Hydrologic time series forecasting is very an important area in water resource. Based on the multi-time scale and the nonlinear characteristics of the rainfall-runoff time series, a new hybrid neural network (NN) has been suggested by Genetic Algorithm (GA) selection the lag period of time series for NN input variables, optimization neural network architecture and connection weights. The evolved neural network architecture and connection weights are then input into a new neural network. The new neural network is trained using back -- propagation (BP) algorithm for hydrologic time series forecasting. The ensemble strategy is implemented using the quadratic programming. The present model absorbs some merits of GA and artificial neural network. Case studies, the short and long term prediction of hydrological time series, have been researched. The comparison results revealed that the suggested model could increase the forecasted accuracy and prolong the length time of prediction.
{"title":"Hybrid Neural Network Models for Hydrologic Time Series Forecasting Based on Genetic Algorithm","authors":"Ganji Huang, Lingzhi Wang","doi":"10.1109/CSO.2011.147","DOIUrl":"https://doi.org/10.1109/CSO.2011.147","url":null,"abstract":"Hydrologic time series forecasting is very an important area in water resource. Based on the multi-time scale and the nonlinear characteristics of the rainfall-runoff time series, a new hybrid neural network (NN) has been suggested by Genetic Algorithm (GA) selection the lag period of time series for NN input variables, optimization neural network architecture and connection weights. The evolved neural network architecture and connection weights are then input into a new neural network. The new neural network is trained using back -- propagation (BP) algorithm for hydrologic time series forecasting. The ensemble strategy is implemented using the quadratic programming. The present model absorbs some merits of GA and artificial neural network. Case studies, the short and long term prediction of hydrological time series, have been researched. The comparison results revealed that the suggested model could increase the forecasted accuracy and prolong the length time of prediction.","PeriodicalId":210815,"journal":{"name":"2011 Fourth International Joint Conference on Computational Sciences and Optimization","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129955733","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the UN Climate Change Conference Copenhagen closed, to develop low carbon economy is upgraded to be a matter of politics, setting new rules for world development pattern. Seizing this opportunity, Chinese government is striving to find a new way to promote low carbon development, hereafter to innovate when facing social governance obstacles, in order to achieve sound management. This paper explores both the opportunities and challenges Chinese local governments will meet in governance innovation in low carbon context.
{"title":"Governance Transformation of Chinese Local Government in the Context of Low Carbon Economy: Opportunities and Challenges","authors":"Wensheng He, Luwen Sun, Lingling Liao","doi":"10.1109/CSO.2011.142","DOIUrl":"https://doi.org/10.1109/CSO.2011.142","url":null,"abstract":"With the UN Climate Change Conference Copenhagen closed, to develop low carbon economy is upgraded to be a matter of politics, setting new rules for world development pattern. Seizing this opportunity, Chinese government is striving to find a new way to promote low carbon development, hereafter to innovate when facing social governance obstacles, in order to achieve sound management. This paper explores both the opportunities and challenges Chinese local governments will meet in governance innovation in low carbon context.","PeriodicalId":210815,"journal":{"name":"2011 Fourth International Joint Conference on Computational Sciences and Optimization","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129124818","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A cellular automata model is proposed to simulate the pedestrian evacuation behavior in a room with multiple exits by considering the surrounding pedestrian density related to current cell based on the direction. The numerical results show that the pedestrian density and the radius of visual area are two important factors in an evacuation which can affect the evacuation times apparently. It is found that blindly constant choosing the direction with smaller pedestrian density may lead to an increase of evacuation time.
{"title":"Simulation of Exit Choosing in Pedestrian Evacuation Using a Cellular Automaton Model Based on Surrounding Pedestrian Density","authors":"Yan Xu, Haijun Huang, Li-jun Tian","doi":"10.1109/CSO.2011.242","DOIUrl":"https://doi.org/10.1109/CSO.2011.242","url":null,"abstract":"A cellular automata model is proposed to simulate the pedestrian evacuation behavior in a room with multiple exits by considering the surrounding pedestrian density related to current cell based on the direction. The numerical results show that the pedestrian density and the radius of visual area are two important factors in an evacuation which can affect the evacuation times apparently. It is found that blindly constant choosing the direction with smaller pedestrian density may lead to an increase of evacuation time.","PeriodicalId":210815,"journal":{"name":"2011 Fourth International Joint Conference on Computational Sciences and Optimization","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132434687","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ying-Jian Qi, Qing Li, Zheng-peng Wu, Bin Zhang, Ying Li
The edges of an image are important information. Edge detection is the base of feature extraction, image analysis and comprehension. The quality of edge detection determines the performance of subsequent processing. The edge of an image stands for the discontinued information. We propos a new algorithm of image edge detection based on grey system theory in this paper. we calculate the relative degree of grey incidences between pixel with its neighbor and the ideal reference vector and then decide the edge property of the pixel. Some discussion and experiments are performed. The result shows that this new algorithm is applicable and we can adjust the edge information through the setting of the threshold.
