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Path planning for autonomous mobile robots using multi-objective evolutionary particle swarm optimization.

PloS one
In this article, a new path planning algorithm is proposed. The algorithm is developed on the basis of the algorithm for finding the best value using multi-objective evolutionary particle swarm optimization, known as the MOEPSO. The proposed algorith...

Fin-TS and Fix-TS on fractional quaternion delayed neural networks with uncertainty via establishing a new Caputo derivative inequality approach.

Mathematical biosciences and engineering : MBE
This paper investigates the finite time synchronization (Fin-TS) and fixed time synchronization (Fix-TS) issues on Caputo quaternion delayed neural networks (QDNNs) with uncertainty. A new Caputo fractional differential inequality is constructed, the...

Harris hawks optimization algorithm and BP neural network for ultra-wideband indoor positioning.

Mathematical biosciences and engineering : MBE
Traditional back propagation neural networks (BPNNs) for ultrawideband (UWB) indoor localization can effectively improve localization accuracy, although there is high likelihood of becoming trapped in nearby minima. To solve this problem, the random ...

Finite-time stability of state-dependent delayed systems and application to coupled neural networks.

Neural networks : the official journal of the International Neural Network Society
Finite-time stability and stabilization problems of state-dependent delayed systems are studied in this paper. Different from discrete delays and time-dependent delays which can be well estimated over time, the information of state-dependent delays i...

Rulkov neural network coupled with discrete memristors.

Network (Bristol, England)
The features of memristive-coupled neural networks have been studied extensively in the continuous field. However, the particularities of the discrete domain are rarely mentioned. This paper constructs a discrete memristor with sine-type conductance ...

Prediction of Duration of Traffic Incidents by Hybrid Deep Learning Based on Multi-Source Incomplete Data.

International journal of environmental research and public health
Traffic accidents causing nonrecurrent congestion and road traffic injuries seriously affect public safety. It is helpful for traffic operation and management to predict the duration of traffic incidents. Most of the previous studies have been in a c...

Deep Learning Reconstruction for Accelerated Spine MRI: Prospective Analysis of Interchangeability.

Radiology
Background Deep learning (DL)-based MRI reconstructions can reduce examination times for turbo spin-echo (TSE) acquisitions. Studies that prospectively employ DL-based reconstructions of rapidly acquired, undersampled spine MRI are needed. Purpose To...

Intelligent Sensors for dc Fault Location Scheme Based on Optimized Intelligent Architecture for HVdc Systems.

Sensors (Basel, Switzerland)
We develop a probabilistic model for determining the location of dc-link faults in MT-HVdc networks using discrete wavelet transforms (DWTs), Bayesian optimization, and multilayer artificial neural networks (ANNs) based on local information. Likewise...

NRN-EZ: an application to streamline biophysical modeling of synaptic integration using NEURON.

Scientific reports
One of the fundamental goals in neuroscience is to determine how the brain processes information and ultimately controls the execution of complex behaviors. Over the past four decades, there has been a steady growth in our knowledge of the morphologi...

Early experience with low-pass filtered images facilitates visual category learning in a neural network model.

PloS one
Humans are born with very low contrast sensitivity, meaning that inputs to the infant visual system are both blurry and low contrast. Is this solely a byproduct of maturational processes or is there a functional advantage for beginning life with poor...