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Tytuł:
Application of RRAP reliability optimization as a test of nature-inspired algorithms
Autorzy:
Pieprzycki, Adam
Filipowicz, Bogusław
Powiązania:
https://bibliotekanauki.pl/articles/35533466.pdf
Data publikacji:
2024-02-15
Wydawca:
Akademia Tarnowska
Tematy:
reliability optimization
RRAP
Firefly Algorithm (FA)
Cuckoo Search (CS)
ANOVA
Lévy flight
Opis:
This paper presents a discussion on the application of two swarm intelligence algorithms, Cuckoo Search (CS) and Firey Algorithm (FA), to maximize the reliability of two complex systems with resource constraints, which have been well-known in the literature. The reliability of the systems is also evaluated using several classical methods. The results indicate that although the CS algorithm, which utilizes Lévy flight, is eective, the FA rey algorithm outperformed it in the presented optimization tasks, within the given parameter range. These ndings contribute to the ongoing discussion on using nature-inspired algorithms for solving Reliability Redundancy Allocation Problem (RRAP) problems, and the two test scenarios used in the study can be useful for validating other algorithms in RRAP problems. The paper introduces metrics and methods for analyzing and comparing the performance of algorithms in RRAP optimization, including the comparison of criterion function values and other parameters introduced in the paper. Additionally, the paper discusses statistical analyses of variance (ANOVA) with post-hoc RIR Tuckey tests.
Źródło:
Science, Technology and Innovation; 2023, 18, 3-4; 1-14
2544-9125
Pojawia się w:
Science, Technology and Innovation
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A new method of decision making in multi-objective optimal placement and sizing of distributed generators in the smart grid
Autorzy:
Khoshayand, Hossein Ali
Wattanapongsakorn, Naruemon
Mahdavian, Mehdi
Ganji, Ehsan
Powiązania:
https://bibliotekanauki.pl/articles/2202555.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
backward-forward load distribution
fuzzy logic
iterative search algorithm
multi-objective optimization
shortest distance from the origin
weighted sum
Opis:
One of the most important aims of the sizing and allocation of distributed generators (DGs) in power systems is to achieve the highest feasible efficiency and performance by using the least number of DGs. Considering the use of two DGs in comparison to a single DG significantly increases the degree of freedom in designing the power system. In this paper, the optimal placement and sizing of two DGs in the standard IEEE 33-bus network have been investigated with three objective functions which are the reduction of network losses, the improvement of voltage profiles, and cost reduction. In this way, by using the backward-forward load distribution, the load distribution is performed on the 33-bus network with the power summation method to obtain the total system losses and the average bus voltage. Then, using the iterative search algorithm and considering problem constraints, placement and sizing are done for two DGs to obtain all the possible answers and next, among these answers three answers are extracted as the best answers through three methods of fuzzy logic, the weighted sum, and the shortest distance from the origin. Also, using the multi-objective non-dominated sorting genetic algorithm II (NSGA-II) and setting the algorithm parameters, thirty-six Pareto fronts are obtained and from each Pareto front, with the help of three methods of fuzzy logic, weighted sum, and the shortest distance from the origin, three answers are extracted as the best answers. Finally, the answer which shows the least difference among the responses of the iterative search algorithm is selected as the best answer. The simulation results verify the performance and efficiency of the proposed method.
