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The traditional neural network is unavoidable to present local extreme value question, may result in failing training. On the basis of quantization of weapon system safe index, it has adopted neural network based on improved genetic algorithm to set up the systematic safety evaluation model of the weapon. It utilizes improved genetic algorithm to optimize the weight of neural network and get the final...
In order to improve the detection rate of T wave, and to solve the problem that the back propagate neural network (BPNN) is invalid when these initial weight and threshold values of BP neural network are chosen impertinently (Objective), Genetic Algorithms (GA)'s characteristic of getting whole optimization value was combined with BP's characteristic of getting local precision value with gradient...
In order to give the computer the ability to play against human opponents, one could utilize the Alpha-Beta algorithm. However, this algorithm has several limitations restricting its playing capabilities. Over the years, many variants of this algorithm were developed, among them a couple that make use of neural networks: a neural network to focus the search in the game tree, and a neural network trained...
A neural network model with adaptive structure for image annotation is proposed in this paper. The adaptive structure enables the proposed model to utilize both global and regional visual features, as well as correlative information of annotated keywords for annotation. In order to achieve an approximate global optimum rather than a local optimum, both genetic algorithm and traditional back-propagation...
Recent advances in microarray technology allow an unprecedented view of the biochemical mechanisms contained within a cell. Deriving useful information from the data is still proving to be a difficult task. In this paper a novel method based on a multi-objective genetic algorithm that discovers relevant sets of genes and uses a neural network to create rules using the evolved genes is described. This...
Operating in critical environments is an extremely desired feature for fault-tolerant embedded systems. In addition, due to design test and validation complexity of these systems, faster and easier development methods are needed. Evolvable Hardware (EHW) is a development technique that, using reconfigurable hardware, builds systems that reconfiguration part is under the control of an Evolutionary...
Using microfossil-based transfer functions, domain scientists from the field of pale oceanography seek to reconstruct environmental conditions at various times in the past. This is accomplished by first determining a quantitative relationship between a forcing function, such as temperature, and the modern for aminiferal response using a calibration data set based on environmental data from an oceanographic...
This paper focuses on the Genetic Algorithm learning paradigm applied to train the ANNs for balancing the cart-pole balancing system. The studied system is a classic control problem namely “cart-pole” problem. We will apply the unconventional techniques Artificial Neural Network, Genetic Algorithm and Fuzzy Logic to a classic control problem "cart-pole”. In this paper we have tried to train the...
It is very important to forecast the ice thickness of Transmission Line for the safe operation of transmission network. The author had introduced artificial neural network(ANN) to the prediction of the ice thickness of transmission line, and proposed a predictive model based on GA and BP addresses on the defects of BP network includes slow convergence and easiness of running to local minimum, and...
One of the major issues concerning the Artificial Neural Networks (ANNs) design is a proper adjustment of the weights of the network. There have been a number of studies comparing the performance of evolutionary and gradient based ANNs learning. But the results of the studies, sometime conflicting to each other although the same and standard dataset development had been used. Motivated by this finding,...
Applications of neural network were widely used in construct project cost estimate. Aim at handling weakness of poor convergence and insufficient forecast, an improved fuzzy neural network method based on SOFM (self-organizing feature map) and GA (genetic algorithm) was proposed to replace the fashionable T-S fuzzy neural network. The method illustrated how to apply SOFM and GA to improve the fault...
This paper describes a method using image processing and genetic algorithm-neural network (GA-NN) for automated Mycobacterium tuberculosis detection in tissues. The proposed method can be used to assist pathologists in tuberculosis (TB) diagnosis from tissue sections and replace the conventional manual screening process, which is time-consuming and labour-intensive. The approach consists of image...
In this paper, a novel approach for online motor fault diagnosis is proposed based on artificial neural network (ANN) trained by immune clustering and genetic algorithm (IGA). The IGA is employed to adaptively optimize the structure of the radial basis function neural network (RBFNN). The clonal selection principle is responsible for how the centres will represent the training data set. The immune...
The deformation of sheet metal is so complicated that the prediction of springback will cost much time with FEM and the results may not match the facts. So it tried to build a function relationship between the springback and the craft parameters with artificial neural network (ANN) in this paper. And for improving the property of prediction it took research on the ANN. It introduced the GA to solve...
Though several approaches have already been proposed in the literature to evolve neural network topologies for solving a wide range of machine learning tasks, this paper presents an alternative one, capable of evolving arbitrarily connected feed forward neural networks (ACFNNs), including linear and nonlinear neurons. A genetic algorithm is conceived to adjust the topology and also to perform variable...
In this paper, we propose a correlation method to assess image quality based on support vector machine (SVM) and genetic algorithm (GA). Instead of the simple linear function to correlate objective indicators with subjective scores of images, we introduce SVM for the correlation function, make GA as the search algorithm, and finally get the image quality assessment model. The results of experiments...
The habitual purpose of data mining is prediction, one of the most direct real-world applications. There are many technologies available to data mining in literature and they achieved some results with reasonable accuracies. This paper designs and implements an advanced model based on fuzzy inference system, namely Standard Additive Model (SAM) for forecasting the output of any record given the input...
Inspired by the genetic algorithm (GA) and wavelet neural networks, a novel modified GA algorithm is proposed for finding the optimal number of hidden layer as well as the networks parameters. The efficacy of the proposed algorithm in function approximation is demonstrated through theoretical analysis and experimental results.
Accurate weather forecasting is important in today's world as agricultural and industrial sectors are largely dependent on the weather conditions. Secondly, it is used to warn about natural disasters. Due to non-linearity in climatic physics, neural networks are suitable to predict these meteorological processes. Back Propagation algorithm using gradient descent method is the most important algorithm...
The discrimination of passive Ultra High Frequency (UHF) Radio Frequency Identification (RFID) system can be affected by several factors. To measure the discrimination of UHF RFID systems, a measurement system based on virtual instruments which can adjust the speed, position and angle of tag is built in this paper. The learning vector quantization neural network based on genetic algorithm (GA-LVQ)...
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