•Journal•ISSN: 1109-2769
WSEAS transactions on mathematics
World Scientific and Engineering Academy and Society
About: WSEAS transactions on mathematics is an academic journal published by World Scientific and Engineering Academy and Society. The journal publishes majorly in the area(s): Computer science & Biology. It has an ISSN identifier of 1109-2769. It is also open access. Over the lifetime, 142 publications have been published receiving 114 citations. The journal is also known as: World Scientific and Engineering Academy and Society transactions on mathematics.
Topics: Computer science, Biology, Nonlinear system, Chemistry, Gene
Papers
More filters
14 citations
12 citations
TL;DR: In this paper , the authors revisited the stability property of symbiotic model of commensalism and parasitism with harvesting in the population and established sufficient conditions which ensure the global stability of the equilibria.
Abstract: This article revisit the stability property of symbiotic model of commensalism and parasitism with harvesting in the commensal population. The model was proposed by Nurmaini Puspitasari, Wuryansari Muharini Kusumawinahyu, Trisilowati (Dynamic analysis of the symbiotic model of commensalism and parasitism with harvesting in commensal populations, Jurnal Teori dan Aplikasi Matematika, 2021, 5(1): 193-204). By establishing three powerful Lemmas, sufficient conditions which ensure the global stability of the equilibria are obtained.
8 citations
TL;DR: In this article , a non-autonomous discrete Lotka-volterra commensal symbiosis model with Michaelis-Menten type harvesting is proposed and studied under some simple and easily verified condition, and it is shown that the system admits at least one positive periodic solution.
Abstract: A non-autonomous discrete Lotka-volterra commensal symbiosis model with Michaelis-Menten type harvesting is proposed and studied in this paper. Under some very simple and easily verified condition, we show that the system admits at least one positive periodic solution.
7 citations
TL;DR: In this article , Liu et al. proposed new two-parameter estimators to solve the multicollinearity problem for logistic regression model, which combines the Liu estimator and the Kibria-Lukman estimator.
Abstract: We proposed new two-parameter estimators to solve the problem called multicollinearity for the logistic regression model in this paper. We have derived these estimators’ properties and using the mean squared error (MSE) criterion; we compare theoretically with some of existing estimators, namely the maximum likelihood, ridge, Liu estimator, Kibria-Lukman, and Huang estimators. Furthermore, we obtain the estimators for k and d. A simulation is conducted in order to compare the estimators' performances. For illustration purposes, two real-life applications have been analyzed, that supported both theoretical and a simulation. We found that the proposed estimator, which combines the Liu estimator and the Kibria-Lukman estimator, has the best performance.
6 citations