Źródło:
Archives of Electrical Engineering; 2023, 72, 1; 253--271
1427-4221
2300-2506
Pojawia się w:
Archives of Electrical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A novel hybrid cuckoo search algorithm for optimization of a line-start PM synchronous motor
Autorzy:
Knypiński, Łukasz
Powiązania:
https://bibliotekanauki.pl/articles/2204509.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
hybrid cuckoo search algorithm
heuristic algorithms
multi-objective optimization
permanent magnet synchronous motor
PMSM
algorytm kukułki hybrydowy
algorytm Cuckoo
algorytm heurystyczny
optymalizacja wielocelowa
silnik synchroniczny z magnesem trwałym
Opis:
The paper presents a novel hybrid cuckoo search (CS) algorithm for the optimization of the line-start permanent magnet synchronous motor (LSPMSM). The hybrid optimization algorithm developed is a merger of the heuristic algorithm with the deterministic Hooke–Jeeves method. The hybrid optimization procedure developed was tested on analytical benchmark functions and the results were compared with the classical cuckoo search algorithm, genetic algorithm, particle swarm algorithm and bat algorithm. The optimization script containing a hybrid algorithm was developed in Delphi Tiburón. The results presented show that the modified method is characterized by better accuracy. The optimization procedure developed is related to a mathematical model of the LSPMSM. The multi-objective compromise function was applied as an optimality criterion. Selected results were presented and discussed.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2023, 71, 1; art. no. e144586
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Applying Hunger Game Search (HGS) for selecting significant blood indicators for early prediction of ICU COVID-19 severity
Autorzy:
Sayed, Safynaz AbdEl-Fattah
ElKorany, Abeer
Sayed, Sabah
Powiązania:
https://bibliotekanauki.pl/articles/27312915.pdf
Data publikacji:
2023
Wydawca:
Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Tematy:
ICU severity prediction
COVID-19
clinical blood tests
Hunger Game search
HGS
optimization algorithm
support vector machine
SVM
feature selection
Opis:
This paper introduces an early prognostic model for attempting to predict the severity of patients for ICU admission and detect the most significant features that affect the prediction process using clinical blood data. The proposed model predicts ICU admission for high-severity patients during the first two hours of hospital admission, which would help assist clinicians in decision-making and enable the efficient use of hospital resources. The Hunger Game search (HGS) meta-heuristic algorithm and a support vector machine (SVM) have been integrated to build the proposed prediction model. Furthermore, these have been used for selecting the most informative features from blood test data. Experiments have shown that using HGS for selecting features with the SVM classifier achieved excellent results as compared with four other meta-heuristic algorithms. The model that used the features that were selected by the HGS algorithm accomplished the topmost results (98.6 and 96.5%) for the best and mean accuracy, respectively, as compared to using all of the features that were selected by other popular optimization algorithms.
Źródło:
Computer Science; 2023, 24 (1); 113--136
1508-2806
2300-7036
Pojawia się w:
Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Loadability maximisation in bilateral network for real-time forecasting system using cuckoo search algorithm
Autorzy:
Venkatasivanagaraju, S.
Rao, M. Venkateswara
Powiązania:
https://bibliotekanauki.pl/articles/38699704.pdf
Data publikacji:
2023
Wydawca:
Instytut Podstawowych Problemów Techniki PAN
Tematy:
optimal power flow
NR method
short-term load forecasting
long-term load forecasting
cuckoo search algorithm
optimisation
loss minimisation
optymalny przepływ mocy
metoda NR
krótkoterminowe prognozowanie obciążeń
długoterminowe prognozowanie obciążeń
algorytm kukułki
optymalizacja
minimalizacja strat
Opis:
This manuscript proposes an optimal power flow (OPF) solution in a coordinated bilateralpower network. The primary goal of this project is to maximise the benefits of the powermarket using Newton–Raphson (NR) and cuckoo search algorithm CSA methodologies.The global solution is found using a CSA-based optimisation approach. The study isconducted on real-time bus system. To avoid this, creative techniques have lately beenused to handle the OPF problem, such as loadability maximisation for real-time predictionsystems employing the CSA. In this work, cuckoo search (CS) is used to optimise theobtained parameters that help to minimise parameters in the predecessor and consequentunits of each sub-model. The proposed approach is used to estimate the power load in thelocal area. The constructed models show excellent predicting performance based on derivedperformance. The results confirm the method’s validity. The outcomes are compared withthose obtained by using the NR method. CSA outperformed the other methods in thisinvestigation and gave more accurate predictions. The OPF problem is solved via CSAin this study. Implementing a real-time data case bus system is recommended to test theperformance of the established method in the MATLAB programme.
Źródło:
Computer Assisted Methods in Engineering and Science; 2023, 30, 1; 73-88
2299-3649
Pojawia się w:
Computer Assisted Methods in Engineering and Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Minimized Group Delay FIR Low Pass Filter Design Using Modified Differential Search Algorithm
Autorzy:
Prajapati, Sonelal
Rai, Sanjeev
Tiwari, Manish
Dwivedi, Atul Kumar
Powiązania:
https://bibliotekanauki.pl/articles/24200750.pdf
Data publikacji:
2023
Wydawca:
Instytut Łączności - Państwowy Instytut Badawczy
Tematy:
differential search optimization algorithm
FIR filter
optimization
small group delay
Opis:
Designing a finite impulse response (FIR) filter with minimal group delay has proven to be a difficult task. Many research studies have focused on reducing pass band and stop band ripples in FIR filter design, often overlooking the optimization of group delay. While some works have considered group delay reduction, their approaches were not optimal. Consequently, the achievement of an optimal design for a filter with a low group delay value still remains a challenge. In this work, a modified differential search optimization algorithm has been used for the purpose of designing a minimal group delay FIR filter. The results obtained have been compared with the classical techniques and they turned out to be promising.
