Modeling land use scenario changes and its potential impacts on the structure and function of the ecosystem in the typical regions are helpful to understanding the interactive mechanism between land use system and eco...Modeling land use scenario changes and its potential impacts on the structure and function of the ecosystem in the typical regions are helpful to understanding the interactive mechanism between land use system and ecological system. A Land Use Scenario Dynamics (LUSD) model by the integration of System Dynamics (SD) model and Cellular Automata (CA) model is developed with land use scenario changes in northern China in the next 20 years simulated in this paper. The basic idea of LUSD model is to simulate the land use scenario de-mands by using SD model at first, then allocate the land use scenario patterns at the local scale with the considerations of land use suitability, inheritance ability and neighborhood effect by using CA model to satisfy the balance between land use scenario demands and supply. The application of LUSD model in northern China suggests that the model has the ability to reflect the complex behavior of land use system at different scales to some extent and is a useful tool for assessing the potential impacts of land use system on ecological system. In addition, the simulated results also indicate that obvious land use changes will take place in the farming-pastoral zone of northern China in the next 20 years with cultivated land and urban land being the most active land use types.展开更多
By applying the rules set in traffic flow and pedestrian flow models, a basic cellular automata model is presented to simulate occupant evacuation in fire. Some extended models are introduced to study the special phen...By applying the rules set in traffic flow and pedestrian flow models, a basic cellular automata model is presented to simulate occupant evacuation in fire. Some extended models are introduced to study the special phenomena of evacuation from the fire room. The key of the models is the introduction of the danger grade which makes the route choice convenient and reasonable. Fire not only influences the emotional and behavioral characteristics of an individual but also affects his physical constitution, which reduces his maximal possible velocity. The models consider these influence factors by applying a set of simple but effective rules. It is needed to emphasize that all rules are established according to the essential phenomenon in fire evacuation, that is, all the occupants would try to move to the safest place as fast as possible. Some simulation examples are also presented to validate the applicability of the models.展开更多
Soil moisture content （SMC） is a key hydrological parameter in agriculture,meteorology and climate change,and understanding of spatio-temporal distributions of SMC in farmlands is important to address the precise ir...Soil moisture content （SMC） is a key hydrological parameter in agriculture,meteorology and climate change,and understanding of spatio-temporal distributions of SMC in farmlands is important to address the precise irrigation scheduling.However,the hybrid interaction of static and dynamic environmental parameters makes it particularly difficult to accurately and reliably model the distribution of SMC.At present,deep learning wins numerous contests in machine learning and hence deep belief network （DBN） ,a breakthrough in deep learning is trained to extract the transition functions for the simulation of the cell state changes.In this study,we used a novel macroscopic cellular automata （MCA） model by combining DBN to predict the SMC over an irrigated corn field （an area of 22 km^2） in the Zhangye oasis,Northwest China.Static and dynamic environmental variables were prepared with regard to the complex hydrological processes.The widely used neural network,multi-layer perceptron （MLP） ,was utilized for comparison to DBN.The hybrid models （MLP-MCA and DBN-MCA） were calibrated and validated on SMC data within four months,i.e.June to September 2012,which were automatically observed by a wireless sensor network （WSN） .Compared with MLP-MCA,the DBN-MCA model led to a decrease in root mean squared error （RMSE） by 18%.Thus,the differences of prediction errors increased due to the propagating errors of variables,difficulties of knowing soil properties and recording irrigation amount in practice.The sequential Gaussian simulation （s Gs） was performed to assess the uncertainty of soil moisture estimations.Calculated with a threshold of SMC for each grid cell,the local uncertainty of simulated results in the post processing suggested that the probability of SMC less than 25% will be difference in different areas at different time periods.The current results showed that the DBN-MCA model performs better than the MLP-MCA model,and the DBN-MCA model provides a powerful tool for predicting SMC in hi展开更多
