Population Competition Model Research Articles

Fractal control and synchronization of population competition model based on the T–S fuzzy model

It is of great significance to study the law of population change in species protection, resource utilization, ecological stability, and so on. The fractal behavior of the population competition model is discussed from the fractal viewpoint. By using the sector nonlinear method, the Takagi–Sugeno (T–S) fuzzy model of the population competition model is established, and the Julia set of the population competition model based on the T–S fuzzy model is introduced. The parallel distributed compensation (PDC) is used to design the corresponding fuzzy controller, and sufficient conditions for the stability of the system are given in the form of linear matrix inequalities (LMIs). The parameters of controller gain are obtained by solving LMIs, and the control of the Julia set of the population competition model based on the T–S fuzzy model is carried out. Using the exact linearization technique, the synchronization of the Julia sets of the population competition models is realized based on the T–S fuzzy model by the linear control method, and the Julia set diagram of the corresponding population competition model is analyzed.

A Hybrid Parallel Balanced Phasmatodea Population Evolution Algorithm and Its Application in Workshop Material Scheduling.

The phasmatodea population evolution algorithm (PPE) is a recently proposed meta-heuristic algorithm based on the evolutionary characteristics of the stick insect population. The algorithm simulates the features of convergent evolution, population competition, and population growth in the evolution process of the stick insect population in nature and realizes the above process through the population competition and growth model. Since the algorithm has a slow convergence speed and falls easily into local optimality, in this paper, it is mixed with the equilibrium optimization algorithm to make it easier to avoid the local optimum. Based on the hybrid algorithm, the population is grouped and processed in parallel to accelerate the algorithm's convergence speed and achieve better convergence accuracy. On this basis, we propose the hybrid parallel balanced phasmatodea population evolution algorithm (HP_PPE), and this algorithm is compared and tested on the CEC2017, a novel benchmark function suite. The results show that the performance of HP_PPE is better than that of similar algorithms. Finally, this paper applies HP_PPE to solve the AGV workshop material scheduling problem. Experimental results show that HP_PPE can achieve better scheduling results than other algorithms.

Dynamic tightness evaluation of salt cavern energy storage

Salt cavern tightness evaluation is a prerequisite for salt cavern energy storage. The current salt cavern tightness testing method can only qualitatively evaluate the salt cavern tightness. In this paper, using logging data from a 61-day closed well in a salt cavern of the Jianghan gas storage cavern, a classification model is developed to analyze the factors affecting salt cavern tightness. A hierarchical model is established to analyze the influence weights of temperature and pressure on salt cavern tightness. A population competition model is constructed to analyze the relative importance of pressure and temperature in evaluating salt cavern tightness. Combined with the results of the above analysis, a principal component analysis evaluation model of salt cavern tightness at different moments is established. The accuracy of the evaluation model is verified by combining pressure data. Then, a prediction model is established to analyze the late changes in pressure. The results of the models show that the pressure change has the greatest influence on the salt cavern tightness. The possibility of salt cavern tightness destabilization increases in the pressure anomaly region. The established dynamic evaluation method of salt cavern tightness has a reference value for the engineering practice.

Discrete Population Competition Model of Poisonous Weed Invasion and Spatial Distribution

Poisonous weeds invade ecosystems and compete with edible forage grassland, changing the population spatial distribution. In this paper, a discrete population competition model for the interaction between poisonous weeds and edible forage grass is established, and a diffusion coefficient to describe the invasion and diffusion effect of poisonous weeds is introduced. By using cellular automata methods, the influence of invasive diffusion of poisonous weeds on the spatial distribution of poisonous weed and edible forage populations is simulated. These findings indicated that the invasion of poisonous weeds affected the ecological distribution of grassland, and that the spatial distribution of poisonous weeds also changed from initial uniform distribution to aggregated distribution.

Improvement of the population competition model

Classic population competition model with fixed parameters can only be used under the condition of constant living environment, which is impossible in real life. So it has little practical significance in some cases. In this paper, the model will be improved so that it can be used in a changeable living environment. The objective is to establish the relationship between model parameters and independent variables of external conditions with multivariate regression. Growth curves of populations competing with each other are obtained by piecewise prediction. The data used in the regression are obtained by doing experiments. This paper will take wood rot fungus as an example to explain how to establish the relationship by doing experiments, and apply the new model and the classic one with artificial simulation data, so that two groups of predicted population competition curves are obtained. It has been found that the new model can more accurately describe population competition in the case of severe fluctuations in external environment, while the classic model has obvious errors. Finally, this paper briefly describes other advantages of the new model.

The decomposition of woody fibers by multiple fungi and their interaction

In this paper, we study the fungal community in which woody fibers are decomposed through fungal activity. Firstly, by analyzing the data of fungal traits, we establish Model I: a model for the decomposition of woody fibers by multiple fungi and their interaction. Secondly, under the existing microbiology research, we establish Model II: The Fungal Population Competition Model, to predict the relative advantages of species combinations in different environments and the importance and role of biodiversity. For this question, we extract the data of different fungi’s hyphal extension rate, moisture tolerance and decomposition rate. Then by modeling the Binary Nonlinear Regression model based on the least square method, we describe the breakdown of ground litter and woody fibers through two traits of fungi. Finally, we analyze the accuracy and sensitivity of the model, and prove that our model is accurate and stable for different parameters. Also, we discuss the latest developments in the role of fungi in ecosystems.

