Parameters used in the Neural Gas algorithm
A genetic algorithm was used in conjunction with the distributed computing network to optimise the parameters of the absorbers
... Genetic Algorithm A GA is a numerical optimisation method based on the principles of natural selection and ...genetics. GAs attempt to manipulate a set of possible solutions until an optimum solution is ...
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BP Neural Network based on PSO Algorithm for Temperature Characteristics of Gas Nanosensor
... Index Terms—gas nanosensor, temperature characteristics, neural network, PSO I. I NTRODUCTION With the development of the electronic and communication technique, sensor technique has been improved greatly ...
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Tuning the parameters of an artificial neural network using central composite design and genetic algorithm
... artificial Neural Network (ANN) is an efficient approach applied to solving a variety of ...optimal parameters for the ANN ...artificial neural network performance measuring criteria and also three ...
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Application of Artificial Neural Network and Genetic Algorithm for Predicting three Important Parameters in Bakery Industries
... layer neural networks with one and two hidden layer respectively were applied and the ones with the best performance are ...Artificial neural networks need a relatively simple structure that can keep their ...
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Evolving convolutional neural network parameters through the genetic algorithm for the breast cancer classification problem
... then used to train the ...is used by Gad and Gad 17 to optimize an ANN network using the ...more parameters to update, we used a larger initial ...
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3. The Structure Used in the Algorithm
... If condition then action where, condition is the criterion that must be satisfied so that the action is carried out, and action is the set of instructions to be executed. There are two basic actions that can be executed: ...
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Tuning the Parameters of a Loading Algorithm
... categorical parameters that show a high degree of synergy, in the sense that it is the collaborative alignment of the entire configuration that results in good performance, rather than the decomposed, optimal ...
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Optimizing the Multilayer Feed Forward Artificial Neural Networks Architecture and Training Parameters using Genetic Algorithm
... Genetic algorithm has been adopted in the neural network to avoid inadequate current trial-and-error approach and to determine a set of initial process parameters for injection moulding ...the ...
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Optimizing Marshall Test Parameters on Asphalt Concrete Using Hybrid Neural Network - Genetic Algorithm Approach
... Abstract — The design of the street should be applied the knowledge of the engineer principles for the density of traffic flow and rapidity in order to reduce the accident. A dilapidated mix-aggregate estimation will ...
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Functional semi-automated segmentation of renal DCE-MRI sequences using a Growing Neural Gas algorithm
... widely used [1]. Several parameters can be non- invasively computed from perfusion curves of different re- gions of interest ...often used in the medical field but few of them have been tested on ...
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DEEP LEARNING ALGORITHM USED IN ROBOTICS
... Advances in deep learning over the last decade have led to a flurry of research in the application of deep artificial neural networks to robotic systems, with at least thirty papers published on the subject ...
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Optimization of machining parameters in wire electrical discharge machine process by combination of genetic algorithm and artificial neural network
... Fig.5 Prediction relative error Optimization model will use ANN model to get MRR value. V. RESULT AND DISCUSSION Because original chromosomes are given randomly, this may induce getting different solution set, so the ...
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Dendritic Cell Algorithm with Optimised Parameters using Genetic Algorithm
... Cell Algorithm (DCA) is a classification algorithm developed for the purpose of anomaly detection based on the danger theory and the functioning of human immune dendritic ...weights used in this ...
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Fuzzy Modeling using Neural Gas
... using Neural Gas Hirofumi Miyajima, Noritaka Shigei, Hiromi Miyajima Abstract—Fuzzy modeling has been extensively ...the parameters by using SDM. On the other hand, Neural Gas (NG) is ...
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Image segmentation with the growing neural gas
... Having a look at the various results that were produced as a result of execution we can clearly deduce two main factors from the results that have been chosen. One of the factors chosen to be tested was the ...
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Corrosion Prediction for Naphtha and Gas System of Atmospheric Distillation Tower Based on Artificial Neural Network and Genetic Algorithm
... and gas system at the top of the atmospheric tower is established by using the strong self-learning ability of BP neural network and the ability of multi factor synergy combined with the actual production ...
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Neural Networks and Back Propagation Algorithm
... Neural Networks (NN) are important data mining tool used for classification and clustering. It is an attempt to build machine that will mimic brain activities and be able to learn. NN usually learns by ...
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A Learning Algorithm For Neural Network Ensembles
... artificial neural networks as learners in a regression context, we show that this method leads to small aggregates with few but very diverse individual ...The algorithm is favorably tested against other ...
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Application of Neural Network to Game Algorithm
... widely used in all aspects of ma- cro-decision-making strategy and micro-decision-making ...of neural network, and the establishment of the game algorithm of neural net- work was also ...on ...
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A Review for Materials Used in Gas Turbine Blades
... the inlet angle and deviation for the outlet angle. The goal with the aerodynamic design of the airfoils is to minimize the aerodynamic related losses but still fulfil structural and manufacturing limitations and, if ...
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