There exist interactions among pedestrians and between pedestrian and environment in evacuation. These interactions include attraction, repulsion and friction that play key roles in human evacuation behaviors, speed a...There exist interactions among pedestrians and between pedestrian and environment in evacuation. These interactions include attraction, repulsion and friction that play key roles in human evacuation behaviors, speed and efficiency. Most former evacuation models focus on the attraction force, while repulsion and friction are not well modeled. As a kind of multi-particle self-driven model, the social force model introduced in recent years can represent those three forces but with low simulation efficiency because it is a continuous model with complex rules. Discrete models such as the cellular automata model and the lattice gas model have simple rules and high simulation efficiency, but are not quite suitable for interactions’ simulation. In this paper, a new cellular automata model based on traditional models is introduced in which repulsion and friction are modeled quantitatively. It is indicated that the model can simulate some basic behaviors, e.g. arching and the “faster-is-slower” phenomenon, in evacuation as multi-particle self-driven models, but with high efficiency as the normal cellular automata model and the lattice gas model.展开更多
Air route network optimization,one of the essential parts of the airspace planning,is an effective way to optimize airspace resources,increase airspace capacity,and alleviate air traffic congestion.However,little has ...Air route network optimization,one of the essential parts of the airspace planning,is an effective way to optimize airspace resources,increase airspace capacity,and alleviate air traffic congestion.However,little has been done on the optimization of air route network in the fragmented airspace caused by prohibited,restricted,and dangerous areas（PRDs）.In this paper,an air route network optimization model is developed with the total operational cost as the objective function while airspace restriction,air route network capacity,and non-straight-line factors（NSLF） are taken as major constraints.A square grid cellular space,Moore neighbors,a fixed boundary,together with a set of rules for solving the route network optimization model are designed based on cellular automata.The empirical traffic of airports with the largest traffic volume in each of the 9 flight information regions in China's Mainland is collected as the origin-destination（OD） airport pair demands.Based on traffic patterns,the model generates 35 air routes which successfully avoids 144 PRDs.Compared with the current air route network structure,the number of nodes decreases by 41.67%,while the total length of flight segments and air routes drop by 32.03% and 5.82% respectively.The NSLF decreases by 5.82% with changes in the total length of the air route network.More importantly,the total operational cost of the whole network decreases by 6.22%.The computational results show the potential benefits of the model and the advantage of the algorithm.Optimization of air route network can significantly reduce operational cost while ensuring operation safety.展开更多
This paper establishes a fundamental framework of automata theory based on complete residuated lattice-valued logic. First it deals with how to extend the transition relation of states and par-ticularly presents a cha...This paper establishes a fundamental framework of automata theory based on complete residuated lattice-valued logic. First it deals with how to extend the transition relation of states and par-ticularly presents a characterization of residuated lattice by fuzzy automata (called (?) valued automata). After that fuzzy subautomata (called (?) valued subautomata), successor and source operators are pro-posed and their basic properties as well as the equivalent relation among them are discussed, from which it follows that the two fuzzy operators are exactly fuzzy closure operators. Finally an L bifuzzy topological characterization of Q valued automata is presented, so a more generalized fuzzy automata theory is built.展开更多
Sustainable development has become a primary objective for many countries and regions throughout the world now. The ecological footprint (EF) is a kind of concise method of quantifiably measuring the natural capital c...Sustainable development has become a primary objective for many countries and regions throughout the world now. The ecological footprint (EF) is a kind of concise method of quantifiably measuring the natural capital consumption and it can reflect the goal of sustainability. In this paper, the concept, the theory and method of ecological footprint are introduced. On this basis, the study brings forward the method of ecological footprint and capacity prediction. The method is employed for the ecological footprint prediction combining consumption model with population model and the technique is adopted for the ecological capacity (EC) prediction uniting the Geographical Cellular Automata (Geo CA) and Geographic Information System (GIS). The above models and methods are employed to calculate EF and EC in 1995 and 2000 and predict them in 2005 in Hexi Corridor. The result shows that EF is continually increasing, and EC ascended in the anterior 5 years and will descend in the posterior 5 years. This suit of method is of the character of accuracy and speediness.展开更多
