Local existence and uniqueness of solutions to the evolutionary model for magnetoviscoelasticity

In this paper,we prove the local existence and uniqueness of solutions to the evolutionary model for magnetoviscoelasticity in R^(2),R^(3).This model consists of an incompressible Navier-Stokes,a regularized system for the evolution of the deformation gradient and the Landau-Lifshitz-Gilbert system for the dynamics of the mag-netization.Our approach depends on approximating the system with a sequence of perturbed systems.

EVOLUTIONARY MODEL OF FREE ECONOMIC ZONES——Different Generations and Structural Features

Free economic zone (FEZ) has a long history and plays a more and more important role in the world economy. Most studies, however, focused on the theoretical analysis of benefit and cost as well as the economic role of FEZ in the less developed countries and little attention has been paid to the evolution of FEZ. This paper will improve the above-mentioned studies and put forward the structural and spatial evolutionary model of FEZ by analyzing the development of objectives, preferential policy, governance structure, industrial sectors and location of FEZs based on the international economic and political development. FEZs develop towards: 1) more comprehensive and macro objectives, 2) more industry-oriented and multi-preferential policies, 3) more cross-national and combination zones with administrative areas, 4) more technology-intensive and multi-industries, 5) more flexible location and larger spatial dimensions, 6) more rapid evolution and typologies, and 7) more economic integration to the host economy.

Application of the Stress Evolutionary Model in Hebei Province,North China

Coulomb stress changes associated with strong earthquakes occurring since 1484 in Hebei Province,China are investigated. The North China block has had many large historical earthquakes and some damaging earthquakes in the past century,including the 1976 Tangshan earthquake (M =7.8) . The study area and the adjacent areas of the province comprise the most active seismic fault zones and suffer from both strong and frequent events. The North China Block,which includes the Ordos plateau and the North China plain,is part of the Archean Sino-Lorean craton and one of the most active seismic regions in the world. Its movement is accommodated on major strike-slip intraplate fault zones that strike in the E-W direction. The faults in the study area contribute to the complexity of the stress field. Seismic hazard assessment in this region is attempted by calculating the change of the Coulomb failure function ( ΔCFF) arising from both the coseismic slip of strong events (MS≥6.5) and the stress built up by continuous tectonic loading on major regional faults. At every step of the stress evolutionary model an examination of possible triggering of each next strong event is made and the model finally puts in evidence that the fault segments that are apt to fail in an impending strong event,thus providing future seismic hazard evaluation. In this paper,the results of ΔCFF for Zhangjiakou fault, Xiadian fault and Langfang fault have been shown as examples to express the possiblity of generating future seismic hazard.

Dynamics of Advantageous Mutant Spread in Spatial Death-Birth and Birth-Death Moran Models

The spread of an advantageous mutation through a population is of fundamental interest in population genetics. While the classical Moran model is formulated for a well-mixed population, it has long been recognized that in real-world applications, the population usually has an explicit spatial structure which can significantly influence the dynamics. In the context of cancer initiation in epithelial tissue, several recent works have analyzed the dynamics of advantageous mutant spread on integer lattices, using the biased voter model from particle systems theory. In this spatial version of the Moran model, individuals first reproduce according to their fitness and then replace a neighboring individual. From a biological standpoint, the opposite dynamics, where individuals first die and are then replaced by a neighboring individual according to its fitness, are equally relevant. Here, we investigate this death-birth analogue of the biased voter model. We construct the process mathematically, derive the associated dual process, establish bounds on the survival probability of a single mutant, and prove that the process has an asymptotic shape. We also briefly discuss alternative birth-death and death-birth dynamics, depending on how the mutant fitness advantage affects the dynamics. We show that birth-death and death-birth formulations of the biased voter model are equivalent when fitness affects the former event of each update of the model, whereas the birth-death model is fundamentally different from the death-birth model when fitness affects the latter event.