Źródło:
Journal of Telecommunications and Information Technology; 2023, 3; 78--84
1509-4553
1899-8852
Pojawia się w:
Journal of Telecommunications and Information Technology
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Minimizing the Makespan and Total Tardiness in Hybrid Flow Shop Scheduling with Sequence-Dependent Setup Times
Autorzy:
Mousavi, Seyyed Mostafa
Shahnazari-Shahrezaei, Parisa
Powiązania:
https://bibliotekanauki.pl/articles/2201180.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
dispatching rule
genetic algorithm
hybrid flow shop
neighborhood search structure
Opis:
The paper considers the production scheduling problem in a hybrid flow shop environment with sequence-dependent setup times and the objectives of minimizing both the makespan and the total tardiness. The multi-objective genetic algorithm is applied to solve this problem, which belongs to the non-deterministic polynomial-time (NP)-hard class. In the structure of the proposed algorithm, the initial population, neighborhood search structures and dispatching rules are studied to achieve more efficient solutions. The performance of the proposed algorithm compared to the efficient algorithm available in literature (known as NSGA-II) is expressed in terms of the data envelopment analysis method. The computational results confirm that the set of efficient solutions of the proposed algorithm is more efficient than the other algorithm.
Źródło:
Management and Production Engineering Review; 2023, 14, 1; 13--24
2080-8208
2082-1344
Pojawia się w:
Management and Production Engineering Review
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Optimizing the harmony search algorithm for combined heat and power economic dispatch in american english
Autorzy:
Benayed, F.Z.
Abdelhakem-Koridak, L.
Bouadi, A.
Rahli, M.
Powiązania:
https://bibliotekanauki.pl/articles/41184379.pdf
Data publikacji:
2023
Wydawca:
Politechnika Warszawska, Instytut Techniki Cieplnej
Tematy:
combined heat and power system
harmony search algorithm
optimization of power systems
połączony system ciepłowniczy i elektroenergetyczny
algorytm poszukiwania harmonii
optymalizacja systemów energetycznych
Opis:
Achieving optimal utilization of multiple combined heat and power (CHP) systems is a complex problem that requires powerful methods for resolution. This paper presents a harmony search (HS) algorithm to address the economic dispatch issue in CHP (CHPED ). The recently developed metaheuristic HS algorithm has been successfully employed in a wide range of optimization problems. The method is demonstrated through a test case from existing literature and a new one proposed by the authors. Numerical results indicate that the proposed algorithm can identify superior solutions compared to traditional methods, and that the Harmony Search algorithm can be effectively applied to CHPED-related problems.
Źródło:
Journal of Power Technologies; 2023, 103, 1; 14-20
1425-1353
Pojawia się w:
Journal of Power Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Real-time validation of an automatic generation control system considering HPA-ISE with crow search algorithm optimized cascade FOPDN-FOPIDN controller
Autorzy:
Babu, Naladi Ram
Chiranjeevi, Tirumalasetty
Devarapalli, Ramesh
Knypiński, Łukasz
Garcìa Màrquez, Fausto Pedro
Powiązania:
https://bibliotekanauki.pl/articles/27312009.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czasopisma i Monografie PAN
Tematy:
crow search algorithm
dish-stirling solar system
AGC
RT Lab
FOPDN-FOPIDN controller
Opis:
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.
Źródło:
Archives of Control Sciences; 2023, 33, 2; 371--390
1230-2384
Pojawia się w:
Archives of Control Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Lung cancer detection using an integration of fuzzy K-Means clustering and deep learning techniques for CT lung images
Autorzy:
Prasad, J. Maruthi Nagendra
Chakravarty, S.