Self-organized criticality(SOC) of forest fires in China from 1950 to 1989 is studied. The stability, scale-invariant character of SOC and external effects on SOC of forest fires in China are analyzed in detail. Fores...Self-organized criticality(SOC) of forest fires in China from 1950 to 1989 is studied. The stability, scale-invariant character of SOC and external effects on SOC of forest fires in China are analyzed in detail. Forest-fire cellular automata model is a typical model for the research of SOC. Based on the traditional forest-fire model, an improved model, in which effects of tree species, meteorological conditions and human efforts on forest fires are considered, is introduced. Actual forest fire data in China are compared with simulation results of the two models. It is shown that forest fire data in China have SOC behavior and simulation results of the improved model accord better with actual forest fire data than those of the traditional model.展开更多
In this paper, we propose a matrix-based approach for finite automata and then study the reachability conditions. Both the deterministic and nondeterministic automata are expressed in matrix forms, and the necessary a...In this paper, we propose a matrix-based approach for finite automata and then study the reachability conditions. Both the deterministic and nondeterministic automata are expressed in matrix forms, and the necessary and sufficient conditions on reachability are given using semitensor product of matrices. Our results show that the matrix expression provides an effective computational way for the reachability analysis of finite automata.展开更多
Urban growth analysis and simulation have been recently conducted by cellular automata （CA） models based on self-organizing theory which differs from system dynamics models. This paper describes the Beijing urban de...Urban growth analysis and simulation have been recently conducted by cellular automata （CA） models based on self-organizing theory which differs from system dynamics models. This paper describes the Beijing urban development model （BUDEM） which adopts the CA approach to support urban planning and policy evaluation. BUDEM, as a spatio-temporal dynamic model for simulating urban growth in the Beijing metropolitan area, is based on the urban growth theory and integrates logistic regression and MonoLoop to obtain the weights for the transition rule with multi-criteria evaluation configuration. Local sensitivity analysis for all the parameters of BUDEM is also carried out to assess the model＇s performances. The model is used to identify urban growth mechanisms in the various historical phases since 1986, to retrieve urban growth policies needed to implement the desired （planned） urban form in 2020, and to simulate urban growth scenarios until 2049 based on the urban form and parameter set in 2020. The model has been proved to be capable of analyzing historical urban growth mechanisms and predicting future urban growth for metropolitan areas in China.展开更多
Aiming at the limitations of the traditional mathematical model for production planning, a novel optimization model is proposed to improve the efficiency and performance for production planning in steelmaking and cont...Aiming at the limitations of the traditional mathematical model for production planning, a novel optimization model is proposed to improve the efficiency and performance for production planning in steelmaking and continuous casting （SCC） process. The optimization model combined with parallel-backward inferring algorithm and genetic algorithm is described. To analyze and evaluate the production plans, a simulation model based on cellular automata is presented. And then, the integrated system including the production plan optimization model and the simulation model is introduced to evaluate and adjust the production plan on-line. The test with production data in a steel plant shows that the optimization model demonstrates ability to deal with time uncertainty in production planning and to set up a conflict-free production plan, and the integrated system provides a useful tool for dynamically drawing and adjusting a production plan on-line. The average staying time of the production plan is about 5% shorter than that in a practical process.展开更多
This paper discusses the issues about the correlation of spatial variables during spatial decisionmaking using multicriteria evaluation (MCE) and cellular automata (CA). The correlation of spatial variables can cause ...This paper discusses the issues about the correlation of spatial variables during spatial decisionmaking using multicriteria evaluation (MCE) and cellular automata (CA). The correlation of spatial variables can cause the malfunction of MCE. In urban simulation, spatial factors often exhibit a high degree of correlation which is considered as an undesirable property for MCE. This study uses principal components analysis (PCA) to remove data redundancy among a large set of spatial variables and determine 'ideal points' for land development. PCA is integrated with cellular automata and geographical information systems (GIS) for the simulation of idealized urban forms for planning purposes.展开更多