{"title":"An Algorithm of Image Edge Detection Based on Grey System Theory","authors":"Ying-Jian Qi, Qing Li, Zheng-peng Wu, Bin Zhang, Ying Li","doi":"10.1109/CSO.2011.66","DOIUrl":"https://doi.org/10.1109/CSO.2011.66","url":null,"abstract":"The edges of an image are important information. Edge detection is the base of feature extraction, image analysis and comprehension. The quality of edge detection determines the performance of subsequent processing. The edge of an image stands for the discontinued information. We propos a new algorithm of image edge detection based on grey system theory in this paper. we calculate the relative degree of grey incidences between pixel with its neighbor and the ideal reference vector and then decide the edge property of the pixel. Some discussion and experiments are performed. The result shows that this new algorithm is applicable and we can adjust the edge information through the setting of the threshold.","PeriodicalId":210815,"journal":{"name":"2011 Fourth International Joint Conference on Computational Sciences and Optimization","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131650900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mobile agents are autonomous software entities that are able to migrate across different execution environments. The characteristics of mobile agents make them ideal for electronic commerce applications in open networks. Security is a fundamental precondition for the acceptance of mobile agent systems. In this paper, using discrete logarithm, an efficient key management proposal for mobile agent based on hierarchical structure is presented and its security is analyzed. It can achieve the property that related parameters do not have to update even if set secret keys are altered. So, the presented scheme may be more suitable for applications.
{"title":"Efficient Key Management Scheme for Mobile Agent in a Hierarchy","authors":"Yi Liu, Yong Ding","doi":"10.1109/CSO.2011.122","DOIUrl":"https://doi.org/10.1109/CSO.2011.122","url":null,"abstract":"Mobile agents are autonomous software entities that are able to migrate across different execution environments. The characteristics of mobile agents make them ideal for electronic commerce applications in open networks. Security is a fundamental precondition for the acceptance of mobile agent systems. In this paper, using discrete logarithm, an efficient key management proposal for mobile agent based on hierarchical structure is presented and its security is analyzed. It can achieve the property that related parameters do not have to update even if set secret keys are altered. So, the presented scheme may be more suitable for applications.","PeriodicalId":210815,"journal":{"name":"2011 Fourth International Joint Conference on Computational Sciences and Optimization","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125413476","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper studies the stability issues of the traveler's day-to-day route adjustment process in the general transportation network with fixed or elastic demand, homogeneous or heterogeneous users. Each traveler is assumed to adjust his/her route choice according to the excess travel cost between the instantaneous experienced travel cost and a certain referred level, which induces an aggregate path flow dynamics. We call the path flow dynamics the excess travel cost dynamics, which corresponds to the excess payoff dynamics in evolutionary games and serves a general framework of modeling the homogeneous or heterogeneous route choice behavior of travelers.
{"title":"Stability Issue of the Day-to-Day Link Flow Pattern with Heterogeneous Users","authors":"Zhijia Tan, Hai Yang","doi":"10.1109/CSO.2011.244","DOIUrl":"https://doi.org/10.1109/CSO.2011.244","url":null,"abstract":"This paper studies the stability issues of the traveler's day-to-day route adjustment process in the general transportation network with fixed or elastic demand, homogeneous or heterogeneous users. Each traveler is assumed to adjust his/her route choice according to the excess travel cost between the instantaneous experienced travel cost and a certain referred level, which induces an aggregate path flow dynamics. We call the path flow dynamics the excess travel cost dynamics, which corresponds to the excess payoff dynamics in evolutionary games and serves a general framework of modeling the homogeneous or heterogeneous route choice behavior of travelers.","PeriodicalId":210815,"journal":{"name":"2011 Fourth International Joint Conference on Computational Sciences and Optimization","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125443210","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We provide new and discrete time binomial approaches for pricing look back options, and develop a numerical method for look back options with dividends. By using generating functions, a very useful tool in lattice path enumeration, the computation of the approach for pricing look back options is significantly simplified on the binomial tree. Numerical experiment shows that the approach is fast, accurate and easy to implement.
{"title":"Pricing Lookback Options with Dividends","authors":"Jingfeng Xu, Haijian Zhao, Zheyuan Zhong","doi":"10.1109/CSO.2011.208","DOIUrl":"https://doi.org/10.1109/CSO.2011.208","url":null,"abstract":"We provide new and discrete time binomial approaches for pricing look back options, and develop a numerical method for look back options with dividends. By using generating functions, a very useful tool in lattice path enumeration, the computation of the approach for pricing look back options is significantly simplified on the binomial tree. Numerical experiment shows that the approach is fast, accurate and easy to implement.","PeriodicalId":210815,"journal":{"name":"2011 Fourth International Joint Conference on Computational Sciences and Optimization","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125531050","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The water depth inversion of shallow reefs plays an important role for marine safety, marine engineering and marine military. The IKONOS satellite remote sensing image and the chart water depth data are analyzed and processed in this paper and a new neural network model is established by transmission bands ratio. The ratio of blue, green, red and near-infrared bands of IKONOS is used to calculate the water depth. Using neural network model, the water depth are inversed directly by the remote sensing image data without regard to other environmental factors (e.g. sea sediments, marine organisms, etc.). The non-linear relationship between the multi-spectral IKONOS data and the measured depth data can be established within the proposed model and higher inversion precision can be obtained compared with traditional regression model.