Krishna, M. Vamsi
Powiązania:
https://bibliotekanauki.pl/articles/2173683.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
fuzzy K-means
artificial neural networks
SVM
support vector machine
crow search optimization algorithm
algorytm rozmytych k-średnich
sztuczne sieci neuronowe
maszyna wektorów wspierających
algorytm optymalizacji wyszukiwania kruków
Opis:
Computer aided detection systems are used for the provision of second opinion during lung cancer diagnosis. For early-stage detection and treatment false positive reduction stage also plays a vital role. The main motive of this research is to propose a method for lung cancer segmentation. In recent years, lung cancer detection and segmentation of tumors is considered one of the most important steps in the surgical planning and medication preparations. It is very difficult for the researchers to detect the tumor area from the CT (computed tomography) images. The proposed system segments lungs and classify the images into normal and abnormal and consists of two phases, The first phase will be made up of various stages like pre-processing, feature extraction, feature selection, classification and finally, segmentation of the tumor. Input CT image is sent through the pre-processing phase where noise removal will be taken care of and then texture features are extracted from the pre-processed image, and in the next stage features will be selected by making use of crow search optimization algorithm, later artificial neural network is used for the classification of the normal lung images from abnormal images. Finally, abnormal images will be processed through the fuzzy K-means algorithm for segmenting the tumors separately. In the second phase, SVM classifier is used for the reduction of false positives. The proposed system delivers accuracy of 96%, 100% specificity and sensitivity of 99% and it reduces false positives. Experimental results shows that the system outperforms many other systems in the literature in terms of sensitivity, specificity, and accuracy. There is a great tradeoff between effectiveness and efficiency and the proposed system also saves computation time. The work shows that the proposed system which is formed by the integration of fuzzy K-means clustering and deep learning technique is simple yet powerful and was effective in reducing false positives and segments tumors and perform classification and delivers better performance when compared to other strategies in the literature, and this system is giving accurate decision when compared to human doctor’s decision.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2022, 70, 3; art. no. e139006
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Research on optimization of unrelated parallel machine scheduling based on IG-TS algorithm
Autorzy:
Chi, Xinfu
Liu, Shijing
Li, Ce
Powiązania:
https://bibliotekanauki.pl/articles/2173693.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
warp knitting machine
parallel machine scheduling
iterative greedy algorithm
tabu search
osnowarka
planowanie maszyn równoległych
algorytm zachłanny iteracyjny
przeszukiwanie tabu
Opis:
This issue is a typical NP-hard problem for an unrelated parallel machine scheduling problem with makespan minimization as the goal and no sequence-related preparation time. Based on the idea of tabu search (TS), this paper improves the iterative greedy algorithm (IG) and proposes an IG-TS algorithm with deconstruction, reconstruction, and neighborhood search operations as the main optimization process. This algorithm has the characteristics of the strong capability of global search and fast speed of convergence. The warp knitting workshop scheduling problem in the textile industry, which has the complex characteristics of a large scale, nonlinearity, uncertainty, and strong coupling, is a typical unrelated parallel machine scheduling problem. The IG-TS algorithm is applied to solve it, and three commonly used scheduling algorithms are set as a comparison, namely the GA-TS algorithm, ABC-TS algorithm, and PSO-TS algorithm. The outcome shows that the scheduling results of the IG-TS algorithm have the shortest manufacturing time and good robustness. In addition, the production comparison between the IG-TS algorithm scheduling scheme and the artificial experience scheduling scheme for the small-scale example problem shows that the IG-TS algorithm scheduling is slightly superior to the artificial experience scheduling in both planning and actual production. Experiments show that the IG-TS algorithm is feasible in warp knitting workshop scheduling problems, effectively realizing the reduction of energy and the increase in efficiency of a digital workshop in the textile industry.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2022, 70, 4; art. no. e141724
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Solving scheduling problems with integrated online sustainability observation using heuristic optimization
Autorzy:
Burduk, Anna
Musiał, Kamil
Balashov, Artem
Batako, Andre
Safonyk, Andrii
Powiązania:
https://bibliotekanauki.pl/articles/2173719.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
production scheduling
sustainable development
genetic algorithm
meta-heuristics
intelligent optimization methods of production systems
tabu search
harmonogramowanie produkcji
