Search results for " Mathematics"

Artificial Neural Networks and Linear Discriminant Analysis:  A Valuable Combination in the Selection of New Antibacterial Compounds

2004

A set of topological descriptors has been used to discriminate between antibacterial and nonantibacterial drugs. Topological descriptors are simple integers calculated from the molecular structure represented in SMILES format. The methods used for antibacterial activity discrimination were linear discriminant analysis (LDA) and artificial neural networks of a multilayer perceptron (MLP) type. The following plot frequency distribution diagrams were used: a function of the number of drugs within a value interval of the discriminant function and the output value of the neural network versus these values. Pharmacological distribution diagrams (PDD) were used as a visualizing technique for the i…

A neural network-based approach to determine FDTD eigenfunctions in quantum devices

2009

This article combines a Neural Network (NN) algorithm with the Finite Difference Time Domain (FDTD) technique to estimate the eigenfunctions in quantum devices. A NN based on the Least Mean Squares (LMS) algorithm is combined with the FDTD technique to provide a first approach to the confined states in quantum wires. The proposed technique is in good agreement with analytical results and is more efficient than FDTD combined with the Fourier Transform. This technique is used to cal- culate a numerical approximation to the eigenfunctions associated to quan- tum wire potentials. The performance and convergence of the proposed technique are also presented in this article. © 2009 Wiley Periodica…

Hybrid Particle Swarm Optimization With Genetic Algorithm to Train Artificial Neural Networks for Short-Term Load Forecasting

2019

This research proposes a new training algorithm for artificial neural networks (ANNs) to improve the short-term load forecasting (STLF) performance. The proposed algorithm overcomes the so-called training issue in ANNs, where it traps in local minima, by applying genetic algorithm operations in particle swarm optimization when it converges to local minima. The training ability of the hybridized training algorithm is evaluated using load data gathered by Electricity Generating Authority of Thailand. The ANN is trained using the new training algorithm with one-year data to forecast equal 48 periods of each day in 2013. During the testing phase, a mean absolute percentage error (MAPE) is used …

State classification for autonomous gas sample taking using deep convolutional neural networks

2017

Despite recent rapid advances and successful large-scale application of deep Convolutional Neural Networks (CNNs) using image, video, sound, text and time-series data, its adoption within the oil and gas industry in particular have been sparse. In this paper, we initially present an overview of opportunities for deep CNN methods within oil and gas industry, followed by details on a novel development where deep CNN have been used for state classification of autonomous gas sample taking procedure utilizing an industrial robot. The experimental results — using a deep CNN containing six layers — show accuracy levels exceeding 99 %. In addition, the advantages of using parallel computing with GP…

Increasing sample efficiency in deep reinforcement learning using generative environment modelling

2020

Global exponential stability of delayed Markovian jump fuzzy cellular neural networks with generally incomplete transition probability

2014

The problem of global exponential stability in mean square of delayed Markovian jump fuzzy cellular neural networks (DMJFCNNs) with generally uncertain transition rates (GUTRs) is investigated in this paper. In this GUTR neural network model, each transition rate can be completely unknown or only its estimate value is known. This new uncertain model is more general than the existing ones. By constructing suitable Lyapunov functionals, several sufficient conditions on the exponential stability in mean square of its equilibrium solution are derived in terms of linear matrix inequalities (LMIs). Finally, a numerical example is presented to illustrate the effectiveness and efficiency of our res…

A COMPARATIVE STUDY OF PHENOMENOLOGICAL MODELS OF MR BRAKE BASED ON NEURAL NETWORKS APPROACH

2013

In this paper a full-scale commercially available magnetorheological (MR) brake installed in a semi-active suspension (SAS) system is modeled and simulated. Two well-known phenomenological hysteresis models are explored: Bouc–Wen and Dahl ones. In particular, influence of their parameters on the response is evaluated and assessed. The next step is to introduce the artificial neural networks and discuss their application in the field of systems identification. Subsequently, two feedforward neural networks are created and trained to estimate parameters characterizing each of the MR damper models described. The semi-active suspension (SAS) system equipped with a MR brake is described and the …

Problems of coding stereo images in human memory

2010

This paper discusses the memorization and recall by man of a sequence of planar or stereoscopic images, including six frames that contain a planar strip (8×8 positions of the stimulus) or a volume strip (8×4×2 positions). At the recall stage, the subject chose between the stimulus and three distractors in each frame. It is shown that the times for recognition and recall are less for volume stimuli, while the percent of correct responses is greater for planar stimuli. For volume stimuli, the distribution of errors depends on the disparity between the target and the selected distractor. A model based on a heteroassociative neural network reproduces the error distribution for planar but not fo…

Topological systems and Artin glueing

2012

Abstract Using methods of categorical fuzzy topology, the paper shows a relation between topological systems of S. Vickers and Artin glueing of M. Artin. Inspired by the problem of interrelations between algebra and topology, we show the necessary and sufficient conditions for the category, obtained by Artin glueing along an adjoint functor, to be (co)algebraic and (co)monadic, incorporating the respective result of G. Wraith. As a result, we confirm the algebraic nature of the category of topological systems, showing that it is monadic.

Caracterización del curriculum evaluado en matemática en sexto año básico. Un estudio descriptivo en Valparaíso, Chile

2014

Este artículo pretende dar cuenta de los principales resultados de la investigación denominada Caracterización del curriculum evaluado en sexto año básico en matemática: orientaciones para la formación inicial y continua de profesores y profesoras, cuyo objetivo principal fue describir y analizar lo que se evalúa y cómo se evalúa en matemática en dicho nivel en la región de Valparaíso, Chile. Se analizaron 103 pruebas escritas de matemática conducentes a calificación, pertenecientes a 27 establecimientos educacionales. A dichas pruebas, y a sus respectivas 2516 preguntas, se les aplicó un conjunto de códigos referido tanto a aspectos formales como de contenidos y habilidades matemáticas. S…