AIMC Topic: Algorithms

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Self-organizing maps based on limit cycle attractors.

Neural networks : the official journal of the International Neural Network Society
Recent efforts to develop large-scale brain and neurocognitive architectures have paid relatively little attention to the use of self-organizing maps (SOMs). Part of the reason for this is that most conventional SOMs use a static encoding representat...

Online monitoring and control of particle size in the grinding process using least square support vector regression and resilient back propagation neural network.

ISA transactions
Particle size soft sensing in cement mills will be largely helpful in maintaining desired cement fineness or Blaine. Despite the growing use of vertical roller mills (VRM) for clinker grinding, very few research work is available on VRM modeling. Thi...

Fully probabilistic control for stochastic nonlinear control systems with input dependent noise.

Neural networks : the official journal of the International Neural Network Society
Robust controllers for nonlinear stochastic systems with functional uncertainties can be consistently designed using probabilistic control methods. In this paper a generalised probabilistic controller design for the minimisation of the Kullback-Leibl...

Classification of lung cancer using ensemble-based feature selection and machine learning methods.

Molecular bioSystems
Lung cancer is one of the leading causes of death worldwide. There are three major types of lung cancers, non-small cell lung cancer (NSCLC), small cell lung cancer (SCLC) and carcinoid. NSCLC is further classified into lung adenocarcinoma (LADC), sq...

Dynamics of neural networks over undirected graphs.

Neural networks : the official journal of the International Neural Network Society
In this paper we study the dynamical behavior of neural networks such that their interconnections are the incidence matrix of an undirected finite graph G=(V,E) (i.e., the weights belong to {0,1}). The network may be updated synchronously (every node...

Improving the Mann-Whitney statistical test for feature selection: an approach in breast cancer diagnosis on mammography.

Artificial intelligence in medicine
OBJECTIVE: This work addresses the theoretical description and experimental evaluation of a new feature selection method (named uFilter). The uFilter improves the Mann-Whitney U-test for reducing dimensionality and ranking features in binary classifi...

Identifying predictive features in drug response using machine learning: opportunities and challenges.

Annual review of pharmacology and toxicology
This article reviews several techniques from machine learning that can be used to study the problem of identifying a small number of features, from among tens of thousands of measured features, that can accurately predict a drug response. Prediction ...

Active learning for semi-supervised clustering based on locally linear propagation reconstruction.

Neural networks : the official journal of the International Neural Network Society
The success of semi-supervised clustering relies on the effectiveness of side information. To get effective side information, a new active learner learning pairwise constraints known as must-link and cannot-link constraints is proposed in this paper....

Noninvasive blood glucose sensing using near infra-red spectroscopy and artificial neural networks based on inverse delayed function model of neuron.

Journal of medical systems
In this paper, a non-invasive blood glucose sensing system is presented using near infra-red(NIR) spectroscopy. The signal from the NIR optodes is processed using artificial neural networks (ANN) to estimate the glucose level in blood. In order to ob...