biosciences and engineering : MBE
In this paper, a novel bio-inspired trajectory planning method is proposed for robotic systems based on an improved bacteria foraging optimization algorithm (IBFOA) and an improved intrinsic Tau jerk (named Tau-J*) guidance strategy. Besides, the ada...