Wyniki wyszukiwania - BazTech

1

Real-time validation of an automatic generation control system considering HPA-ISE with crow search algorithm optimized cascade FOPDN-FOPIDN controller

Babu Naladi Ram, Chiranjeevi Tirumalasetty, Devarapalli Ramesh, Knypiński Łukasz, Garcìa Màrquez Fausto Pedro

Archives of Control Sciences

|

2023

|

Vol. 33, No. 2

371--390

EN

This article validates the application of RT-Lab for the AGC studies of three-area systems. All the areas are employed with thermal-DSTS systems. A new controller named cascade FOPDN-FOPPIDN is employed. Its parameters are optimized using a CSA, subjecting to a new PI named HPA-ISE. The responses of the FOPDN-FOPIDN controller are related and are superior over PIDN and TIDN controllers. Moreover, the dominance of HPA-ISE is verified with ISE, and it performs better in terms of system dynamics. Further, the system performance reliability is analyzed with the AC-HVDC and is better than the AC system. Besides, sensitivity analysis recommends that the proposed FOPDN-FOPIDN at diverse conditions is robust and more reliability.

2

Feature selection and classification in mammography using hybrid crow search algorithm with Harris hawks optimization

Thawkar Shankar

Biocybernetics and Biomedical Engineering

|

2022

|

Vol. 42, no. 4

1094--1111

EN

The purpose of this study is to develop a hybrid algorithm for feature selection and classification of masses in digital mammograms based on the Crow search algorithm (CSA) and Harris hawks optimization (HHO). The proposed CSAHHO algorithm finds the best features depending on their fitness value, which is determined by an artificial neural network. Using an artificial neural network and support vector machine classifiers, the best features determined by CSAHHO are utilized to classify masses in mammograms as benign or malignant. The performance of the suggested method is assessed using 651 mammograms. Experimental findings show that the proposed CSAHHO tends to be the best as compared to the original CSA and HHO algorithms when evaluated using ANN. It achieves an accuracy of 97.85% with a kappa value of 0.9569 and area under curve AZ = 0.982 ± 0.006. Furthermore, benchmark datasets are used to test the feasibility of the suggested approach and then compared with four state-of-the-art algorithms. The findings indicate that CSAHHO achieves high performance with the least amount of features and support to enhance breast cancer diagnosis.

3

Cancer growth treatment using immune linear quadratic regulator based on crow search optimization algorithm

Hussein Mohammed A., Karam Ekhlas H., Habeeb Rokaia S.

Applied Computer Science

|

2021

|

Vol. 17, no 2

56--69

EN

The rapid and uncontrollable cell division that spreads to surrounding tissues medically termed as malignant neoplasm, cancer is one of the most common diseases worldwide. The need for effective cancer treatment arises due to the increase in the number of cases and the anticipation of higher levels in the coming years. Oncolytic virotherapy is a promising technique that has shown encouraging results in several cases. Mathematical models of virotherapy have been widely developed, and one such model is the interaction between tumor cells and oncolytic virus. In this paper an artificially optimized Immune-Linear Quadratic Regulator (LQR) is introduced to improve the outcome of oncolytic virotherapy. The control strategy has been evaluated in silico on number of subjects. The crow search algorithm is used to tune immune and LQR parameters. The study is conducted on two subjects, S1 and S3, with LQR and Immune-LQR. The experimental results reveal a decrease in the number of tumor cells and remain in the treatment area from day ten onwards, this indicates the robustness of treatment strategies that can achieve tumor reduction regardless of the uncertainty in the biological parameters.

4

Single-objective optimal power flow for electric power systems based on crow search algorithm

Fathy A., Abdelaziz A.

Archives of Electrical Engineering

|

2018

|

Vol. 67, nr 1

123--138

EN

This paper presents the application of a recent meta-heuristic optimization technique named a crow search algorithm (CSA) in solving the problem of an optimal power flow (OPF) for electric power systems. Various constrained objective functions, total fuel cost, active power loss and pollutant emission are proposed. The generators’ output powers, generators’ terminal voltages, transmission lines’ taps and the shunt capacitors’ reactive powers are considered as variables to be designed. The proposed methodology based on the CSA is applied on an IEEE 30-bus system and IEEE 118-bus system. The obtained results via the CSA are compared to others and they ensure the superiority of the CSA in solving the OPF problem in electric power systems.