Evolutionary model of the central place hierarchical system

Central place theory is one of the two theoretical cornerstones of geography, yet it cannot be connected with other spatial structure models, fails to provide definite time-space parameter conditions, lacks an evolutionary process model, and does not easily enable construction of a complete theoretical system of regional spatial structure. This paper gives an in-depth analysis of the process and mechanism for production and evolution of central places of different grades, and constructs an evolutionary model of the central place hierarchical system. The results of deduction, analysis and simulation show that production and evolution of the central place hierarchical system may be divided into five stages. These stages are the embryonic, formative, improvement, maturation, and advancement stages. Affected by spatial location and centricity, central places have obvious differences in scale and functional structures. There are great differences in the scale of same-grade central places. However, low-grade central places could have larger scales than high-grade central places, and the central places of a central location may form the agglomeration area of central places. Based on the hypothesis condition of an isotropic plain, the research shows that it is possible not only to form proportional functional structures of central places, but also to produce non-proportional scale structures of central places, and thus to complete the transformation from rationalistic deduction of spatial equilibrium mode to an explanation and demonstration of an unbalanced practical model.

Financial Data Modeling by Using Asynchronous Parallel Evolutionary Algorithms

In this paper, the high-level knowledge of financial data modeled by ordinary differential equations (ODEs) is discovered in dynamic data by using an asynchronous parallel evolutionary modeling algorithm (APHEMA). A numerical example of Nasdaq index analysis is used to demonstrate the potential of APHEMA. The results show that the dynamic models automatically discovered in dynamic data by computer can be used to predict the financial trends.

The Evolutionary Modeling and Short-range Climatic Prediction for Meteorological Element Time Series

The time series of precipitation in flood season (May-September) at WuhanStation, which is set as an example of the kind of time series with chaos characters, is split intotwo parts: One includes macro climatic timescale period waves that are affected by some relativelysteady climatic factors such as astronomical factors (sunspot, etc.), some other known and/orunknown factors, and the other includes micro climatic timescale period waves superimposed on themacro one. The evolutionary modeling (EM), which develops from genetic programming (GP), is supposedto be adept at simulating the former part because it creates the nonlinear ordinary differentialequation (NODE) based upon the data series. The natural fractals (NF) are used to simulate thelatter part. The final prediction is the sum of results from both methods, thus the model canreflect multi-time scale effects of forcing factors in the climate system. The results of thisexample for 2002 and 2003 are satisfactory for climatic prediction operation. The NODE can suggestthat the data vary with time, which is beneficial to think over short-range climatic analysis andprediction. Comparison in principle between evolutionary modeling and linear modeling indicates thatthe evolutionary one is a better way to simulate the complex time series with nonlinearcharacteristics.

A Hybrid Model for the Mid-Long Term Runoff Forecasting by Evolutionary Computation Techniques

The mid-long term hydrology forecasting is one of most challenging problems in hydrological studies. This paper proposes an efficient dynamical system prediction model using evolutionary computation techniques. The new model overcomes some disadvantages of conventional hydrology forecasting ones. The observed data is divided into two parts; the slow 'smooth and steady' data, and the fast 'coarse and fluctuation' data. Under the divide and conquer strategy, the behavior of smooth data is modeled by ordinary differential equations based on evolutionary modeling, and that of the coarse data is modeled using gray correlative forecasting method. Our model is verified on the test data of the mid-long term hydrology forecast in the northeast region of China. The experimental results show that the model is superior to gray system prediction model (GSPM).

Hysteresis behavior and nonequilibrium phase transition in a one-dimensional evolutionary game model

We investigate a simple evolutionary game model in one dimension. It is found that the system exhibits a discontinuous phase transition from a defection state to a cooperation state when the b payoff of a defector exploiting a cooperator is small. Furthermore, if b is large enough, then the system exhibits two continuous phase transitions between two absorbing states and a coexistence state of cooperation and defection, respectively. The tri-critical point is roughly estimated. Moreover, it is found that the critical behavior of the continuous phase transition with an absorbing state is in the directed percolation universality class.

Dynamic Behavior Modeling in Multi-Agent System By Evolutionary Programming

In a multi-agent system, each agent must adapt itself to the environment and coordinate with other agents dynamically. TO predict or cooperate with the behavior of oiller agents. An agent should dynamically establish and evolve the cooperative behavior model of itself. In this paper, we represent the behavior model of an agent as a f-mite state machine and propose a new method of dynamically evolving the behavior model of an agent by evolutionary programming.

