Utilising the Genetic Neural Mathematical Method
Fuzzy neural networks with genetic algorithm-based learning method
... artificial neural networks based on granules for both crisp and uncertain ...artificial neural networks depends on an in-depth understanding of data and fine tracking of relations between data ...granular ...
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Fuzzy neural networks with genetic algorithm-based learning method
... granular neural networks, fuzzy artificial neural networks, fuzzy information granulation, generic algorithms and fuzzy sets ...artificial neural networks, artificial immune systems, swarm ...
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Highly efficient Localisation utilising Weightless neural systems
... several stochastic maps. Sturm and Visser [8] show that vision based localisation could determine pose and place from discretised colours, for real-time applications. Stone et al. [9] determined that, despite ...
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A New Method for Intrusion Detection Using Genetic Algorithm and Neural network
... the neural network. Then, through a dynamic neural network, our network can be carefully chosen to determine the optimal network architecture by receiving feedback from the network and the process of ...
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A NOVEL IMAGE ENHANCEMENT METHOD USING GENETIC ALGORITHM AND NEURAL NETWORK
... DWT-HAAR method of resolution enhancement of the image is ...unique method for the image enhancement which would be a combination of wavelet transformation followed by the Neural ...combined, ...
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Neural Model of the Genetic Network*
... the genetic network of a cell or ...new mathematical models of the regulatory processes, which make it possible to analyze the dynamics of the processes and identify interactions among genes and their ...
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Genetic Evolution of Neural Networks
... of neural networks, Moriarty and Miikkulainen came up with an innovative idea in 1994 [7]: instead of using populations of networks, they used populations of neurons, each containing a vector of references to its ...
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Neural Networks using Genetic Algorithms
... c) Selection Process: In selection process, chromosomes are copied into next generation with a probability associated with their fitness value. By assigning to next generation a higher portion of the highly fit, ...
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Improving Convergence Time of the Electromagnetic Inverse Method Based on Genetic Algorithm Using the Pzmi and Neural Network
... learning method is the back-propagation. To implement a neural network in our study, we have prepared a learning database including 1,158 PZMI vectors calculated from 1,158 different ...the neural ...
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Structural damage identification utilising PCA-compressed frequency response functions and neural network ensembles
... based method that locates and quantifies dam- age in numerical beam structures from differences in FRF ...of neural network en- sembles is utilised to identify ...
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Application of Genetic Neural Network in Fault Diagnosis
... is. Genetic Operation Select operation: Select operations can allow individuals with high fitness in the previous generation to survive and inherit to the next generation, thus obtaining the most satisfying ...
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A Genetic-Neural System Diagnosing Hepatitis B
... hybrid method comprising of Feature Selection (FS) and Artificial Immune Recognition System (AIRS) with fuzzy resource allocation mechanism in predicting ...hybrid method which combined Local Fisher ...
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A Method for Graph Drawing Utilising Patterns
... drawing method may also abandon particularly bad layouts while in the process of drawing, if it identifies significant improvements may be possible with a different drawing ...
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MATHEMATICAL MODELING OF NEURAL ACTIVITY
... Model studies of biological neural networks have just started. While one, particularly for the early visual system, has had some success in describing stimulus-driven responses, the modeling of cortical population ...
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Mathematical Models of Overparameterized Neural Networks
... IRECTIONS Neural network has become an essential tool in machine learning and artificial intelligence, with a wide range of appli- ...develop mathematical models for overparameterized neural networks ...
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A MATHEMATICAL MODEL ON GENETIC DIHYBRID AND MULTIHYBRID
... There are two distinct reasons for making comparisons of genetic variation for quan- titative characters. The first one is to compare evoluabilities or ability to respond to selection, and the second is to make ...
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Verification of the Quality of the Weld When Utilising the MAG/CO2 Method
... recording method could be used not only for assessing the quality of the weld but also, for example, for evaluating the quality of other types of connections (pressed ...
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Neural and genetic determinants of creativity
... new neural framework for visuospatial ...2012. Genetic and functional analyses of SHANK2 mutations suggest a multiple hit model of autism spectrum ...
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USING NEURAL NETWORKS AND GENETIC
... 6.3.2 Pattern Detection As it has already been stated our experiments proved that neither the autoregressive (AR) nor the neural network (NN) models managed to trace patterns in the datasets they were applied to ...
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Neural Networks and Genetic Algorithm
... Na druhou stranu NEAT obsahuje množství různých parametrů, které potřebují být optimálně nastaveny. Taktéž použití přímého kódování limituje algoritmus pouze na menší sítě, neboť musí op[r] ...
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