In this papert weights of output set and of input set for finiteautomata are discussed. For a weakly invertible finite automaton, we proye thatfor states with minimal output weight, the distribution of input sets is u...In this papert weights of output set and of input set for finiteautomata are discussed. For a weakly invertible finite automaton, we proye thatfor states with minimal output weight, the distribution of input sets is uniform.Then for a kind of compound finite automata, we give weights of output set and ofinput set explicitly, and a characterization of their input-trees. For finite automatonpublic key cryptosystems, of which automata in public keys belong to such a kind ofcompound finite automata, we evaluate search amounts of exhaust search algorithmsin average case and in worse case for both encryption and signature, and successfulprobabilities of stochastic search algorithms for both encryption and signature. Inaddition, a result on mutual invertibility of finite automata is also given.展开更多
Although traditional urban expansion simulation models can simulate dynamic features, these models fail to address complex changes produced by different agents＇ behaviors. The paper has built up a set of spatial-temp...Although traditional urban expansion simulation models can simulate dynamic features, these models fail to address complex changes produced by different agents＇ behaviors. The paper has built up a set of spatial-temporal land resource allocation rules and developed a dynamic urban expansion model based on a multi-agent system, which can simulate the interaction among different agents, such as residents, peasants, and governments. This model is applied to simulate urban expansion process taking Changsha City, in China as a study area. The results show that this model can not only reflect basic characteristics of urban expansion, but also help explain the reasons for urban expansion process and understand the effect of agents＇ behavior on the expansion process, and provide insights into the causing factors behind the expansion. In addition, in contrast to simulation results with land use classification map from remote sensing images, the precision of the simulation reached over 68% with higher precision than cellular automata model according to the cell-by-cell comparison. The results suggest that the model can help to provide land use decision making support to government and urban planners.展开更多
基金This work was supported by the State Basic Research Program of China(Grant Nos.G200018604 and G1999043406-03)the Youth Teacher Foundation of Beijing Normal University of China(Grant No.10770001).
文摘Modeling land use scenario changes and its potential impacts on the structure and function of the ecosystem in the typical regions are helpful to understanding the interactive mechanism between land use system and ecological system. A Land Use Scenario Dynamics (LUSD) model by the integration of System Dynamics (SD) model and Cellular Automata (CA) model is developed with land use scenario changes in northern China in the next 20 years simulated in this paper. The basic idea of LUSD model is to simulate the land use scenario de-mands by using SD model at first, then allocate the land use scenario patterns at the local scale with the considerations of land use suitability, inheritance ability and neighborhood effect by using CA model to satisfy the balance between land use scenario demands and supply. The application of LUSD model in northern China suggests that the model has the ability to reflect the complex behavior of land use system at different scales to some extent and is a useful tool for assessing the potential impacts of land use system on ecological system. In addition, the simulated results also indicate that obvious land use changes will take place in the farming-pastoral zone of northern China in the next 20 years with cultivated land and urban land being the most active land use types.
基金This work was supported by the National Natural Science Foundation of China (Grant No. 50006012)the Chinese NKBRSF project (Grant No. 2001CB409600)the project of high-level university establishment.
文摘By applying the rules set in traffic flow and pedestrian flow models, a basic cellular automata model is presented to simulate occupant evacuation in fire. Some extended models are introduced to study the special phenomena of evacuation from the fire room. The key of the models is the introduction of the danger grade which makes the route choice convenient and reasonable. Fire not only influences the emotional and behavioral characteristics of an individual but also affects his physical constitution, which reduces his maximal possible velocity. The models consider these influence factors by applying a set of simple but effective rules. It is needed to emphasize that all rules are established according to the essential phenomenon in fire evacuation, that is, all the occupants would try to move to the safest place as fast as possible. Some simulation examples are also presented to validate the applicability of the models.
