Artificial neural network

An experimental study was conducted on a high-voltage glass-type disc (LD-160) to investigate the effect of string arrangements on pollution and icing flashover characteristics. Two Artificial Neural Network (ANN) applications were developed to simulate and calculate the flashover voltage based on the experimental results. The test results showed that the inverted T-type arrangement can improve the pollution flashover voltage and increase the icing flashover voltage of insulator strings compared to the traditional arrangement of the I-string.

The most popular and active area of data mining study is sentiment analysis. Twitter is a crucial platform for collecting and distributing people's thoughts, feelings, views, and attitudes regarding specific entities. There are several social media networks available today. In light of this, sentiment analysis in natural language processing (NLP) field became fascinating. Different techniques have been developed for sentiment analysis. However, there is still a need for improvement in terms of accuracy and system effectiveness.

The dataset Provides S-parameter measurements of two ISO/ICE 14443-1 Coils with series capacitance compensation at 13.56 MHz under different spatial configurations of vertical and horizontal misalignment, inter-coil distance, and azimuthal tilt as indicated in the image. The dataset  can be used for training of neural networks controlling adaptive impedance matching networks.

Power transmission system losses can typically represent from five to ten percent of the total generation, a quantity worth millions of dollars per year. The purpose of loss allocation in the context of pool dispatch is to assign to each individual generation and load the responsibility of paying for part of the system transmission losses. Since the system losses are non-separable, non-linear functions of the real power generation and loads, the allocation of transmission loss is a challenging and contentious issue in a fully deregulated system.