AIMC Topic: Computer Simulation

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An artificial neural network chip based on two-dimensional semiconductor.

Science bulletin
Recently, research on two-dimensional (2D) semiconductors has begun to translate from the fundamental investigation into rudimentary functional circuits. In this work, we unveil the first functional MoS artificial neural network (ANN) chip, including...

A Neural Networks Approach to Determine Factors Associated With Self-Reported Discomfort in Picking Tasks.

Human factors
OBJECTIVE: A neural networks approach has been proposed to handle various inputs such as postural, anthropometric and environmental variables in order to estimate self-reported discomfort in picking tasks. An input reduction method has been proposed,...

Spatial rank-based multifactor dimensionality reduction to detect gene-gene interactions for multivariate phenotypes.

BMC bioinformatics
BACKGROUND: Identifying interaction effects between genes is one of the main tasks of genome-wide association studies aiming to shed light on the biological mechanisms underlying complex diseases. Multifactor dimensionality reduction (MDR) is a popul...

Competency of Neural Networks for the Numerical Treatment of Nonlinear Host-Vector-Predator Model.

Computational and mathematical methods in medicine
The aim of this work is to introduce a stochastic solver based on the Levenberg-Marquardt backpropagation neural networks (LMBNNs) for the nonlinear host-vector-predator model. The nonlinear host-vector-predator model is dependent upon five classes, ...

Optimization of running-in surface morphology parameters based on the AutoML model.

PloS one
Running-in is an important and relatively complicated process. The surface morphology prior to running-in affects the surface morphology following the running-in process, which in turn influences the friction and wear characteristics of the workpiece...

An artificial intelligence model to predict hepatocellular carcinoma risk in Korean and Caucasian patients with chronic hepatitis B.

Journal of hepatology
BACKGROUND & AIMS: Several models have recently been developed to predict risk of hepatocellular carcinoma (HCC) in patients with chronic hepatitis B (CHB). Our aims were to develop and validate an artificial intelligence-assisted prediction model of...

A Joint Model Provisioning and Request Dispatch Solution for Low-Latency Inference Services on Edge.

Sensors (Basel, Switzerland)
With the advancement of machine learning, a growing number of mobile users rely on machine learning inference for making time-sensitive and safety-critical decisions. Therefore, the demand for high-quality and low-latency inference services at the ne...

Potential Fault Diagnosis Method and Classification Accuracy Detection of IGBT Device Based on Improved Single Hidden Layer Feedforward Neural Network.

Computational intelligence and neuroscience
Insulated Gate Bipolar Transistor (IGBT) is a high-power switch in the field of power electronics. Its reliability is closely related to system stability. Once failure occurs, it may cause irreparable loss. Therefore, potential fault diagnosis method...

Intelligent Optimization Algorithm-Based Path Planning for a Mobile Robot.

Computational intelligence and neuroscience
The purpose of mobile robot path planning is to produce the optimal safe path. However, mobile robots have poor real-time obstacle avoidance in local path planning and longer paths in global path planning. In order to improve the accuracy of real-tim...

Intelligent Simulation of Children's Psychological Path Selection Based on Chaotic Neural Network Algorithm.

Computational intelligence and neuroscience
In recent years, there are many problems in the study of intelligent simulation of children's psychological path selection, among which the main problem is to ignore the factors of children's psychological path selection. Based on this, this paper st...