基金supported by the National Natural Science Foundation of China (41130530,91325301,41401237,41571212,41371224)the Jiangsu Province Science Foundation for Youths (BK20141053)the Field Frontier Program of the Institute of Soil Science,Chinese Academy of Sciences (ISSASIP1624)
文摘Soil moisture content （SMC） is a key hydrological parameter in agriculture,meteorology and climate change,and understanding of spatio-temporal distributions of SMC in farmlands is important to address the precise irrigation scheduling.However,the hybrid interaction of static and dynamic environmental parameters makes it particularly difficult to accurately and reliably model the distribution of SMC.At present,deep learning wins numerous contests in machine learning and hence deep belief network （DBN） ,a breakthrough in deep learning is trained to extract the transition functions for the simulation of the cell state changes.In this study,we used a novel macroscopic cellular automata （MCA） model by combining DBN to predict the SMC over an irrigated corn field （an area of 22 km^2） in the Zhangye oasis,Northwest China.Static and dynamic environmental variables were prepared with regard to the complex hydrological processes.The widely used neural network,multi-layer perceptron （MLP） ,was utilized for comparison to DBN.The hybrid models （MLP-MCA and DBN-MCA） were calibrated and validated on SMC data within four months,i.e.June to September 2012,which were automatically observed by a wireless sensor network （WSN） .Compared with MLP-MCA,the DBN-MCA model led to a decrease in root mean squared error （RMSE） by 18%.Thus,the differences of prediction errors increased due to the propagating errors of variables,difficulties of knowing soil properties and recording irrigation amount in practice.The sequential Gaussian simulation （s Gs） was performed to assess the uncertainty of soil moisture estimations.Calculated with a threshold of SMC for each grid cell,the local uncertainty of simulated results in the post processing suggested that the probability of SMC less than 25% will be difference in different areas at different time periods.The current results showed that the DBN-MCA model performs better than the MLP-MCA model,and the DBN-MCA model provides a powerful tool for predicting SMC in hi
文摘There exist interactions among pedestrians and between pedestrian and environment in evacuation. These interactions include attraction, repulsion and friction that play key roles in human evacuation behaviors, speed and efficiency. Most former evacuation models focus on the attraction force, while repulsion and friction are not well modeled. As a kind of multi-particle self-driven model, the social force model introduced in recent years can represent those three forces but with low simulation efficiency because it is a continuous model with complex rules. Discrete models such as the cellular automata model and the lattice gas model have simple rules and high simulation efficiency, but are not quite suitable for interactions’ simulation. In this paper, a new cellular automata model based on traditional models is introduced in which repulsion and friction are modeled quantitatively. It is indicated that the model can simulate some basic behaviors, e.g. arching and the “faster-is-slower” phenomenon, in evacuation as multi-particle self-driven models, but with high efficiency as the normal cellular automata model and the lattice gas model.
基金co-supported by the National Natural Science Foundation of China(No.61304190)the Natural Science Foundation of Jiangsu Province(No.BK20130818)the Fundamental Research Funds for the Central Universities of China(No.NJ20150030)
文摘Air route network optimization,one of the essential parts of the airspace planning,is an effective way to optimize airspace resources,increase airspace capacity,and alleviate air traffic congestion.However,little has been done on the optimization of air route network in the fragmented airspace caused by prohibited,restricted,and dangerous areas（PRDs）.In this paper,an air route network optimization model is developed with the total operational cost as the objective function while airspace restriction,air route network capacity,and non-straight-line factors（NSLF） are taken as major constraints.A square grid cellular space,Moore neighbors,a fixed boundary,together with a set of rules for solving the route network optimization model are designed based on cellular automata.The empirical traffic of airports with the largest traffic volume in each of the 9 flight information regions in China's Mainland is collected as the origin-destination（OD） airport pair demands.Based on traffic patterns,the model generates 35 air routes which successfully avoids 144 PRDs.Compared with the current air route network structure,the number of nodes decreases by 41.67%,while the total length of flight segments and air routes drop by 32.03% and 5.82% respectively.The NSLF decreases by 5.82% with changes in the total length of the air route network.More importantly,the total operational cost of the whole network decreases by 6.22%.The computational results show the potential benefits of the model and the advantage of the algorithm.Optimization of air route network can significantly reduce operational cost while ensuring operation safety.
