Stability in a population model without random deaths by the Verhulst factor

Piñol, Chrysline Margus N.; Banzon, Ronald

doi:10.1016/j.physa.2010.11.046

Cited by 5 publications

(5 citation statements)

References 22 publications

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“…These describe the very slow aging process observed in coldwater fish, bivalves, turtles, whales, and, fairly recently, in the naked mole-rats [22]. Note that within the framework of the Penna model, Verhulstfree demonstrations are limited to threshold values that are greater than the reproduction age (T > R) with one semelparous birth per adult (B = 1) [23]. So far, these are the only parameter sets that lead to nonzero steady states even without random deaths by the Verhulst factor.…”

Section: Resultsmentioning

confidence: 95%

The effect of limiting resources in aging populations

Pinol,

Banzon

2010

Preprint

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The concept of a carrying capacity is essential in most models to prevent unlimited growth. Despite the large amount of deaths it introduces, the actual influence of the Verhulst term in simulations is often times not accounted for. Generally, it is treated merely as a scaling parameter that functions to keep simulated populations within computer limits. Here, we compare two different implementations of the concept in the Penna model -Vehulst applied to all individuals (VA) and to newborns only (VB). We observe variations in certain model features when random Verhulst deaths are restricted to a single age group.

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Section: Resultsmentioning

confidence: 95%

The effect of limiting resources in aging populations

Pinol,

Banzon

2010

Preprint

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“…As such, the evaluation of the importance of each attribute is determined by the community's overall survival as evidence by population changes and species composition. A common evaluation method is broadly quantified through Lotka and Vito Volterra's equations [18] below: where K is the maximum number of individuals' a given habitat can accommodate and the populations of predators (P) and prey (N) is determined by constant a, b, c, and e, such that:…”

Section: A Survival In Naturementioning

confidence: 99%

“…The capacity of a system to provide essential services even after successful intrusion and compromise, and to recover full services in a timely manner. 18 Network design and management procedures to minimize the impact of failures on the network. 19 Defined in the terms of a telecommunications network where it is the ability of the network to maintain or restore an acceptable level of performance in the event of deterministic or random network failures, such as link failures and node failures.…”

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confidence: 99%

Survivability Analogy for Cloud Computing

Mthunzi

Benkhelifa

2017

2017 IEEE/ACS 14th International Conference on Computer Systems and Applications (AICCSA)

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As cloud computing has become the most popular computing platform, and cloud-based applications a commonplace, the methods and mechanisms used to ensure their survivability is increasingly becoming paramount. One of the prevalent trends in recent times is a turn to nature for inspiration in developing and supporting highly survivable environments. This paper aims to address the problems of survivability in cloud environments through inspiration from nature. In particular, the community metaphor in nature's predator-prey systems where autonomous individuals' local decisions focus on ensuring the global survival of the community. Thus, we develop analogies for survivability in cloud computing based on a range of mechanisms which we view as key determinants of prey's survival against predation. For this purpose we investigate some predator-prey systems that will form the basis for our analogical designs. Furthermore, due to a lack of a standardized definition of survivability, we propose a unified definition for survivability, which emphasizes as imperative, a high level of proactiveness to thwart black swan events, as well as high capacity to respond to insecurity in a timely and appropriate manner, inspired by prey's avoidance and anti-predation approaches.

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“…Eq. ( 1) is a population growth model that depends on the carrying capacity of the environment [Jorgensen, 1994;Kribs-Zaleta, 2004;Chong et al, 2005;Peleg et al, 2007;Pinol and Banzon, 2011;Al-Saffar and Kim, 2017]. Some of the dynamic models that are modified from Eq.…”

Section: Introductionmentioning

confidence: 99%

Ecological Implications of the Dynamics of Water Volume Growth in a Reservoir

Kartono¹,

Purwanto²,

Suripin³

2021

Ecol. Eng. Environ. Technol.

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The rate of growth of the water volume in the reservoir varies with each charging season. The accuracy of the predictions is required in sustainable reservoir management. Its intrinsic growth rate as an ecological parameter plays a role in determining this speed. This study aimed to analyze the dynamics of water volume growth based on its intrinsic growth rate to assess the potential for hydrometeorology disasters. The population growth models proposed to be tested for suitability and goodness is the Verhulst, Richards, Comperzt, and modified Malthus model. Test suitability and model goodness were subjected to stages of verification, parameter estimation and model validation based on daily water volume data in the Gembong Reservoir, Pati, Indonesia for the period 2007-2020. A good model is determined based on the Mean Average Percentage Error (MAPE) criteria. The Richards model with b = 2 and r = 0.063/day had consistently low MAPE values during training and testing. This model was chosen as a new approach to understand the dynamics of water volume growth in a reservoir. The ecological implication of these dynamics of water volume growth is that reservoirs experience an abundance of water during the charging season. Reservoir normalization can be prioritized as a mitigation strategy for potential flood disasters.

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Stability in a population model without random deaths by the Verhulst factor

Cited by 5 publications

References 22 publications

The effect of limiting resources in aging populations

The effect of limiting resources in aging populations

Survivability Analogy for Cloud Computing

Ecological Implications of the Dynamics of Water Volume Growth in a Reservoir

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