Progresses and future directions on yardangs

Background,aim,and scope Yardang is a kind of typical wind-eroded landform in arid zones both on Earth and other planets.Their geomorphic process records the surface changes and climate,which may play a vital role in exploring the coupled landform-atmosphere system in arid zones.Recently,significant progresses have been made in this research field,and a review is still absent,which is the aim of the paper.Materials and methods Previous studies on the distribution,composition,morphology,and climatic driving force of yardang landform were reviewed.Results Earth yardang’s three evolutionary models were generalized:morphology evolution model,altitude evolution model and climate driven evolution model.Extraterrestrial yardang and its evolution are also summarized:the morphology is dominated by long ridges on Venus and Titan,and three yardang evolution hypotheses and an indirect dating method based on stratigraphic contact have been studied on Mars.Discussion In this study,firstly,the definition and morphology of yardang were described to define its characteristics.Secondly,we argue that yardang evolution has two dimensions:short-term variation and longterm variation.In the short-term variation,the morphological evolution of yardang on earth can be divided into four stages:embryonic stage,juvenile stage,mature stage,and demise stage.In the long-term variation,the evolution of yardang on earth is climate-driven,i.e.,it is controlled by atmospheric circulation changes during glacial-interglacial periods.Thirdly,yardang research on extraterrestrial bodies was also summarized:yardang has been found on Mars,Venus,and Titan,and the research focus by far are on geomorphology only.Conclusions(1)Yardang landform is an erosion landform with alternating ridges and troughs,with main form of whale back shape and fluctuations in the range of aspect ratios;(2)the short-term variation of yardang is manifested in its morphological evolution and height change,while the long-term variation is climate-driven;(3)based on Earth yardang,extraterrestrial yardang research has been carried out on Mars,Venus,and Titan.Recommendations and perspectives We then proposed that:(1)yardang formation ages,due to the erosion characteristics,are difficult to constraint;(2)the wind erosion capacity in the yardang areas might have been severely underestimated,making it essential to re-evaluate the previous paleoclimate reconstruction in the closed basins with limited chronological data;(3)yardang evolution is driven by climate change,but the coupling relationship between the yardang geomorphy and the air circulation is still unclear.Finally,future research directions:(1)more chronological data are needed,as well as the wind erosion capacity for yardang initiation and development;(2)the co-evolution of mid-low latitude landforms involved in yardang long-term variation and its relationship with global atmospheric circulation.

Path-dependent speciation in dynamic fitness landscapes

Species is a fundamental concept in evolutionary biology and biodiversity.However,existing species definitions are often influenced by artificial factors or are challenging in practical application,leading to confusion in species classification.Due to uncertain environmental changes and random genetic drift,the fitness expectations of a population may shift,causing species to evolve to a new evolutionary state based on their current instantaneous fitness within a dynamic fitness landscape.This contrasts with the classic static fitness landscape,where fitness expectations are constant.In a dynamic fitness landscape,speciation may exhibit path dependence,where the evolution of traits follows a probabilistic path,creating feedback that shapes evolutionary trajectories.The path-dependent evolutionary mechanism suggests that species survival within an ecosystem is not directly determined by their fitness but by the probability of their evolutionary pathways.This model also indicates that species can coexist with varying probabilities under limited environmental pressures.Consequently,new species,cryptic species,or sympatric species may emerge via path-dependent evolutionary processes.Within this framework,we developed a mathematical species concept,which may guide future species classification methodologies.

Parallel Implementations of Modeling Dynamical Systems by Using System of Ordinary Differential Equations

First, an asynchronous distributed parallel evolutionary modeling algorithm (PEMA) for building the model of system of ordinary differential equations for dynamical systems is proposed in this paper. Then a series of parallel experiments have been conducted to systematically test the influence of some important parallel control parameters on the performance of the algorithm. A lot of experimental results are obtained and we make some analysis and explanations to them.