基金This work was supported by the National Foundation for Distinguished Young Scholars (Grant No. 69725004) the National Key Project for Basic Research (Grant No.1998030509) the National Natural Science Foundation of China (Grant No. 69823001).
文摘This paper establishes a fundamental framework of automata theory based on complete residuated lattice-valued logic. First it deals with how to extend the transition relation of states and par-ticularly presents a characterization of residuated lattice by fuzzy automata (called (?) valued automata). After that fuzzy subautomata (called (?) valued subautomata), successor and source operators are pro-posed and their basic properties as well as the equivalent relation among them are discussed, from which it follows that the two fuzzy operators are exactly fuzzy closure operators. Finally an L bifuzzy topological characterization of Q valued automata is presented, so a more generalized fuzzy automata theory is built.
基金Knowledge Innovation Project of CAS No.KZCX-10-09+1 种基金 Project of Office of the Leading Group for Western Region Development of the State Council No.[2002]11
文摘Sustainable development has become a primary objective for many countries and regions throughout the world now. The ecological footprint (EF) is a kind of concise method of quantifiably measuring the natural capital consumption and it can reflect the goal of sustainability. In this paper, the concept, the theory and method of ecological footprint are introduced. On this basis, the study brings forward the method of ecological footprint and capacity prediction. The method is employed for the ecological footprint prediction combining consumption model with population model and the technique is adopted for the ecological capacity (EC) prediction uniting the Geographical Cellular Automata (Geo CA) and Geographic Information System (GIS). The above models and methods are employed to calculate EF and EC in 1995 and 2000 and predict them in 2005 in Hexi Corridor. The result shows that EF is continually increasing, and EC ascended in the anterior 5 years and will descend in the posterior 5 years. This suit of method is of the character of accuracy and speediness.
基金This work was supported by theSpecial Fund for the Major National Basic Research Projects in China the National Basic Research Climbing Project and the National Natural Science Foundation of China (Grant Nos. 59936140 and 19932020).
文摘Self-organized criticality(SOC) of forest fires in China from 1950 to 1989 is studied. The stability, scale-invariant character of SOC and external effects on SOC of forest fires in China are analyzed in detail. Forest-fire cellular automata model is a typical model for the research of SOC. Based on the traditional forest-fire model, an improved model, in which effects of tree species, meteorological conditions and human efforts on forest fires are considered, is introduced. Actual forest fire data in China are compared with simulation results of the two models. It is shown that forest fire data in China have SOC behavior and simulation results of the improved model accord better with actual forest fire data than those of the traditional model.
基金supported by the National Natural Science Foundation of China (No. 61174071)
文摘In this paper, we propose a matrix-based approach for finite automata and then study the reachability conditions. Both the deterministic and nondeterministic automata are expressed in matrix forms, and the necessary and sufficient conditions on reachability are given using semitensor product of matrices. Our results show that the matrix expression provides an effective computational way for the reachability analysis of finite automata.
