Neural Networks and Evolutionary Algorithms
Evolutionary Algorithms For Neural Networks Binary And Real Data Classification
... Artificial neural networks are complex networks emulating the way human rational neurons process ...training algorithms that used to determine the network weights are almost the most important ...
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Boosting wavelet neural networks using evolutionary algorithms for short-term wind speed time series forecasting
... wavelet neural networks. The basic building block of the neural network models is a ridge type ...problem. Evolutionary algorithms (EAs), in- cluding genetic algorithm (GA) and particle ...
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Music composition using recurrent neural networks and evolutionary algorithms
... the neural network would no longer need to maintain knowledge of the key throughout ...the neural network’s ability to write a wide range of music since most composers agree that the exact key has very ...
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Multi-objective evolutionary algorithms of spiking neural networks
... More information has been used with the average firing rate for computations with real neurons. Furthermore, instead of rate coding, the difference in firing times may be used (Belatreche et al., 2006). Although there ...
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COMPARING EVOLUTIONARY ALGORITHMS ON TUNING THE PARAMETERS OF FUZZY WAVELET NEURAL NETWORK
... Wavelet Neural Networks (FWNNs) have been used in many ...different evolutionary algorithms including Genetic Algorithm (GA), Gravitational Search Algorithm (GSA), Evolutionary Strategy ...
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Overview: Evolutionary Algorithms
... methods, neural networks, and support vector machines and describe applications in the areas of inferential sensors, empirical emulators of mechanistic models, acceler- ated new product development, complex ...
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EvoDeep: A new evolutionary approach for automatic Deep Neural Networks parametrisation
... Learning, Evolutionary Algorithms, Finite-State Machines, Automated Parametrisation ...learning algorithms are being increasingly adopted in various ...learning algorithms, such as logistic ...
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Evolutionary Design of Neural Networks
... The work deals with the development of the genetic algorithm, which designs the structure and learning of the neural networks. The fitness function also includes the number of hidden neurons, and thus we ...
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An Evolutionary Approach: Analysis of Artificial Neural Networks
... find algorithms which can adjust the weights of the ANN in order to obtain the desired output from the ...real neural networks, and study behavior and control in animals and machines, but also there ...
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A Survey On Backpropagation Algorithms For Feedforward Neural Networks
... 2007 Wang et al. An Individual Inference Adjusting Learning Rate technique (IIALR) is proposed to enhance the learning performance of the BPNN. 2007 Sammy Siu et al[15]. By using Evolutionary technique Back ...
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Artificial neural networks with evolutionary instance selection for financial forecasting
... learning algorithms may be considered as a method of knowledge refinement and it maintains the ...selection algorithms for maintaining the case-base in case-based reasoning (CBR) ...
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Combining Genetic Algorithms and Neural Networks: The Encoding Problem
... The second case is more close to natural Darwian evolution and profits from the Baldwin effect, which was first described in the 19th century . It impact on genetic algorithm was first suggested in [Hinton, 1987], though ...
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Optimizing Weights of Artificial Neural Networks using Genetic Algorithms
... Multilayer Neural Network (NN) using Genetic Algorithms (GAs) ...the evolutionary techniques based on GAs are studied and employed for the Model Reference Adaptive Control (MRAC) scheme of different ...
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Neural Networks algorithms and applications
... Practical problems There are some practical problems applying Neural networks to applications. It is not possible to know in advance the ideal network for an application. So every time a NN is to be built ...
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Efficient Algorithms for Trees and Networks in Evolutionary Genomics
... good networks when compared to other subsets with the same ...all networks with hybridization number greater than r + a for speedup because these networks may not lead to a good final ...
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Evolutionary Algorithms using Evolutionary Algorithms
... Intelligence, Evolutionary Algorithm, Genetic ...of Evolutionary Algorithm is Search ...of evolutionary algorithms for faster and better evaluation of ...
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Neural Networks using Genetic Algorithms
... crossover. Neural network is computational model having number of processing elements called ...and neural networks have a wide real-world application area, also suffers from various cons so in ...
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Coevolution of Cartesian Genetic Algorithms and Neural Networks
... 3.6.2 Učení hlubokých neuronových sítí s omezeným Boltzmannovým strojem 29 4 Koevoluce genetického programování a neuronových sítí 32 4.1 Nepřímé zakódování sítě pomocí Developmental Net[r] ...
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Algorithms for Optimized Training of Artificial Neural Networks
... Artificial neural networks (ANNs) are one of the most widely used paradigms in pattern analysis and machine learning ...research. Neural networks (NN) have been used to solve a variety of ...
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Evolutionary robotics, neural networks, video game AI
... Joel Lehman, Sebastian Risi, David D’Ambrosio, and Kenneth O.. Encouraging Reactivity to Create Robust Machines.[r] ...
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