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Examines the use of artificial feedforward neural networks and GRNN type networks in solving prediction problems. Exemplified by student research, the authors conducted the study on the choice of the type of neural network that is most suitable for the solution of such problems. The article desctibes the set-up and the training of generalized regression neural network of and feedforward neural network...
In this paper, a sequential and partially parallel Fuzzy Adaptive Resonance Theory (ART) neural network (NN) are simulated. Simulations are performed in Matlab environment. According to simulation results, partially parallel Fuzzy ART NN is capable to reach by order higher speed of data processing than its sequential counterpart.
Traffic prediction systems are currently the most important techniques, as they can be wildly applied in different aspects. Given a set of past traffic data, a traffic prediction system is able to predict the future traffic conditions. However, the existing traffic prediction systems are hard to implement and are quite expensive. Hence, this work proposed a Matlab-based traffic prediction system,...
In this paper, General Purpose Graphical Processing Unit (GPGPU) based concurrent implementation of handwritten digit classifier is presented. Different styles of handwriting make it difficult to recognize a pattern but using neural network, it is not a difficult task to perform. Different softwares like torch and MATLAB provide the support of multiple training algorithms to train a network. By choosing...
Noise reduction has always been an important part of any control, acquisition or processing task. In order to increase the usage of some smaller and cheaper, but on the other hand less precise sensor solutions, it is necessary to incorporate some signal processing techniques for noise reduction. Nowadays soft computing techniques such as neural networks are widely used in many signal processing applications...
Artificial To better achieve character recognition, analyze the impact of noise character. BP neural network application describes the process of character recognition, and the corresponding algorithm improvements. Created with MATLAB and training the neural network to identify the different samples, combined toolbox simulink simulation module, so that the character recognition to get better recognition...
We analyze workload traces from production data centers and focus on their VM usage patterns of CPU, memory, disk, and network bandwidth. Burstiness is a clear characteristic of many of these time series: there exist peak loads within clear periodic patterns but also within patterns that do not have clear periodicity. We present PRACTISE, a neural network based framework that can efficiently and accurately...
Although the basic method of cognitive reliability and error analysis method (CREAM) is widely used, there are still a lot of problems, for example, there is no consideration of the problems that CPC has different weights in different industrial environments and the process of determining control mode is not smooth. Therefore, the prediction of human error probability (HEP) in the basic method is...
On the nowadays society exist a lot of communication problems, particularly when the persons has sensory disabilities as deafness or blindness. This problem take place at the moment of interpreting the sign language. The present paper shows the development of a current research project that integrates an intelligent system in the recognition of images and its reproduction in hardware interpretations...
This research aims at introduction of a hand gesture recognition based system to recognize real time gestures in natural environment and compare patterns with image database for matching of image pairs to trigger unlocking of mobile devices. The efforts made in this direction during past relating to security systems for mobile devices has been a major concern and methods like draw pattern unlock,...
The use of artificial neural networks has enabled applications that would be impossible to achieve with conventional electronics, through to versatility that them have, they can be configured as needed and use as required such as classifiers, adaptive filters, controllers and predictors. This paper describes a experimental implementation of virtual speed sensor for DC motor using back-propagation...
Rising admissions in the South African institutions of higher education have enlarged student-to-lecturer ratios and increased the lecturer's workload, already burdened by administrative tasks. After marking tests, lecturers usually fill in a document called the cover page where the student's number, name and marks according to the questions are placed. Once this is done, they will have to recopy...
Predictive analytics of the traffic flow is paid more attention by the traffic engineering experts and relevant departments. However, how to forecast traffic volume still is an important problem affecting the traffic theoretical and practical analysis. Firstly, this paper set up a three layers BP neural network basing on the actual situation to introduce the modeling process of the neural network...
In order to solve the problems existing in the fault diagnosis of tank fire control system, such as bigger subjectivity and less accuracy, a fault diagnosis model based on BP (Back Propagation) is studied. The working conditions of tank fire control system are described with a group of state parameters. A fault diagnosis model is established and a self adaptive variable BP learning algorithm is designed...
Based on the analysis of The BP Neural Network's structrue and drawbacks, the article uses the Genetic Algorithms to optimize initial weights and thresholds. It still uses function simulation to compare these two neural networks based on the MATLAB. The results show that GA-BP neural networks can reduce the function time and make it more scientific.
Combination of genetic algorithms and neural network intelligence technology, use of neural networks as a model, conversion of GPS Height, proposed the basic idea of the algorithm and the algorithm implementation process, and calculated by example. The results show that the algorithm used for better accuracy of GPS height transformation, has some practical value.
Wasting of electric and water, when we use washing machine, has become an important issue in life, how to reduce water consumption charge electric washing machine is an important task. The washing machine fuzzy controller neural network is researched deeply, which is based on fuzzy logic, neural network and its learning algorithm. The BP neural network is combined with fuzzy control and experiments...
The geological information of logging data is very important for people to determine oil reserves and make the plan of exploitation. So it is essential to identify litho logy of the logging data. Neural network with self-organizing, self-learning and the ability of highly non-linear mapping has been widely used in the field of classification. It has achieved good results. Using self-organizing and...
Based on ergonomics, fuzzy theory and BP neural network, weighted integrated comfort index WICI is proposed in the paper. WICI is calculated as the weighted sum of integrated comfort indices which gained by the data recorded in different periods of wheelchair assessment experiments. The integrated comfort index ICI is the output of a trained BP neural network. The inputs of the network are the main...
A BP network model for transformer fault diagnosis is established based on the MATLAB environment in this paper. A large number of data samples are collected and tested, L_M algorithm is used for training samples and simulation in network model. The actual output is gained and made comparative study with the expected output. Finally, it confirms that this network model has a high accuracy and can...
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