competitive neural network algorithm
An improved BP neural network algorithm for competitive sports evaluation
... genetic algorithm, the individual with highest fitness in the population at present is possible to participate in crossover and mutation calculation, just with small probability; on the contrary, the lower the ...
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Hybrid imperialistic competitive algorithm incorporated with hopfield neural network for robust 3 satisfiability logic programming
... HNN-3SATICA algorithm has outperformed HNN-3SATES algorithm and ...Hopfield Neural Network, and it is closest to achieving the global minima, regardless of the number of number of neurons ...
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Applying neural network approach with imperialist competitive algorithm for software reliability prediction
... In terms of training the NN structure, variety sets of algorithms can be exploited. BP, GA and Evolutionary algorithm are common learning algorithms. Each of them has some weaknesses which give motivation to ...
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Face recognition system based on imperialist competitive algorithm and neural network (ICANN)
... Video surveillance has acquired wide attention and interest due to the growing concerns about security. Facial recognition in critical surveillance environments to identify potential terrorists and criminals on the watch ...
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Competitive Hopfield Neural Network Model for Evaluating Pedicle Screw Placement Accuracy
... segmentation algorithm for X-ray images analysis. Based on this algorithm, dedicated software is developed within a training system for automatically determining the deviation of the screw insertion ...
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Credit Card Fraud Detection with a Cascade Artificial Neural Network and Imperialist Competitive Algorithm
... Artificial Neural Networks (ANN) [13] are computational models that try to mimic our body’s biological neural networks and can easily adapt to ...a neural network that is an accurate ...
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Application of Neural Network to Game Algorithm
... DOI: 10.4236/jcc.2018.62001 2 Journal of Computer and Communications of interests and mechanisms of conflict resolved, balance and optimizing the in- terests of all parties [1]. The game theory could solve these ...
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Integrating Neural Network and Colonial Competitive Algorithm: A New Approach for Predicting Bankruptcy in Tehran Security Exchange
... to neural network models (NN) (Tam and Kiang, 1992), discrete hazard models (Shumway, 2001), Bayesian network (BN) models (Sarkar and Sriram, 2001), and genetic programming (McKee and Lensberg, ...
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A Hybrid Approach for Software Development Effort Estimation using Neural networks, Genetic Algorithm, Multiple Linear Regression and Imperialist Competitive Algorithm
... genetic algorithm. Cost function in genetic algorithm is called Feature Selection Cost ...the neural network are then set and the function evaluates neural network with function ...
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Optimizing locomotive body structures using imperialist competitive algorithm
... Acceptable error between results of the finite element analysis and experimental analyses was assumed as three percent. The optimization process began after ensuring accuracy of the finite element model. Optimization ...
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Comparative Analysis of ANN-ICA and ANN-GWO for Crop Yield Prediction
... of neural networks can be determined by factors like the quality of the sample, the network structure, and the training parameters ...artificial neural networks- imperialist competitive ...
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Carbon Monoxide Prediction Using Artificial Neural Network And Imperialist Competitive Algorithm
... artificial neural networks (ANN) and evolutionary algorithms, like genetic algorithm, in simulating the nonlinear dynamic of environmental phenomena, have introduced them as powerful alternatives amongst ...
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Artificial Intelligence Approaches for GPS GDOP Classification
... on neural network (NN) and evolutionary algorithms (EAs) for GPS GDOP ...genetic algorithm (GA), particle swarm optimization (PSO), new PSO (NPSO), and imperialist competitive algorithm ...
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Mill Load Control System Based on the Improved Ant Colony Neural Network
... of neural networks were trained using gradient descent algorithm such back propagation algorithm (BP) with a longer convergence time and more probability to fall into local ...colony ...
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Challenges to Multi-Layer Feed Forward Neural Networks in Intrusion Detection
... forward neural networks. The most common used algorithm is the ...neural network. Also it was found that the back propagation algorithm becomes difficult to function effectively when ...
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Neural Network Design - Free Computer, Programming, Mathematics, Technical Books, Lecture Notes and Tutorials
... training neural net- works to perform various ...practical algorithm: the perceptron learning rule. The perceptron network has fundamental limitations, but it is impor- tant for historical reasons ...
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Classification Using Two Layer Neural Network Back Propagation Algorithm
... Dataset consists of 998 records each of which is characterized by nine attributes given in Table 2. [11] pro- posed the classification of malignant and benign tumor feature extraction algorithms based on principal compo- ...
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FACE DETECTION WITH SKIN COLOR AND FEATURES AND RECOGNIZATION USING GENETIC ALGORITHM
... training neural network models from scratch can be high, another feature employed in this work was to guarantee that when a new offspring is generated it does not duplicate any chromosome ...
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DETECTION AND CLASSIFICATION OF DIABETIC RETINOPATHY USING ADAPTIVE BOOSTING AND ARTIFICIAL NEURAL NETWORK
... our network for training purpose. Multiple layered convolutional neural networks are designed and trained with different hyper- parameter values, changing behavior of the training curves are analyzed and ...
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USE OF GENETIC SVM FOR ECG ARRHYTHMIA CLASSIFICATION
... e Neural Network Training: The training to the network is given using a Supervised learning algorithm;back- propogation This algorithm looks for the minimum of the error function in ...
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