Analyzing Industrial Structure Evolution of Old Industrial Cities Using Evolutionary Resilience Theory：A Case Study in Shenyang of China

The recession and revitalization of old industrial cities concerns urban industrial evolution and its characteristics. Based on the theory of evolutionary resilience, we developed an analytical framework for the industrial structure evolution of old industrial cities, and applied the framework to a case study in Shenyang. The following conclusions are drawn. First, since 1978, Shenyang's industrial growth capacity has shown fluctuation between ‘contraction-expansion'. As the secondary industry has a much stronger expansionary and contractionary capacity for growth, this results in lacking stability leading to industrial structure transformation. Second, since 1999, the orientation towards a high-end manufacturing industry in Shenyang has weakened, and the evolution of the new and old growth path is characterized by low-end orientation. Third, since 2007, Shenyang's industrial innovation output capacity has dropped sharply which has been significantly affected by scientific and technological personnel and enterprise-owed science and technology institutions and to a less extent by R&D expenditure. We applied the resilience theory to study the industrial evolution of an old industrial city, explored new study perspectives on industrial evolution and verified the applicability of the resilience theory. This paper provides a scientific reference for understanding the recent deceleration in economic growth in the Northeast old industrial base, and for exploring new paths toward revitalization.

Parameter Optimization Method for Gaussian Mixture Model with Data Evolution

To learn from evolutionary experimental data points effectively,an evolutionary Gaussian mixture model based on constraint consistency(EGMM)is proposed and the corresponding method of parameter optimization is presented.Here,the Gaussian mixture model(GMM)is adopted to describe the data points,and the differences between the posterior probabilities of pairwise points under the current parameters are introduced to measure the temporal smoothness.Then,parameter optimization of EGMM can be realized by evolutionary clustering.Compared with most of the existing data analysis methods by evolutionary clustering,both the whole features and individual differences of data points are considered in the clustering framework of EGMM.It decreases the algorithm sensitivity to noises and increases the robustness of evaluated parameters.Experimental result shows that the clustering sequence really reflects the shift of data distribution,and the proposed algorithm can provide better clustering quality and temporal smoothness.

Stock Prediction Based on Technical Indicators Using Deep Learning Model

Stock market trends forecast is one of the most current topics and a significant research challenge due to its dynamic and unstable nature.The stock data is usually non-stationary,and attributes are non-correlative to each other.Several traditional Stock Technical Indicators(STIs)may incorrectly predict the stockmarket trends.To study the stock market characteristics using STIs and make efficient trading decisions,a robust model is built.This paper aims to build up an Evolutionary Deep Learning Model(EDLM)to identify stock trends’prices by using STIs.The proposed model has implemented the Deep Learning(DL)model to establish the concept of Correlation-Tensor.The analysis of the dataset of three most popular banking organizations obtained from the live stock market based on the National Stock exchange(NSE)-India,a Long Short Term Memory(LSTM)is used.The datasets encompassed the trading days from the 17^(th) of Nov 2008 to the 15^(th) of Nov 2018.This work also conducted exhaustive experiments to study the correlation of various STIs with stock price trends.The model built with an EDLM has shown significant improvements over two benchmark ML models and a deep learning one.The proposed model aids investors in making profitable investment decisions as it presents trend-based forecasting and has achieved a prediction accuracy of 63.59%,56.25%,and 57.95%on the datasets of HDFC,Yes Bank,and SBI,respectively.Results indicate that the proposed EDLA with a combination of STIs can often provide improved results than the other state-of-the-art algorithms.

