Neural representation of interval time.

Neuron Mathematical Model Representation of Neural Tensor Network for RDF Knowledge Base Completion

In this paper, a state-of-the-art neuron mathematical model of neural tensor network (NTN) is proposed to RDF knowledge base completion problem. One of the difficulties with the parameter of the network is that representation of its neuron mathematical model is not possible. For this reason, a new representation of this network is suggested that solves this difficulty. In the representation, th...

A Novel Fuzzy and Artificial Neural Network Representation of Overcurrent Relay Characteristics

Accurate models of Overcurrent (OC) with inverse time relay characteristics play an important role for coordination of power system protection schemes. This paper proposes a new method for modeling OC relays curves. The model is based on fuzzy logic and artificial neural networks. The feed forward multilayer perceptron neural network is used to calculate operating times of OC relays for various...

Performance of the Wavelet Transform-Neural Network Based Receiver for DPIM in Diffuse Indoor Optical Wireless Links in Presence of Artificial Light Interference

Artificial neural network (ANN) has application in communication engineering in diverse areas such as channel equalization, channel modeling, error control code because of its capability of nonlinear processing, adaptability, and parallel processing. On the other hand, wavelet transform (WT) with both the time and the frequency resolution provides the exact representation of signal in both doma...

INTERVAL ARTIFICIAL NEURAL NETWORK BASED RESPONSE OF UNCERTAIN SYSTEM SUBJECT TO EARTHQUAKE MOTIONS

Earthquakes are one of the most destructive natural phenomena which consist of rapid vibrations of rock near the earth’s surface. Because of their unpredictable occurrence and enormous capacity of destruction, they have brought fear to mankind since ancient times. Usually the earthquake acceleration is noted from the equipment in crisp or exact form. But in actual practice those data may not be...

Representation of Adsorption Data for the Case of Energetically Heterogeneous Solid Surfaces Using Artificial Neural Network

Modeling the potential of Sand and Dust Storm sources formation using time series of remote sensing data, fuzzy logic and artificial neural network (A Case study of Euphrates basin)

Due to the differences between the visible and thermal infrared images, the combination of these two types of images leads to better understanding of  the characteristics of targets and the environment. Thermal infrared images are really in distinguishing targets from the background based on the radiation differences and  land surface temperature (LST) calculation. However, their spatial resolu...