Research on potential interactions between connectionist learning systems, i.e., articial neural networks (ANNs), and evolutionary search procedures, like genetic algorithms (GAs), has attracted a lot of attention recently. Evolutionary ANNs (EANNs) can be considered as the combination of ANNs and evolutionary search procedures. This paper rst distinguishes among three kinds of evolution in EAN...

The work is devoted to the method of multispectral space images analyzing aquatic coastal systems for identifying phytoplankton populations complicated structures: determining their boundaries, distributing color gradations and, based on this, distribution concentrations within patches and location "mass" center. A combination local binary patterns (LBP) neuralnetworks methods considered. Due t...

| Given a problem, a case-based reasoning (CBR) system will search its case memory and use the stored cases to nd the solution, possibly modifying retrieved cases to adapt to the required input speciications. In discrete domains CBR reasoning can be based on a rigorous Bayesian probability propagation algorithm. Such a Bayesian CBR system can be implemented as a probabilistic feedforward neural...

background: we aimed to assess the high-risk group for suicide using different classification methods includinglogistic regression (lr), decision tree (dt), artificial neural network (ann), and support vector machine (svm). methods: we used the dataset of a study conducted to predict risk factors of completed suicide in hamadan province, the west of iran, in 2010. to evaluate the high-risk grou...

Neural networks with external memories (NNEM),such as the Neural Turing Machine [1] and Memory Networks [2], have often been compared to the human hippocampus in their ability to maintain episodic information over long timescales [3]. But so far, these networks have only been trained on tasks requiring memory storage comparable to a few minutes, whereas the hippocampus stores information on the...

Review and classification of electric load forecasting (LF) techniques based on artificial neuralnetworks (ANN) is presented. A basic ANNs architectures used in LF reviewed. A wide range of ANNoriented applications for forecasting are given in the literature. These are classified into five groups:(1) ANNs in short-term LF, (2) ANNs in mid-term LF, (3) ANNs in long-term LF, (4) Hybrid ANNs inLF,...

The movements of talkers’ faces are known to convey visual cues that can improve speech intelligibility, especially where there is noise or hearing-impairment. This suggests that visible facial gestures could be exploited to enhance speech intelligibility in automatic systems. Handling the volume of data represented by images of talkers’ faces implies some form of data compression. Rather than ...

In this work, we present a thorough experimental study about feature extraction using Convolutional NeuralNetworks (CNNs) for the task of image captioning in context deep learning. We perform set 72experiments on 12 classification CNNs pre-trained ImageNet [29] dataset. The features areextracted from last layer after removing fully connected and fed into model. usea unified model with fixed voc...