evolutionary neural network approach
An Optimum Neural Network for Evolutionary Aerodynamic Shape Design
... for neural network is the feed forward Multi-Layer Perceptron (MLP) and the most popular method for training the network is the back propagation method (BP) ...a network contains the input, ...
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Evolutionary extreme learning machine for the interval type-2 radial basis function neural network: A fuzzy modelling approach
... an Evolutionary Extreme Learning Machine (E-ELM) that is based on Particle Swarm Optimisation (PSO) and Extreme Learning Machine (ELM) theory is extended to the Interval Type-2 Radial Basis Function Neural ...
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Detection of Tumor in Mammographic Images by RBF Neural Network and Multi Population Genetic Algorithm
... hybrid approach for tumor detection in medical ...Artificial neural networks mainly arises from their potential ability to perform interesting computational tasks, it had to adopt themselves under unknown ...
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PERFORMANCE ANALYSIS OF HOPFIELD MODEL OF NEURAL NETWORK WITH EVOLUTIONARY APPROACH FOR PATTERN RECALLING
... The simulation results (i.e. tables 4-7) are indicating that genetic algorithm has more success rate then the Hebbian rule for recalling the taken set of objects, which are containing 0, 1, 2, and 3 bit errors from ...
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An Evolutionary Approach: Analysis of Artificial Neural Networks
... the network. Even without being told whether it's right or wrong, the network still must have some information about how to organize ...the network topology and learning ...a network until a ...
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Testing Currency Predictability Using An Evolutionary Neural Network Model
... the neural network. In the string representation approach there is need for a function that codes a network to a string and another one that decodes the string back to the network, in ...
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Implementation of Evolutionary Computing Techniques for Cancer Diagnosis Using Digital Signal Processor
... logic, Neural Network, Genetic algorithm and adaptive neuro fuzzy inference system approaches have been used earlier in the computerized diagnostic system for cancer ...of Evolutionary computing ...
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An evolutionary algorithm based Feature extraction and selection to Persian and Arabic Handwritten Recognition
... including neural networks and ant colony optimization has been presented in which neural network has been used as a classifier function used in ant colony optimization ...hybrid approach for ...
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Metrics to guide a multi-objective evolutionary algorithm for ordinal classification
... optimization approach in the context of ordinal ...multi-objective evolutionary algorithm optimizes a artificial neural network ordinal model with different pairs of metrics combinations, and ...
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Diagnosis of Breast Cancer by Combining the Techniques of Data Mining and Artificial Immune System
... new approach to the LA-VQIS algorithm for diagnosis of breast cancer by combining two competitive and evolutionary ...the neural network by an artificial safety ...the neural ...
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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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Bacterial foraging optmization algorithm for neural network learning enhancement
... such as Adaptive Tuning of PID Controllers by BFOA for Multivariable System (Kim and Cho, 2005). This technique can also potentially produce effective solutions to very large scale problems. However, BFOA is used to ...
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Curriculum Vitae of Antonia Azzini
... • November 2003 – November 2006 she was in her course for Ph.D. degree in Computer Science, at the Information Technology Department, at the University of Milan. The research activity developed in the soft-computing ...
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A Neural Network Approach for ECG Classification
... and neural network for signal classification are those techniques which used in this pattern recognition ...layer network structure with 25 inputs, 5 neurons in the output layer and 5 neurons in its ...
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Energy Efficient Neural Network Technique to Recover Collision in WSN
... the network, the vulnerability is the data integrity requirement and the layer used is the link ...the network or total degradation if the attack is applied in multiple precise locations in the ...
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Evaluating Neural Machine Translation in English Japanese Task
... evaluate Neural Machine Translation (NMT) models in English-Japanese translation ...Various network architectures with dif- ferent recurrent units are ...
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Economic Geography and the Evolution of Networks
... a network so defined implies the same kind of relationship for each tie, analytical emphasis is put on the structural effects of network position on ...
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Modeling and Solving the Multitrip Multiobjective Pollution Routing Problem on Urban Road Networks
... road network is first pre-processed to identify and discard all proven to be redundant paths between the pairs of the required nodes ...a network reduction approach that basically works by ...
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Applying Linear Regression and Neural Network Meta-Models for Evolutionary Algorithm Based Simulation Optimization
... Most simulations are stochastic in nature and therefore produce stochastic output as stated in Chapter 2. This additional level of complexity (i.e., noisy solution values) may confound other factors. Therefore the first ...
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A Holistic Review of Soft Computing Techniques
... Koza in [119] invented Genetic programming (GP) by extending the capability of genetic algorithm which uses the ideas and terms of biological evolution to handle a complex problem with a model for testing and selecting ...
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