Improved mammalian family phylogeny using gap-rare multiple sequence alignment:A timetree of extant placentals and marsupials

The timing of mammalian diversification in relation to the Cretaceous-Paleogene(KPg)mass extinction continues to be a subject of substantial debate.Previous studies have either focused on limited taxonomic samples with available whole-genome data or relied on short sequence alignments coupled with extensive species samples.In the present study,we improved an existing dataset from the landmark study of Meredith et al.(2011)by filling in missing fragments and further generated another dataset containing 120 taxa and 98 exonic markers.Using these two datasets,we then constructed phylogenies for extant mammalian families,providing improved resolution of many conflicting relationships.Moreover,the timetrees generated,which were calibrated using appropriate molecular clock models and multiple fossil records,indicated that the interordinal diversification of placental mammals initiated before the Late Cretaceous period.Additionally,intraordinal diversification of both extant placental and marsupial lineages accelerated after the KPg boundary,supporting the hypothesis that the availability of numerous vacant ecological niches subsequent to the mass extinction event facilitated rapid diversification.Thus,our results support a scenario of placental radiation characterized by both basal cladogenesis and active interordinal divergences spanning from the Late Cretaceous into the Paleogene.

Investigation on Relationship between Cost and Software Reliability

Based on the fact that the software development cost is an important factorto control the whole project, we discuss the relationship between the software development cost andsoftware reliability according to the empirieal data collected from the development process. Byevolutionary modeling we get an empirical model of the relationship between cost and softwarereliability, and validate the estimate results with the empirical data.

Hydrocarbon Generation Characteristics of Source Rocks from Different Saline Environments in the Dongpu Depression,Bohai Bay Basin,China

The Dongpu Depression is a secondary salt-bearing tectonic unit in the Bohai Bay Basin,eastern China.The depositional environment of this depression regarding its Paleogene strata is clearly different in plane,including the saltwater environment(SE)in the north,the freshwater environment(FE)in the south and the brackish water environment(BE)in the middle.The result of oil and gas exploration in the Dongpu Depression shows that more than 90%of the proven oil reserves are distributed in the northern saltwater environment.Previous studies indicate that the organic geochemistry characteristics and the hydrocarbon generation capacity of the source rocks are very clearly diverse under different environments,which results in the significant differences in the proved reserves between the north and the south.In order to further explore the differences in the hydrocarbon generation capacity of the source rocks under distinct depositional environments and the mechanism of their occurrence,three samples from different depositional environments(W18-5 for SE,H7-18 for BE,CH9 for FE)were used for confined gold tube pyrolysis experiments.The results show that the CH4 yields of W18-5,H7-18 and CH9 increase with increasing temperature,the maximum yields being 405.62 mg/g TOC,388.56 mg/g TOC and 367.89 mg/g TOC,respectively.The liquid hydrocarbon yields of W18-5,H7-18 and CH9 firstly increase with increasing temperature and then decrease after the critical temperatures.The maximum yields of C6-14 are 149.54 mg/g TOC,140.18 mg/g TOC and 116.94 mg/g TOC,the maximum yields of C14+being 852.4 mg/g TOC,652.6 mg/g TOC and 596.41 mg/g TOC,respectively for W18-5,H7-18 and CH9.To summarize,the order of hydrocarbon potential from high to low is W18-5,H7-18 and CH9.On this basis,through analyzing the influencing factors of hydrocarbon differences,this paper reveals that the saltwater environment is characterized by 4 factors:higher salinity,halophilic algae,high paleo-productivity and a strongly reducing environment,which are beneficial to the enrichment of organic matter and lead to the formation of high levels of sapropelite and exinite.According to the variation of oil and gas components in the pyrolysis experiments,the hydrocarbon generation process is divided into three stages:kerogen cracking,oil cracking and C2-5 cracking.Combined with hydrocarbon generation characteristics and stages,the evolutionary model of hydrocarbon generation for source rocks under different environments is established.

A Simulation Study on the Evolution of Groundwater Circulation Systems in Cenozoic Basins of Northern China

Three Cenozoic basins—the Qaidam basin, the Weihe graben-type basin and the North China plain—which are different in climatic conditions, geological settings and run—off types, are selected for the study. Based on an analysis of background information of the transect along the middle-latitude region, studies of groundwater dynamics, geochemistry, simulation of water circulation of the main elements as well as isotopic chronology, the information on global changes is collected, the formation of groundwater circulation systems and their evolution under stacked impacts of natural conditions and human activities are discussed, and a correlation is made between the evolutionary features of the above systems in these basins since 25 ka B.P. All these have laid a good foundation for further generalizing the evolutionary model of land water in northern China.