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This article explores the problems of automated retail systems, which named are vending machines. The main problem is the formation of an assortment of a vending machine, the realization of which will bring maximum profit. As a modern analysis tool of consumer demand in retail trade artificial intelligence is regarded. Attention is focused on one of the methods of constructing artificial intelligence...
The aim of the paper is to introduce a new approach for the Regions of Required Quality (RRQ) construction under the Control Systems computer-aided analysis and design. Application of the Artificial Neural Networks (ANNs) as a tool in the proposed techniques is represented under the title “Method of Sensitive Border”. The developed Neural network model of the RRQ-region's border allows one to get...
Recurrent neural networks are represented as non-linear models of dynamic systems. This kind of neural networks is divided into two groups, which are globally and locally recurrent neural networks. Some types are distinguished among globally recurrent networks. The major approximation properties and features of every distinguished type are emphasized. The represented analysis is useful for choosing...
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...
A 3-Axis Gimbal structure is used to inertially stabilize a platform which can be used to track afixed or moving point in space with the help of optical sensors such as Laser, IR or camera installed on the platform. This paper presents a solution to the problem of non-linear indirect relationship between the platform's Euler angles, gimbals' orientation angles and disturbance angles by using a Neural...
On-Line Learning Behavior depend on learning subject self-control learning, collaborative learning, and obtaining of support and help. Based on learning subject, the On-Line learning behavior need the real-time monitoring and the effective instruction to through the evaluation in the learning process. The BP algorithm model of evaluating E-Learning behavior selects the learning behavior which affects...
This paper presents a neural network based approach to the identification and control of an experimental natural circulation loop. The aim of the model is to predict the dynamical evolution of the oscillations, characterizing the system dynamics in some operating conditions and that can cause dangerous flow reversal. The identification of the system was the first step towards the design of an appropriate...
This paper presents an approach to digit recognition using single layer neural network classifier with Principal Component Analysis (PCA). The handwritten digit recognition is an important area of research as there are so many applications which are using handwritten recognition and it can also be applied to new application. There are many algorithms applied to this computer vision problem and many...
In the present article was implemented a maximum sensibility neural network in a reconfigurable logical electronic structure (cell) in which different basic logical functions and combinational logic circuits as comparators, multiplexers and encoders are obtained. This neural network has advantages like easy implementation and a quick learning based on manipulation of the information in place of a...
Neural network architecture designed for large-scale and the generalization is poor, presents a neural network algorithm for fast pruning based on significance analysis. The essence of the method is based on large-scale neural network perceptron as the research object, the constructor error curved surface model to analyze the network connection weights of disturbance on the network output error caused...
Feed forward Multilayer Perceptron (MLP) Neural Networks are universal approximators. Weight adjustment of the connectionist model is crucial to architectures that model systems behavior. This paper developed a neural network for hydrological purposes. Two architectures were developed, investigated, and tested for forecasting rainfall in the rain-fed Sectors in Sudan. A monthly architecture and a...
Topology design of artificial neural networks (AANs) is a complex problem. This paper presents a study of some approaches which derived from a pruning technique (OBS). In the first step, we explicit the corresponding algorithms used to determine the adequate number of neurons and weights for neural structure. In the second step, a comparative study of the presented strategies is also investigated...
Data pre-processing in modeling of neural network (NN) is relatively more complicated and usually manual. Trial and error method is commonly used to determine the number of hidden layer neurons, which is easily affected by human factors and is opportunistic. Relevant training parameters using default value commonly result in lower model accuracy. In this paper, a NN load forecasting model with higher...
This paper presents an algorithm based on a combination of Discrete Wavelet Transforms and back-propagation neural networks for location of interturn faults in a two-winding three-phase transformer. Fault conditions of the transformer are simulated using ATP/EMTP in order to obtain current signals. The training process for the neural network and fault diagnosis decision are implemented by MATLAB....
Auto anti-lock braking system (ABS) bench test is a safe, high-efficiency and low-cost method for ABS performance detection. The key parameters such as slip ratio, adhesion coefficient utilization rate and deceleration can be obtained quickly. In this paper, a classification model based on neural network for ABS bench test results was established. And the detailed BP network structure design process...
By using neural networks, Beijing's water supplied and consumed is forecasted, and connection number and total partial connection number of the set pair analysis (SPA) are obtained. Principal factors and development trend are sequenced based on absolute relative error between sample value xi and predominant value yi so as to set up a mathematics model of forecasting Beijing's water supplied and consumed...
For the research of Chinese word segmentation, the BP algorithm model has a lot of defects such as low convergent velocity, easily falling into local minimum, low velocity and efficiency. In this paper, we proposed a new particle swarm neural network algorithm (NPSO-BP), and used it in Chinese word segmentation. The results show that the speed of the segmentation algorithm is obviously faster than...
Sample database was established and the mapping relationship between span,rise-span ratios and type of shell with minimum weight was simulated by using BP neural network method. The selected typical samples were chosen from hundreds of sectional optimized results based on sequential two-level algorithm from five typical types of reticulated domes. This paper provides a simple lectotype optimization...
Neural network has a problem that learning time becomes so long for real world problems. To achieve fast learning, some researchers proposed to implement a neural network into Wafer Scale Integration (WSI). Since WSI uses one wafer as a parallel computer, a part of defect leads entire system fault. Therefore a defect compensation method is necessary to implement a neural network into WSI. Partial...
Sample database was established and the mapping relationship between span,rise-span ratios and type of shell with minimum weight was simulated by using BP neural network method. The selected typical samples were chosen from hundreds of sectional optimized results based on sequential two-level algorithm from five typical types of reticulated domes. This paper provides a simple lectotype optimization...
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