AIMC Topic: Neural Networks, Computer

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Application of fuzzy neural networks for modeling of biodegradation and biogas production in a full-scale internal circulation anaerobic reactor.

Journal of environmental science and health. Part A, Toxic/hazardous substances & environmental engineering
This paper presents the development and evaluation of three fuzzy neural network (FNN) models for a full-scale anaerobic digestion system treating paper-mill wastewater. The aim was the investigation of feasibility of the approach-based control syste...

A neurodynamic approach to convex optimization problems with general constraint.

Neural networks : the official journal of the International Neural Network Society
This paper presents a neurodynamic approach with a recurrent neural network for solving convex optimization problems with general constraint. It is proved that for any initial point, the state of the proposed neural network reaches the constraint set...

Clustering-based classification of road traffic accidents using hierarchical clustering and artificial neural networks.

International journal of injury control and safety promotion
Artificial neural networks (ANNs) have been widely used in predicting the severity of road traffic crashes. All available information about previously occurred accidents is typically used for building a single prediction model (i.e., classifier). Too...

Emergence of low noise frustrated states in E/I balanced neural networks.

Neural networks : the official journal of the International Neural Network Society
We study emerging phenomena in binary neural networks where, with a probability c synaptic intensities are chosen according with a Hebbian prescription, and with probability (1-c) there is an extra random contribution to synaptic weights. This new te...

An Incremental Radial Basis Function Network Based on Information Granules and Its Application.

Computational intelligence and neuroscience
This paper is concerned with the design of an Incremental Radial Basis Function Network (IRBFN) by combining Linear Regression (LR) and local RBFN for the prediction of heating load and cooling load in residential buildings. Here the proposed IRBFN i...

Cultivar classification of Apulian olive oils: Use of artificial neural networks for comparing NMR, NIR and merceological data.

Food chemistry
The development of an efficient and accurate method for extra-virgin olive oils cultivar and origin authentication is complicated by the broad range of variables (e.g., multiplicity of varieties, pedo-climatic aspects, production and storage conditio...

Characterization of neural network generalization in the determination of pH and anthocyanin content of wine grape in new vintages and varieties.

Food chemistry
The generalization ability of hyperspectral imaging combined with neural networks (NN) in estimating pH and anthocyanin content during ripening was evaluated for vintages and varieties not employed in the NN creation. A NN, from a previously publishe...

Automatic 3D liver location and segmentation via convolutional neural network and graph cut.

International journal of computer assisted radiology and surgery
PURPOSE: Segmentation of the liver from abdominal computed tomography (CT) images is an essential step in some computer-assisted clinical interventions, such as surgery planning for living donor liver transplant, radiotherapy and volume measurement. ...

Multistability of complex-valued neural networks with discontinuous activation functions.

Neural networks : the official journal of the International Neural Network Society
In this paper, based on the geometrical properties of the discontinuous activation functions and the Brouwer's fixed point theory, the multistability issue is tackled for the complex-valued neural networks with discontinuous activation functions and ...

Evaluating the predictability of PM grades in Seoul, Korea using a neural network model based on synoptic patterns.

Environmental pollution (Barking, Essex : 1987)
As of November 2014, the Korean Ministry of Environment (KME) has been forecasting the concentration of particulate matter with diameters ≤ 10 μm (PM) classified into four grades: low (PM ≤ 30 μg m), moderate (30 < PM ≤ 80 μg m), high (80 < PM ≤ 150 ...