{"title":"An Inversion Method of Remote Sensing Water Depth Based on Transmission Bands Ratio","authors":"Zhenxing Zhang, H. Teng","doi":"10.1109/CSO.2011.80","DOIUrl":"https://doi.org/10.1109/CSO.2011.80","url":null,"abstract":"The water depth inversion of shallow reefs plays an important role for marine safety, marine engineering and marine military. The IKONOS satellite remote sensing image and the chart water depth data are analyzed and processed in this paper and a new neural network model is established by transmission bands ratio. The ratio of blue, green, red and near-infrared bands of IKONOS is used to calculate the water depth. Using neural network model, the water depth are inversed directly by the remote sensing image data without regard to other environmental factors (e.g. sea sediments, marine organisms, etc.). The non-linear relationship between the multi-spectral IKONOS data and the measured depth data can be established within the proposed model and higher inversion precision can be obtained compared with traditional regression model.","PeriodicalId":210815,"journal":{"name":"2011 Fourth International Joint Conference on Computational Sciences and Optimization","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126714742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Many real-world networks appear with community structure, and evolve with both growing and rewiring dynamics. Although some empirical investigations show the universal power law distribution in each community of such real-world networks, the study on the degree distribution in each community with both growing and rewiring dynamics lacks. In this paper, we construct a multi-community bipartite network model with both growing and rewiring dynamics. The growing rate and rewiring rate in each community evolve with time due to the interacting of communities. We find that the steady degree distribution in each community of the multi-community bipartite network model is equivalent to that in a bipartite network model without community structure.
{"title":"The Degree Distribution of a Multi-community Bipartite Network with Both Growing and Rewiring Dynamics","authors":"H. Fan","doi":"10.1109/CSO.2011.260","DOIUrl":"https://doi.org/10.1109/CSO.2011.260","url":null,"abstract":"Many real-world networks appear with community structure, and evolve with both growing and rewiring dynamics. Although some empirical investigations show the universal power law distribution in each community of such real-world networks, the study on the degree distribution in each community with both growing and rewiring dynamics lacks. In this paper, we construct a multi-community bipartite network model with both growing and rewiring dynamics. The growing rate and rewiring rate in each community evolve with time due to the interacting of communities. We find that the steady degree distribution in each community of the multi-community bipartite network model is equivalent to that in a bipartite network model without community structure.","PeriodicalId":210815,"journal":{"name":"2011 Fourth International Joint Conference on Computational Sciences and Optimization","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126836875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Due to the distinct seasonal characteristics of hydropower, this study tries to propose a seasonal decomposition (SD) based least squares support vector regression (LSSVR) ensemble learning model for hydropower consumption forecasting. In the SD-LSSVR-based decomposition and ensemble model, the original hydropower consumption series are first decomposed into trend cycle, seasonal factor and irregular component. Then the LSSVR is used to predict the three different components independently. Finally, these prediction results of the three components are combined with another LSSVR to formulate an ensemble result as the final prediction. Experimental results reveal that the proposed novel method is very promising for time series forecasting with seasonality and nonlinearity for that it outperforms all the other benchmark methods listed in our study in both level accuracy and directional accuracy.
{"title":"SD-LSSVR-Based Decomposition-and-Ensemble Methodology with Application to Hydropower Consumption Forecasting","authors":"Shuai Wang, L. Tang, Lean Yu","doi":"10.1109/CSO.2011.303","DOIUrl":"https://doi.org/10.1109/CSO.2011.303","url":null,"abstract":"Due to the distinct seasonal characteristics of hydropower, this study tries to propose a seasonal decomposition (SD) based least squares support vector regression (LSSVR) ensemble learning model for hydropower consumption forecasting. In the SD-LSSVR-based decomposition and ensemble model, the original hydropower consumption series are first decomposed into trend cycle, seasonal factor and irregular component. Then the LSSVR is used to predict the three different components independently. Finally, these prediction results of the three components are combined with another LSSVR to formulate an ensemble result as the final prediction. Experimental results reveal that the proposed novel method is very promising for time series forecasting with seasonality and nonlinearity for that it outperforms all the other benchmark methods listed in our study in both level accuracy and directional accuracy.","PeriodicalId":210815,"journal":{"name":"2011 Fourth International Joint Conference on Computational Sciences and Optimization","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123328433","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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