zrównoważony rozwój
algorytm genetyczny
przeszukiwanie tabu
metaheurystyki
inteligentne metody optymalizacji systemów produkcyjnych
Opis:
The paper deals with the issue of production scheduling for various types of employees in a large manufacturing company where the decision-making process was based on a human factor and the foreman’s know-how, which was error-prone. Modern production processes are getting more and more complex. A company that wants to be competitive on the market must consider many factors. Relying only on human factors is not efficient at all. The presented work has the objective of developing a new employee scheduling system that might be considered a particular case of the job shop problem from the set of the employee scheduling problems. The Neuro-Tabu Search algorithm and the data gathered by manufacturing sensors and process controls are used to remotely inspect machine condition and sustainability as well as for preventive maintenance. They were used to build production schedules. The construction of the Neuro-Tabu Search algorithm combines the Tabu Search algorithm, one of the most effective methods of constructing heuristic algorithms for scheduling problems, and a self-organizing neural network that further improves the prohibition mechanism of the Tabu Search algorithm. Additionally, in the paper, sustainability with the use of Industry 4.0 is considered. That would make it possible to minimize the costs of employees’ work and the cost of the overall production process. Solving the optimization problem offered by Neuro-Tabu Search algorithm and real-time data shows a new way of production management.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2022, 70, 6; art. no. e143830
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Balancing of a linear elastic rotor-bearing system with arbitrarily distributed unbalance using the Numerical Assembly Technique
Autorzy:
Quinz, Georg
Prem, Marcel S.
Klanner, Michael
Ellermann, Katrin
Powiązania:
https://bibliotekanauki.pl/articles/2086883.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
Numerical Assembly Technique
rotor dynamics
modal balancing
recursive eigenvalue search algorithm
dynamika wirnika
wyważanie modalne
Opis:
In this paper, a new application of the Numerical Assembly Technique is presented for the balancing of linear elastic rotor-bearing systems with a stepped shaft and arbitrarily distributed mass unbalance. The method improves existing balancing techniques by combining the advantages of modal balancing with the fast calculation of an efficient numerical method. The rotating stepped circular shaft is modelled according to the Rayleigh beam theory. The Numerical Assembly Technique is used to calculate the steady-state harmonic response, eigenvalues and the associated mode shapes of the rotor. The displacements of a simulation are compared to measured displacements of the rotor-bearing system to calculate the generalized unbalance for each eigenvalue. The generalized unbalances are modified according to modal theory to calculate orthogonal correction masses. In this manner, a rotor-bearing system is balanced using a single measurement of the displacement at one position on the rotor for every critical speed. Three numerical examples are used to show the accuracy and the balancing success of the proposed method.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2021, 69, 6; e138237, 1--7
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Cancer growth treatment using immune linear quadratic regulator based on crow search optimization algorithm
Autorzy:
Hussein, Mohammed A.
Karam, Ekhlas H.
Habeeb, Rokaia S.
Powiązania:
https://bibliotekanauki.pl/articles/1837793.pdf
Data publikacji:
2021
Wydawca:
Polskie Towarzystwo Promocji Wiedzy
Tematy:
oncolytic virotherapy
feedback mechanism
crow search algorithm
Immune-LQR
wiroterapia onkolityczna
mechanizm sprzężenia zwrotnego
algorytm wyszukiwania w tłumie
Opis:
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.
Źródło:
Applied Computer Science; 2021, 17, 2; 56-69
1895-3735
Pojawia się w:
Applied Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Cryptographically Strong Elliptic Curves of Prime Order
Autorzy:
Barański, Marcin
Gliwa, Rafał
Szmidt, Janusz
Powiązania:
https://bibliotekanauki.pl/articles/1844627.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
Mersenne primes
elliptic curves
security requirements
search algorithm
Magma
Opis:
The purpose of this paper is to generate cryptographically strong elliptic curves over prime fields Fp, where p is a Mersenne prime, one of the special primes or a random prime. We search for elliptic curves which orders are also prime numbers. The cryptographically strong elliptic curves are those for which the discrete logarithm problem is computationally hard. The required mathematical conditions are formulated in terms of parameters characterizing the elliptic curves. We present an algorithm to generate such curves. Examples of elliptic curves of prime order are generated with Magma.
Źródło:
International Journal of Electronics and Telecommunications; 2021, 67, 2; 207-212
2300-1933
Pojawia się w:
International Journal of Electronics and Telecommunications
Dostawca treści:
Biblioteka Nauki
Artykuł
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