In our previous work we proposed a Multilayer Perceptron Neural Networks (MLP NN) consisting of fuzzy flipflops (F3) based on various operations. We showed that such kind of fuzzy-neural network had good learning properties. In this paper we propose an evolutionary approach for optimizing fuzzy flip-flop networks (FNN). Various popular fuzzy operation and three different fuzzy flip-flop types w...

The authors present results of the research aiming at human identification based on tensor representation of the gait motion capture data. High-dimensional tensor samples were reduced by means of the multilinear principal component analysis (MPCA). For the purpose of classification the following methods from the WEKA software were used: k Nearest Neighbors (kNN), Naive Bayes, Multilayer Percept...

In this work we present a variational formulation for neural networks. Within this formulation, the learning problem for the multilayer perceptron lies in terms of finding a function which is an extremal for some functional. As we will see, a variational formulation for neural networks provides a direct method for the solution of general variational problems, in any dimension and up to any degr...

Reinforcement learning (RL) offers a set of various algorithms for in-situation behavior synthesis [1]. The Qlearning [2] technique is certainly the most used of the RL methods. Multilayer perceptron implementations of the Q-learning have been proposed early [3], due to the interest of the restricted memory need and the generalization capability [4]. Self-organizing map implementation of the Q-...

Microcompression tests were performed on the Al/Nb multilayers of incoherent interfaces with the layer thicknesses of 5 nm Al/5 nm Nb and 50 nm Al/50 nm Nb. The Al-Nb multilayers showed increase in strength as the layer thickness was reduced; the average flow stresses at 5% plastic strain from the 5 nm Al/5 nm Nb and 50 nm Al/50 nm Nb layer thickness specimens were determined to be 2.1 GPa and ...

The investigation of thermal and excess noise in the high-Q modes of all fused silica suspension for the Advanced LIGO test masses.. 2 1.2 The investigation of thermal and excess noise in the fused silica plates with multilayer reflective coating. .

Hydrological data are often missing due to natural disasters, improper operation, limited equipment life, and other factors, which limit hydrological analysis. Therefore, missing data recovery is an essential process in hydrology. This paper investigates the accuracy of artificial neural networks (ANN) in estimating missing flow records. The purpose is to develop and apply neural networks model...

Weather forecasting is most challenging problem around the world. There are various reason because of its experimented values in meteorology, but it is also a typical unbiased time series forecasting problem in scientific research. A lots of methods proposed by various scientists. The motive behind research is to predict more accurate. This paper contribute the same using artificial neural netw...

Training neural networks is a complex task that is important for supervised learning. A few metaheuristic optimization techniques have been applied to increase the effectiveness of the training process. The Cuckoo Search (CS) algorithm is a recently developed meta-heuristic optimization algorithm which is suitable for solving optimization problems. In this paper, Cuckoo search is implemented in...

This paper presents the prediction propagation paths of angle of arrivals (AoAs) of a Smart Antenna System in an outdoor environment utilizing Artificial Neural Networks (ANN). The proposed models consist of a Multilayer Perceptron and a Generalized Regression Neural Network trained with measurements of an antenna system consisted of a Single Input Single Output (SISO) system in the millimeter ...