Temat: population dynamic - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Parameter identification and estimation for stage-structured population models
Autorzy:: Coll, Carmen
Sánchez, Elena
Powiązania:: https://bibliotekanauki.pl/articles/331082.pdf
Data publikacji:: 2019
Wydawca:: Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:: system identification
parameter estimation
dynamic population
discrete time system
rank-one matrix
identyfikacja systemu
estymacja parametru
dynamika populacji
system czasu dyskretnego
Opis:: A stage-structured population model with unknown parameters is considered. Our purpose is to study the identifiability of the model and to develop a parameter estimation procedure. First, we analyze whether the parameter vector can or cannot uniquely be determined with the knowledge of the input-output behavior of the model. Second, we analyze how the information in the experimental data is translated into the parameters of the model. Furthermore, we propose a process to improve the recursive values of the parameters when successive observation data are considered. The structure of the state matrix leads to an analysis of the inverse of a sum of rank-one matrices.
Źródło:: International Journal of Applied Mathematics and Computer Science; 2019, 29, 2; 327-336
1641-876X
2083-8492
Pojawia się w:: International Journal of Applied Mathematics and Computer Science
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Swarm intelligence algorithm based on competitive predators with dynamic virtual teams
Autorzy:: Yang, S.
Sato, Y.
Powiązania:: https://bibliotekanauki.pl/articles/91592.pdf
Data publikacji:: 2017
Wydawca:: Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:: swarm intelligence
sitness predator optimizer
dynamic virtual team
population diversity
Opis:: In our previous work, Fitness Predator Optimizer (FPO) is proposed to avoid premature convergence for multimodal problems. In FPO, all of the particles are seen as predators. Only the competitive, powerful predator that are selected as an elite could achieve the limited opportunity to update. The elite generation with roulette wheel selection could increase individual independence and reduce rapid social collaboration. Experimental results show that FPO is able to provide excellent performance of global exploration and local minima avoidance simultaneously. However, to the higher dimensionality of multimodal problem, the slow convergence speed becomes the bottleneck of FPO. A dynamic team model is utilized in FPO, named DFPO to accelerate the early convergence rate. In this paper, DFPO is more precisely described and its variant, DFPO-r is proposed to improve the performance of DFPO. A method of team size selection is proposed in DFPO-r to increase population diversity. The population diversity is one of the most important factors that determines the performance of the optimization algorithm. A higher degree of population diversity is able to help DFPO-r alleviate a premature convergence. The strategy of selection is to choose team size according to the higher degree of population diversity. Ten well-known multimodal benchmark functions are used to evaluate the solution capability of DFPO and DFPO-r. Six benchmark functions are extensively set to 100 dimensions to investigate the performance of DFPO and DFPO-r compared with LBest PSO, Dolphin Partner Optimization and FPO. Experimental results show that both DFPO and DFPO-r could demonstrate the desirable performance. Furthermore, DFPO-r shows better robustness performance compared with DFPO in experimental study.
Źródło:: Journal of Artificial Intelligence and Soft Computing Research; 2017, 7, 2; 87-101
2083-2567
2449-6499
Pojawia się w:: Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: Solution of singular optimal control problems using the improved differential evolution algorithm
Autorzy:: Lobato, F. S.
Steffen, Jr, V.
Silva Neto, A. J.
Powiązania:: https://bibliotekanauki.pl/articles/91654.pdf
Data publikacji:: 2011
Wydawca:: Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:: differential evolution algorithm
optimal control
dynamic updating
population
convergence rate
mechanical engineering
chemical engineering
Opis:: The Differential Evolution algorithm, like other evolutionary techniques, presents as main disadvantage the high number of objective function evaluations as compared with classical methods. To overcome this disadvantage, this work proposes a new strategy for the dynamic updating of the population size to reduce the number of objective function evaluations. This strategy is based on the definition of convergence rate to evaluate the homogeneity of the population in the evolutionary process. The methodology is applied to the solution of singular optimal control problems in chemical and mechanical engineering. The results demonstrated that the methodology proposed represents a promising alternative as compared with other competing strategies.
Źródło:: Journal of Artificial Intelligence and Soft Computing Research; 2011, 1, 3; 195-206
2083-2567
2449-6499
Pojawia się w:: Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:: Biblioteka Nauki

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