Pure Mathematics for Theoretical Computer Science

In this paper, we concentrate on comparing the restricted least squares with restricted Liu estimator  based on (MSE) criterion in the existence of multi-collinearity. In addition, we find the best estimation in many different cases with some related numerical examples.

DC-DC converter circuits effectively convert the DC input voltage into a regulated output voltage more efficiently than linear regulators or magnetic transformers. The electronic switches of these converters are controlled to obtain the desired regulated output voltage value. In recent years, the concept of using Artificial Intelligence systems to control electrical circuits and their practical applications has expanded, as Fuzzy Logic Controller (FLC) is one of the most famous types of these systems because it uses inferential logic to simulate the work of the human brain by formulating the fuzzy rule and following the membership of the system’s input and output and converting the output into a numerical value that controls it’s in turn the duty cycle of the converter. The research proposes the use of Genetic Algorithms (GA) that simulate the principle of natural inheritance (the survival of the fittest principle) to improve the accuracy of the fuzzy controller and thus the efficiency of the step-down converter (Buck) by finding the ideal values for its coefficients in order to obtain the closest value for the reference voltage by improving the parameters of the gain constants and changing the shape of membership. The results of the research using MATLAB show the improvement provided by the Genetic-Fuzzy controller (GA-FLC) compared to the fuzzy logic controller in terms of the response parameters and output curves of the Buck converter.

In this paper, we introduce the notion of orthogonal semi derivations on Γ-semi rings. Some characterizations of semiprime Γ-semirings are obtained by means of orthogonal semi derivations and obtained necessary and sufficient conditions for two semi derivations to be orthogonal.

The simulation was used to evaluate the method of kernel K , Neural network NN, Convolution Neural network  CNN bys using (MINIST) data set. The accuracy of the method was tested and compared with the convolutional neural network as well as with the kernel function for the same input data (training and testing). The results of simulation showed that there is a high accuracy of the method, and at the same time there is a decreasing loss over the epochs, which indicates the. We note high smooth by method for recognize among features.  

In this paper, we investigate topologies produced by simple connected graphs. In particular, we associate a topology with G, called the incidence topology of G. A sub-base family to generate a incidence topology is implemented on the Vertices V set. Then we analyze some of the properties and discuss the impact topology of a few essential types of graphs. Our motivation in this section is to take a fundamental step towards the investigation of some of the characteristics of simple graphs by their corresponding incidence topology.