Search results for "NEURAL NETWORK"

Performance Evaluation for a Sustainable Supply Chain Management System in the Automotive Industry Using Artificial Intelligence

2020

Increasing the sustainability of a system can be achieved by evaluating the system, identifying the issues and their root cause and solving them. Performance evaluation translates into key performance indicators (KPIs) with a high impact on increasing overall efficacy and efficiency. As the pool of KPIs has increased over time in the context of evaluating the supply chain management (SCM) system&rsquo

Noise effect in a FitzHugh-Nagumo circuit driven by a bichromatic signal

2013

We analyze the response of a nonlinear circuit exactly ruled by the FitzHugh-Nagumo equations. This circuit is submitted to a bichromatic signal including a high frequency and a low frequency. In absence of noise, we show that for an appropriate amplitude of the high frequency driving, the response of the circuit estimated at the low frequency can be optimized via the phenomenon of vibrational resonance. Next, we show that under certain conditions, noise can contribute to the effect of vibrational resonance. Colored noise is also considered. Our experimental results are confirmed by a numerical analysis.

Detector-based visual analysis of time-series data

2015

Mixtures identification of chemical compounds on the basis of their IR spectra by artificial intelligence

2012

Infrared (IR) spectrometric identification of individual chemical compounds from their mixtures is still a challenging process. Therefore, we developed a method in which we use the IR “Fingerprint” spectra of a particular chemical substance followed by artificial intelligence (AI) – based analysis to correctly characterise components of relatively simple chemical mixtures. We describe here the assembly of tools developed especially for this purpose as well as the artificial neural network design together with the requirements that must be met for its proper functioning. To test our approach, we used a mixture of amphetamine and creatinine which are difficult to identify in mixtures by stand…

SEAM PUCKERING EVALUATION METHOD FOR SEWING PROCESS

2014

The paper presents an automated method for the assessment and classification of puckering defects detected during the preproduction control stage of the sewing machine or product inspection. In this respect, we have presented the possible causes and remedies of the wrinkle nonconformities. Subjective factors related to the control environment and operators during the seams evaluation can be reduced using an automated system whose operation is based on image processing. Our implementation involves spectral image analysis using Fourier transform and an unsupervised neural network, the Kohonen Map, employed to classify material specimens, the input images, into five discrete degrees of quality…

Ghost stochastic resonance in FitzHugh–Nagumo circuit

2014

International audience; The response of a neural circuit submitted to a bi-chromatic stimulus and corrupted by noise is investigated. In the presence of noise, when the spike firing of the circuit is analysed, a frequency not present at the circuit input appears. For a given range of noise intensities, it is shown that this ghost frequency is almost exclusively present in the interspike interval distribution. This phenomenon is for the first time shown experimentally in a FitzHugh-Nagumo circuit.

Neural Classification of Compost Maturity by Means of the Self-Organising Feature Map Artificial Neural Network and Learning Vector Quantization Algo…

2019

Self-Organising Feature Map (SOFM) neural models and the Learning Vector Quantization (LVQ) algorithm were used to produce a classifier identifying the quality classes of compost, according to the degree of its maturation within a period of time recorded in digital images. Digital images of compost at different stages of maturation were taken in a laboratory. They were used to generate an SOFM neural topological map with centres of concentration of the classified cases. The radial neurons on the map were adequately labelled to represent five suggested quality classes describing the degree of maturation of the composted organic matter. This enabled the creation of a neural separator classify…

Theoretical and experimental study of two discrete coupled Nagumo chains

2001

We analyze front wave (kink and antikink) propagation and pattern formation in a system composed of two coupled discrete Nagumo chains using analytical and numerical methods. In the case of homogeneous interaction among the chains, we show the possibility of the effective control on wave propagation. In addition, physical experiments on electrical chains confirm all theoretical behaviors.

Seizure Prediction Using EEG Channel Selection Method

2022

Seizure prediction using intracranial electroencephalogram (iEEG) is still challenging because of complicated signals in spatial and time domains. Feature selection in the spatial domain (i.e., channel selection) has been largely ignored in this field. Hence, in this paper, a novel approach of iEEG channel selection strategy combined with one-dimensional convolutional neural networks (1D-CNN) was presented for seizure prediction. First, 15-sec and 30-sec iEEG segments with an increasing number of channels (from one channel to all channels) were sequentially fed into 1D-CNN models for training and testing. Then, the channel case with the best classification rate was selected for each partici…

Assessing the Open Trenches in Screening Railway Ground-Borne Vibrations by Means of Artificial Neural Network

2009

Reducing ground borne vibrations in urban areas is a very challenging task in railway transportation. Many mitigation measures can be considered and applied; among these open trenches are very effective. This paper deals with the study of the effect, in terms of reduction of vertical and horizontal displacements and velocities, of the open trenches. 2D FEM simulations have been performed and several open trench configurations have been analysed varying the main geometric features such as width and depth, distance from the rail, thickness of the soil layer over the rigid bedrock, type of the ground, ratio between the depth of the trench, and the thickness of the soil layer. For quantifying t…