evolutionary neural network algorithm
Detection of Tumor in Mammographic Images by RBF Neural Network and Multi Population Genetic Algorithm
... Artificial neural networks mainly arises from their potential ability to perform interesting computational tasks, it had to adopt themselves under unknown situations by the means their training ...The ...
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CNC Thermal Compensation Based on Mind Evolutionary Algorithm Optimized BP Neural Network
... the neural network models needs a large amount of samples for conducting trainings, and first of all, we needed to collect the sample data; and this Paper conducted relevant data acquisition with the axis X ...
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An evolutionary algorithm based Feature extraction and selection to Persian and Arabic Handwritten Recognition
... genetic algorithm and simulated annealing has been used in [Saberi ...genetic algorithm have been used for better recognition of Persian handwritten ...including neural networks and ant colony ...
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A Hybrid System Based on Neural Network and Immune Co-Evolutionary Algorithm for Garment Pattern Design Optimization
... hybrid algorithm (NN-ICEA) based on Neural Network (NN) and immune co-evolutionary algorithm (ICEA) to predict the fit of the garments and search optimal ...
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Time Series Forecasting using Evolutionary Neural Network
... training algorithm is to minimize the approximation error and it is going to be a multimodal search ...genetic algorithm (GA) [17], particle swarm optimization (PSO) [18], ant colony optimization (ACO) ...
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Hybridization of Neural Network-cum-Evolutionary Algorithm variants for Fraud Detection in Credit Cards Online Transaction
... than a fuzzy model for the same system, when the MFs were heuristically defined.PSO has no evolution operators such as crossover and mutation. The researchers in [7] developed an hybridized system (particle swarm ...
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FIR Digital Filter and Neural Network Design using Harmony Search Algorithm
... In evolutionary computation, differential evolution is a method that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of ...
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Differential evolution for neural networks learning enhancement
... Artificial Neural Network (ANN) ...of neural network ...forward neural network to enhance the learning process and the network learning is validated in terms of ...
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Backpropagation Neural Network Based on Local Search Strategy and Enhanced Multi-objective Evolutionary Algorithm for Breast Cancer Diagnosis
... multiobjective evolutionary method hybrid with a local search approach to enhance the backpropagation neural ...multiobjective evolutionary algorithms, which is a non-dominated sorting genetic ...
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Applying Linear Regression and Neural Network Meta-Models for Evolutionary Algorithm Based Simulation Optimization
... requires a large population and utilizes the computer to generate many points during each generation. Many individuals are often poor and will die off in subsequent generations. Also early in the search, the GA just ...
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Implementation of Evolutionary Computing Techniques for Cancer Diagnosis Using Digital Signal Processor
... implement Evolutionary Computing (EI) techniques like Fuzzy Logic, Genetic Algorithm, Neural Network, and Adoptive Neuro-Fuzzy Inference System (ANFIS) for diagnosis of cancer using ...
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Vol 9, No 1 (2014)
... Genetic Algorithm provides evolutionary characteristics and hybridization with fuzzy logic and neural ...Genetic Algorithm along with advantages of Genetic ...Genetic Algorithm. It ...
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FLEXIBLE SHARING IN DHT BASED P2P NETWORKS USING METADATA OF RESOURCE
... new algorithm for computing the ML estimator of the direction of multiples source in the far field by using NN ....The algorithm is iterative. It over-perform traditional algorithm in the aspect of ...
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Classification Using Two Layer Neural Network Back Propagation Algorithm
... layer neural network back propagation ...propagation algorithm is used to train the neural ...layer neural networks outperform the previous work in terms of ...layer neural ...
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Hybrid soft computing systems for electromyographic signals analysis: a review
... However, SVM was originally developed for solving regression and binary classification problems [46]. Several techniques have been proposed to extend a binary classifier to multi-class problems, including one-against-all ...
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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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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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Neural Network based LEACH Clustering Algorithm in WSN
... Yu Gu et al. [2013] discussed a good framework for examining this mutual sink mobility, redirecting, delay, and therefore on. Then, we generalize these alternatives and propose a polynomial-time optimum algorithm ...
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Neural Network Design - Free Computer, Programming, Mathematics, Technical Books, Lecture Notes and Tutorials
... each network input, the algorithm is only given a ...to network inputs ...a network if you don’t know what it is supposed to do? Most of these algorithms perform some kind of clustering ...
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Application of Neural Network to Game Algorithm
... of neural network, and the establishment of the game algorithm of neural net- work was also ...on neural network is a powerful tool to solve the above ...
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