Study on the Relationship between the Interaction of Different Fungi and Environment Change

Fungi, as decomposers, mainly decompose wood fibers and litter. The decomposition of wood fiber and litter is an important part of the ecosystem cycle. The aim of this study is to establish a fungal population competition model to simulate the effects of the intrinsic characteristics of fungi on the interactions between different fungi. In addition, the effects of short - and long-term climatic changes on fungal community interactions, as well as the advantages and disadvantages of fungi in communities under different climatic conditions are studied. This study hopes to find and predict the rules between the fungal decomposition process and the ecological environment, and explore the effects of fungal species diversity on the ecosystem. First use ARIMA (0,1,0) to predict the trend of temperature change in Europe in the next three years, and then use Power BI to predict the trend of precipitation change in Europe in the next three years. Next using Linear interpolation method for curve fitting, fitting out the temperature - humidity - fungal distribution density diagram, and then for a long-term in Europe (2009-2023 - the temperature of precipitation data) and short-term rainfall anomaly in London (2018-2019 years) in the diagram, respectively for long-term and short-term trend of fungal distribution density changing with time.

Dynamic Analysis of a Population Competition Model with Disease in One Species and Group Defense in Another Species

In this paper, we study the dynamics of an ecoepidemic competition system where the individuals of one population gather together in herds with a defensive strategy, showing social behavior, while another predator population is subject to a transmissible disease and behaves individually. By analyzing the existence and stability of the equilibria of the system, we find that the relatively isolated population can be eradicated, or the population with group defense can live alone eventually under some constraints. Infected individuals end up in two possible situations. In the first case, the disease is eventually eliminated, meaning that only healthy and group-defense individuals in the system can survive. In the other case, the spread of the disease is controlled and eventually all three individuals can coexist. We also conduct a correlation analysis using competition parameter and recovery rate of disease as birfurcation parameters in order to study the transcritical bifurcation, saddle-node bifurcation and Hopf bifurcation. The long-term dynamics of the boundary and interior equilibria are demonstrated by numerical simulations.

Externally controlled Lotka-Volterra dynamics in a linearly polarized polariton fluid.

Spontaneous formation of transverse patterns is ubiquitous in nonlinear dynamical systems of all kinds. An aspect of particular interest is the active control of such patterns. In nonlinear optical systems this can be used for all-optical switching with transistorlike performance, for example, realized with polaritons in a planar quantum-well semiconductor microcavity. Here we focus on a specific configuration which takes advantage of the intricate polarization dependencies in the interacting optically driven polariton system. Besides detailed numerical simulations of the coupled light-field exciton dynamics, in the present paper we focus on the derivation of a simplified population competition model giving detailed insight into the underlying mechanisms from a nonlinear dynamical systems perspective. We show that such a model takes the form of a generalized Lotka-Volterra system for two competing populations explicitly including a source term that enables external control. We present a comprehensive analysis of both the existence and stability of stationary states in the parameter space spanned by spatial anisotropy and external control strength. We also construct phase boundaries in nontrivial regions and characterize emerging bifurcations. The population competition model reproduces all key features of the switching observed in full numerical simulations of the rather complex semiconductor system and at the same time is simple enough for a fully analytical understanding.

Analysis on the market evolution of new energy vehicle based on population competition model

New energy vehicles (NEVs) development has recently become China's national strategy. For NEVs, the scientific prediction of market scale is the guarantee to formulate the effective policy planning. Considering the competition and substitution phenomenon between traditional fuel vehicles (TFVs) and NEVs, we propose a system dynamics (SD) model to investigate and predict the market evolution of NEVs and TFVs in China based on the competitive Lotka-Volterra (LV) model. Furthermore, the effect mechanism of key model parameters is evaluated by sensitivity analysis. Finally, the potential environmental impacts of NEVs in China are analyzed based on the above simulation results. It shows that NEVs will continue to grow rapidly in the coming decades and will dominate in Chinese vehicle market around 2050. Government subsidies and other consumption stimulus factors are the main driving force for NEVs development in its early stages, however, along with the policy stimulus and policy influence gradually weakening, growth in later stages will rely on convenience factors and cost advantages brought by technological progress and infrastructure improvements. It is noteworthy that the national strategic planning target in 2020 can hardly be achieved under China’s current policy system and market conditions. The results of sensitivity analysis reveal that the policy support and maximum market capacity show different decisive influences on the development trend of the entire automotive market. In addition, if China's relevant energy and environmental planning can be effectively implemented, the rapid expansion of NEVs will significantly reduce the environmental impact of vehicles.

