The Research On Biological Evolution Model Based On Bit-String

Biological evolution is one of important phenomena in life science.Due to rapid developments in computing capability,modeling and numerical simulation methods have been applied to analyze biological evolution in many studies.These studies have shown the feasibility and necessity of the methods from different aspects.However some of them were not efficient due to insufficiency in individual information revelation.The model proposed by Penna TJP in 1995 has then used a computer Bit-String to represent an individual,i.e.,the genome of this individual.The death and reproduction rules are introduced in Penna model by considering environment,age,gene and mutation based on mutation accumulation hypothesis.And the dynamics of population is simulated in this model. Since Penna model can explain many biological phenomena and their meaning,it has been used widely and feasibly.Introduction to Penna model and review of it applications are given in Chapter 1.Our contributions to the model's application are then introduced in the chapters that follow.Disease dynamics model based on the Bit-String model is given in Chapter 2.Firstly,the extragenetic disease is considered by adding another Bit-String.Based on this model the influences of disease-resistant and cure capability of species are discussed.Secondly,a cellular automata model is developed to study the epidemic on a two dimensional lattice.The influences of infection and death rates on the number of epidemical patients are discussed. Thirdly,the infection information is also denoted by a Bit-String corresponding to individual information.The hamming distance with age difference between individual and infection virus is defined.The existence and extinction for a certain infection on the process of evolution are discussed.An intelligence model based on Bit-String and its application are given in Chapter 3. Firstly,an individual of intelligence is defined with the transmissibility of intelligence.And the evolution of population size and intelligence are discussed.Secondly,an evolutionary model based on Bit-String with intelligence and learning capability is constructed considering the influence of knowledge on survival of the individual.Then,the results of our simulations are presented and the evolution of population,intelligence and knowledge are discussed respectively.The results show that learning knowledge contributes to the evolution of intelligence,especially for children.In addition,the distribution of intelligence quotient is good agreement with observation.Thirdly,a learning model on the basis of Bit-String model with intelligence is set up.The individuals are set on the lattice.Then,the evolution of intelligence and knowledge are discussed.Results show that the intelligence for living individuals is more than that for dead ones.The effect of natural selection on the evolution of intelligence can then be summarized.Finally,a prey-predator model of learning based on Bit-String with intelligence is developed.The capacity of escape and predation for the individual depends on intelligence and knowledge,and the successful experience can be cumulated.The results show that for coexistence of predator and prey,higher average knowledge of the predator automatically leads to higher average intelligence of the prey.It can be concluded that every species has certain advantage.Thus they can coexist in an ecosystem forever.Another contribution to the Bit-String model application is given in Chapter 4.Firstly, the Bit-String model with seasonal characteristics is presented.And then the "fishing fallow" policy and practice in China are discussed in this model.The conclusion is that though the policy is good for the species expanding,it would be significant only if fishing intensity is beyond a certain range.If the fishing intensity is limited below a certain level,appropriate fishing may lead to the highest production,not "fishing fallow".Therefore reducing fishing intensity is essential,but "fishing fallow" is only conditional.Secondly,a cellular automata model containing movable wolves,sheep and reproducible grass is set up.And the final states of this ecosystem are discussed.Thirdly,the information entropy is introduced in Bit-String model to discuss common ancestor and genetic diversity.We discuss the formation mechanism of common ancestor and the production mechanism of genetic diversity from the variation law of entropy.The thesis is then concluded in a short summary.