基金Supported by the National Natural Science Foundation of China (No.50678088)the National Project of Scientific and Technical Supporting Programs Funded by the Ministry of Science & Technology of China (No.2006BAJ14B08)
文摘Urban growth analysis and simulation have been recently conducted by cellular automata （CA） models based on self-organizing theory which differs from system dynamics models. This paper describes the Beijing urban development model （BUDEM） which adopts the CA approach to support urban planning and policy evaluation. BUDEM, as a spatio-temporal dynamic model for simulating urban growth in the Beijing metropolitan area, is based on the urban growth theory and integrates logistic regression and MonoLoop to obtain the weights for the transition rule with multi-criteria evaluation configuration. Local sensitivity analysis for all the parameters of BUDEM is also carried out to assess the model＇s performances. The model is used to identify urban growth mechanisms in the various historical phases since 1986, to retrieve urban growth policies needed to implement the desired （planned） urban form in 2020, and to simulate urban growth scenarios until 2049 based on the urban form and parameter set in 2020. The model has been proved to be capable of analyzing historical urban growth mechanisms and predicting future urban growth for metropolitan areas in China.
基金Item Sponsored by National High-Tech Research and Development Plan of China(2007AA04Z161)
文摘Aiming at the limitations of the traditional mathematical model for production planning, a novel optimization model is proposed to improve the efficiency and performance for production planning in steelmaking and continuous casting （SCC） process. The optimization model combined with parallel-backward inferring algorithm and genetic algorithm is described. To analyze and evaluate the production plans, a simulation model based on cellular automata is presented. And then, the integrated system including the production plan optimization model and the simulation model is introduced to evaluate and adjust the production plan on-line. The test with production data in a steel plant shows that the optimization model demonstrates ability to deal with time uncertainty in production planning and to set up a conflict-free production plan, and the integrated system provides a useful tool for dynamically drawing and adjusting a production plan on-line. The average staying time of the production plan is about 5% shorter than that in a practical process.
基金This project was supported by the National Natural Science Foundation of China (Grant No. 40071060) the Croucher Foundation of Hong Kong (Grant No. 21009619).
文摘This paper discusses the issues about the correlation of spatial variables during spatial decisionmaking using multicriteria evaluation (MCE) and cellular automata (CA). The correlation of spatial variables can cause the malfunction of MCE. In urban simulation, spatial factors often exhibit a high degree of correlation which is considered as an undesirable property for MCE. This study uses principal components analysis (PCA) to remove data redundancy among a large set of spatial variables and determine 'ideal points' for land development. PCA is integrated with cellular automata and geographical information systems (GIS) for the simulation of idealized urban forms for planning purposes.
文摘In this papert weights of output set and of input set for finiteautomata are discussed. For a weakly invertible finite automaton, we proye thatfor states with minimal output weight, the distribution of input sets is uniform.Then for a kind of compound finite automata, we give weights of output set and ofinput set explicitly, and a characterization of their input-trees. For finite automatonpublic key cryptosystems, of which automata in public keys belong to such a kind ofcompound finite automata, we evaluate search amounts of exhaust search algorithmsin average case and in worse case for both encryption and signature, and successfulprobabilities of stochastic search algorithms for both encryption and signature. Inaddition, a result on mutual invertibility of finite automata is also given.
基金National Natural Science Foundation of China, No.40771198Hunan Provincial Natural Science Foundation of China, No.08JJ6023
文摘Although traditional urban expansion simulation models can simulate dynamic features, these models fail to address complex changes produced by different agents＇ behaviors. The paper has built up a set of spatial-temporal land resource allocation rules and developed a dynamic urban expansion model based on a multi-agent system, which can simulate the interaction among different agents, such as residents, peasants, and governments. This model is applied to simulate urban expansion process taking Changsha City, in China as a study area. The results show that this model can not only reflect basic characteristics of urban expansion, but also help explain the reasons for urban expansion process and understand the effect of agents＇ behavior on the expansion process, and provide insights into the causing factors behind the expansion. In addition, in contrast to simulation results with land use classification map from remote sensing images, the precision of the simulation reached over 68% with higher precision than cellular automata model according to the cell-by-cell comparison. The results suggest that the model can help to provide land use decision making support to government and urban planners.