Dynamics in a parabolic–elliptic two-species population competition model with cross-diffusion for one species

This work deals with a simplified parabolic–elliptic population competition model with cross-diffusion for one species. We first claim that this model has at least a non-trivial global smooth solution, and then we detect explicit parameter ranges under which the coexistence steady state and the two semi-trivial steady states are globally and asymptotically stable.

Customer social network affects marketing strategy: A simulation analysis based on competitive diffusion model

Abstract To explain the competition phenomenon and results between QQ and MSN (China) in the Chinese instant messaging software market, this paper developed a new population competition model based on customer social network. The simulation results show that the firm whose product with greater network externality effect will gain more market share than its rival when the same marketing strategy is used. The firm with the advantage of time, derived from the initial scale effect will become more competitive than its rival when facing a group of common penguin customers within a social network, verifying the winner-take-all phenomenon in this case.

Fractal analysis and control of the competition model

Lotka–Volterra population competition model plays an important role in mathematical models. In this paper, Julia set of the competition model is introduced by use of the ideas and methods of Julia set in fractal geometry. Then feedback control is taken on the Julia set of the model. And synchronization of two different Julia sets of the model with different parameters is discussed, which makes one Julia set change to be another. The simulation results show the efficacy of these methods.

A population-competition model for analyzing transverse optical patterns including optical control and structural anisotropy

We present a detailed study of a low-dimensional population-competition (PC) model suitable for analysis of the dynamics of certain modulational instability patterns in extended systems. The model is applied to analyze the transverse optical exciton–polariton patterns in semiconductor quantum well microcavities. It is shown that, despite its simplicity, the PC model describes quite well the competitions among various two-spot and hexagonal patterns when four physical parameters, representing density saturation, hexagon stabilization, anisotropy, and switching beam intensity, are varied. The combined effects of the last three parameters are given detailed considerations here. Although the model is developed in the context of semiconductor polariton patterns, its equations have more general applicability, and the results obtained here may benefit the investigation of other pattern-forming systems. The simplicity of the PC model allows us to organize all steady state solutions in a parameter space ‘phase diagram’. Each region in the phase diagram is characterized by the number and type of solutions. The main numerical task is to compute inter-region boundary surfaces, where some steady states either appear, disappear, or change their stability status. The singularity types of the boundary points, given by Catastrophe theory, are shown to provide a simple geometric overview of the boundary surfaces. With all stable and unstable steady states and the phase boundaries delimited and characterized, we have attained a comprehensive understanding of the structure of the four-parameter phase diagram. We analyze this rich structure in detail and show that it provides a transparent and organized interpretation of competitions among various patterns built on the hexagonal state space.

America, China and India: A 3-D competition model for economic & strategic interests in South East Asia

This paper provides a new and different perspective on the competition-collaboration dynamic in business and international relations, using a hypothetical model involving three nations—the United States, China and India. While the United States has been preoccupied with internal squabbles and external wars, India and China have been quietly emerging as powerful Asian states, building relationships both economic and military. The two countries have had a competitive relationship for several decades, not the least of which has been competing for a more muscular economic, political, and military alliance with the United States. This paper seeks to identify the relationships between the two nations and the United States in an effort to quantify the conditions under which a stable three-way balance of power may exist, using classic competition modeling. Simulations demonstrate stable coexistence when each market consumes most of the resource for which the other two are better competitors, oscillations in market dominance when each consumes most of the resource for which one is a better competitor and one is a worse competitor, and unstable coexistence or extinction when each market consumes most of the resource for which it is the better competitor. The population competition model employed for analysis is a novel way to look at collaboration and competition within multination treaties. This quantitative paper is a first step to a later qualitative analysis of the values presented.

Global stability in a structured population competition model with distributed maturation delay and harvesting

This paper is concerned with a delay differential equation model for the interaction between two species, the adult members of which are in competition, with stage-structure and harvesting of the mature and immature members of each species. The maturation delay for each species is modelled as a distribution, to allow for the possibility that individuals may take a different amount of time to mature. General birth and death rate functions are used. We find that the dynamics of the model depends largely on the birth and death functions, which depend on the total number of adults. We study the dynamics of our model analytically and we present results on the positivity and boundedness of the solutions, and global stability results are established for each equilibrium.

A novel ecological particle swarm optimization algorithm and its population dynamics analysis

This paper presents a novel particle swarm optimization algorithm from the angle of ecological population evolution, called the ecological particle swarm optimization, or EPSO. Initially, ecological population competition model (EPCM) is presented. From the basis of the EPCM, the EPSO algorithm and its general framework are proposed; in which particle swarm system with ecological hierarchy and competition model is defined and two collocating strategies of inertia weight factor are considered. The convergence performance and population dynamics including population aggregation and population diversity of the proposed approach are discussed separately through empirical simulations with well-known benchmarks from the standard literature.

Basins of Attraction and Perturbed Numerical Solutions using Euler's Method

Small uncertainties in a dynamical system due to imperfect measurements or variations in the environment can dramatically impact the long term behavior of a trajectory. This phenomenon is studied in a population competition model by introducing a random error term into a numerical solver and investigating the effect on the behavior of solutions. Two methods for analyzing the impact of a random term are demonstrated.