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1.
Three continuous marine fish cell lines of FG (i. e., Hounder Gill) from flounder (Paralichthys olivaceus) gill, SPH (i. e. , Sea Perch Heart) from sea perch (Lateolabrax japonicus) heart and RSBF (i.e., Red Sea Bream Fin) from red sea bream (Pagrosomus major) fin, were characterized by lactate dehydrogenase (LDH) isozyme and morphological analysis. The LDH isozyme patterns of these three cell lines and their corresponding tissues of origin were investigated and compared. The results showed: (1) No difference was found in the LDH isozyme patterns of FG and flounder gill tissue. However, the LDH isozyme patterns of SPH and RSBF were significantly different from their corresponding tissues of origin; (2) LDH isozyme patterns of FG, SPH and RSBF were markedly different from each other and could serve as genetic markers for species identification and detection of cross contamination. Morphological change analysis of these three cell lines in comparison to their original tissues indicated that FG cells still appeared epithelioid without morphological transformation. However, morphological changes were found in SPH and RSBF compared to their original tissues. Therefore, the cellular morphology was still plastic in the relatively stable culture conditions, and it was possible that change of LDH patterns wasrelated to morphological changes of fish cells in vitro.  相似文献   
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A cellular model of Holocene upland river basin and alluvial fan evolution   总被引:1,自引:0,他引:1  
The CAESAR (Cellular Automaton Evolutionary Slope And River) model is used to simulate the Holocene development of a small upland catchment (4·2 km2) and the alluvial fan at its base. The model operates at a 3 m grid scale and simulates every flood over the last 9200 years, using a rainfall record reconstructed from peat bog wetness indices and land cover history derived from palynological sources. Model results show that the simulated catchment sediment discharge above the alluvial fan closely follows the climate signal, but with an increase in the amplitude of response after deforestation. The important effects of sediment storage and remobilization are shown, and findings suggest that soil creep rates may be an important control on long term (>1000 years) temperate catchment sediment yield. The simulated alluvial fan shows a complex and episodic behaviour, with frequent avulsions across the fan surface. However, there appears to be no clear link between fan response and climate or land use changes suggesting that Holocene alluvial fan dynamics may be the result of phases of sediment storage and remobilization, or instabilities and thresholds within the fan itself. Copyright © 2002 John Wiley & Sons, Ltd.  相似文献   
4.
基于神经网络的单元自动机CA及真实和忧化的城市模拟   总被引:6,自引:0,他引:6  
提出了一种基于神经网络的单元自动机(CA)。CA已被越来越多地应用在城市及其它地理现象的模拟中。CA模拟所碰到的最大问题是如何确定模型的结构和参数。模拟真实的城市涉及到使用许多空间变量和参数。当模型较复杂时,很难确定模型的参数值。本模型的结构较简单,模型的参数能通过对神经网络的训练来自动获取。分析表明,所提出的方法能获得更高的模拟精度,并能大大缩短寻找参数所需要的时间。通过筛选训练数据,本模型还可以进行优化的城市模拟,为城市规划提供参考依据。  相似文献   
5.
基于遥感与GIS的20世纪90年代中国城镇用地时空特征   总被引:18,自引:1,他引:18  
文章利用20世纪90年代初期、中期和末期全国1:100000土地利用动态变化数据提取城镇用地动态变化数据,利用单元自动机和人工神经网络模型对全国城镇用地进行了区划.在此基础上,研究了90年代两个阶段中国城镇用地时空格局.研究表明:90年代前5年东部沿海地区受经济高速发展和开放政策的影响,城镇用地扩展迅速,中西部地区城镇用地扩展较慢;90年代后5年国家加大了耕地资源保护力度,在政府宏观调控政策和耕地资源保护条例的影响下,东部沿海地区城镇用地扩展大幅回落,中部地区城镇扩展也有较大幅度回落,西部地区随着经济发展加快,城镇用地扩展回落较小.  相似文献   
6.
在城镇化发展水平及土地开发评价的基础上,评价待扩张区域土地转变潜力分值,基于最大转变潜力分值,提出一种有别于传统元胞自动机模拟城市扩张的新方法。该方法与传统元胞自动机模拟城市扩张相比在迭代方式上存在不同,它克服了传统元胞自动机因阈值设置不同而导致结果不确定的难题。分别将该方法与传统元胞自动机模型应用于武汉主城区,模拟了其2003年到2013年的城市扩张情况,最后,将模拟结果与实际土地利用现状图进行对比发现改进后的新方法在模拟精度上大大提高。  相似文献   
7.
元胞自动机结构简单且具备模拟复杂系统的能力,已被广泛应用于大气、流体力学、地球物理等领域。然而,现有元胞自动机以欧氏空间为约束进行地球系统过程模拟,忽略了地球重力等天然约束,导致计算过程中元胞状态的传递方向与真实运动的趋势方向不相符,一定程度上扭曲了最终的模拟结果。本文提出了地球系统元胞自动机这一概念,并从元胞表达及构建、邻居模型等方面设计了基于SDOG-ESSG格网的地球系统元胞自动机框架。由于演化规则取决于不同的应用,因此本文进一步以地壳的热传递为例,通过对热力学方程离散化设计了相应的演化规则。最后,借助公开的数据源开展了地壳热传递元胞自动机模拟的初步试验,并与一定区域下的数值模拟结果展开了比对。试验表明,与数值模拟方法相比,本文方法的模拟结果相对误差控制在27%以内,具备一定程度的可行性,可作为地球系统过程模拟的一种新思路。  相似文献   
8.
Urbanization processes challenge the growth of orchards in many cities in Iran. In Maragheh, orchards are crucial ecological, economical, and tourist sources. To explore orchards threatened by urban expansion, this study first aims to develop a new model by coupling cellular automata (CA) and artificial neural network with fuzzy set theory (CA–ANN–Fuzzy). While fuzzy set theory captures the uncertainty associated with transition rules, the ANN considers spatial and temporal nonlinearities of the driving forces underlying the urban growth processes. Second, the CA–ANN–Fuzzy model is compared with two existing approaches, namely a basic CA and a CA coupled with an ANN (CA–ANN). Third, we quantify the amount of orchard loss during the last three decades as well as for the upcoming years up to 2025. Results show that CA–ANN–Fuzzy with 83% kappa coefficient performs significantly better than conventional CA (with 51% kappa coefficient) and CA–ANN (with 79% kappa coefficient) models in simulating orchard loss. The historical data shows a considerable loss of 26% during the last three decades, while the CA–ANN–Fuzzy simulation reveals a considerable future loss of 7% of Maragheh’s orchards in 2025 due to urbanization. These areas require special attention and must be protected by the local government and decision-makers.  相似文献   
9.
This paper presents a spatial autoregressive (SAR) method-based cellular automata (termed SAR-CA) model to simulate coastal land use change, by incorporating spatial autocorrelation into transition rules. The model captures the spatial relationships between explained and explanatory variables and then integrates them into CA transition rules. A conventional CA model (LogCA) based on logistic regression (LR) was studied as a comparison. These two CA models were applied to simulate urban land use change of coastal regions in Ningbo of China from 2000 to 2015. Compared to the LR method, the SAR model yielded smaller accumulated residuals that showed a random distribution in fitting the CA transition rules. The better-fitting SAR model performed well in simulating urban land use change and scored an overall accuracy of 85.3%, improving on the LogCA model by 3.6%. Landscape metrics showed that the pattern generated by the SAR-CA model has less difference with the observed pattern.  相似文献   
10.
The dynamic relationships between land use change and its driving forces vary spatially and can be identified by geographically weighted regression (GWR). We present a novel cellular automata (GWR-CA) model that incorporates GWR-derived spatially varying relationships to simulate land use change. Our GWR-CA model is characterized by spatially nonstationary transition rules that fully address local interactions in land use change. More importantly, each driving factor in our GWR model contains effects that both promote and resist land use change. We applied GWR-CA to simulate rapid land use change in Suzhou City on the Yangtze River Delta from 2000 to 2015. The GWR coefficients were visualized to highlight their spatial patterns and local variation, which are closely associated with their effects on land use change. The transition rules indicate low land conversion potential in the city’s center and outer suburbs, but higher land conversion potential in the inner near suburbs along the belt expressway. Residual statistics show that GWR fits the input data better than logistic regression (LR). Compared with an LR-based CA model, GWR-CA improves overall accuracy by 4.1% and captures 5.5% more urban growth, suggesting that GWR-CA may be superior in modeling land use change. Our results demonstrate that the GWR-CA model is effective in capturing spatially varying land transition rules to produce more realistic results, and is suitable for simulating land use change and urban expansion in rapidly urbanizing regions.  相似文献   
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