Research paradigm plays an important role in the study of decision support system (DSS). Currently most researches in DSS heavily rely on positivist paradigm while other paradigms are ignored. Firstly this paper compares the paradigms for the inquiry in DSS. Then we propose a design framework of cognitive DSS based on dialectic pluralist paradigm. Some major components of the system and the design of key recommendation algorithm are introduced.
{"title":"The Paradigms for the Inquiry in Decision Support System (DSS) and a Design Framework of Cognitive DSS","authors":"Yinghong Zhong, Yingchun Zhong","doi":"10.1109/CINC.2009.203","DOIUrl":"https://doi.org/10.1109/CINC.2009.203","url":null,"abstract":"Research paradigm plays an important role in the study of decision support system (DSS). Currently most researches in DSS heavily rely on positivist paradigm while other paradigms are ignored. Firstly this paper compares the paradigms for the inquiry in DSS. Then we propose a design framework of cognitive DSS based on dialectic pluralist paradigm. Some major components of the system and the design of key recommendation algorithm are introduced.","PeriodicalId":173506,"journal":{"name":"2009 International Conference on Computational Intelligence and Natural Computing","volume":"181 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122421622","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}
Aghion and Howitt have respectively discussed the models of introducing the restraints of environment pollution and nonrenewable resources under the framework of Vertical Product Innovation. In this article, the authors try to introduce both the restraints of environment pollution and nonrenewable resources into Vertical Product Innovation model simultaneously. The basic conclusions of the model in this article are as follows. Firstly, technical innovation serves as the sources of economic growth and sustainable development; secondly, comparing with the restraints of nonrenewable resources, environment pollution affects economic growth and sustainable development to a greater extent; Lastly, the model proposed in this paper is of wide use, which can contain the basic ideas and conclusions of environmental problems models under the framework of Horizontal Product Innovation and Human Capital.
{"title":"A Kind of Endogenous Growth Model Considering the Restraints of Nonrenewable Resources and Environment Pollution","authors":"Jun He, Ting Liu, Hua-ping Chen, Xiao Ding","doi":"10.1109/CINC.2009.210","DOIUrl":"https://doi.org/10.1109/CINC.2009.210","url":null,"abstract":"Aghion and Howitt have respectively discussed the models of introducing the restraints of environment pollution and nonrenewable resources under the framework of Vertical Product Innovation. In this article, the authors try to introduce both the restraints of environment pollution and nonrenewable resources into Vertical Product Innovation model simultaneously. The basic conclusions of the model in this article are as follows. Firstly, technical innovation serves as the sources of economic growth and sustainable development; secondly, comparing with the restraints of nonrenewable resources, environment pollution affects economic growth and sustainable development to a greater extent; Lastly, the model proposed in this paper is of wide use, which can contain the basic ideas and conclusions of environmental problems models under the framework of Horizontal Product Innovation and Human Capital.","PeriodicalId":173506,"journal":{"name":"2009 International Conference on Computational Intelligence and Natural Computing","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129545104","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}
To develop a fast solution for indexing high-dimensional image contents, which is crucial to building large-scale CBIR systems, is one key challenge in content-based image retrieval (CBIR). In this paper, we propose a scalable content-based image retrieval scheme using locality-sensitive hashing (LSH), and conduct extensive evaluations on a large image test-bed of a half million images. To the best of our knowledge, there is less comprehensive study on large-scale CBIR evaluation with a half million images. Our empirical results show that our proposed solution is able to scale for hundreds of thousands of images, which is promising for building web-scale CBIR systems.
{"title":"A Scalable Content-based Image Retrieval Scheme Using Locality-sensitive Hashing","authors":"Wang Weihong, Wang Song","doi":"10.1109/CINC.2009.124","DOIUrl":"https://doi.org/10.1109/CINC.2009.124","url":null,"abstract":"To develop a fast solution for indexing high-dimensional image contents, which is crucial to building large-scale CBIR systems, is one key challenge in content-based image retrieval (CBIR). In this paper, we propose a scalable content-based image retrieval scheme using locality-sensitive hashing (LSH), and conduct extensive evaluations on a large image test-bed of a half million images. To the best of our knowledge, there is less comprehensive study on large-scale CBIR evaluation with a half million images. Our empirical results show that our proposed solution is able to scale for hundreds of thousands of images, which is promising for building web-scale CBIR systems.","PeriodicalId":173506,"journal":{"name":"2009 International Conference on Computational Intelligence and Natural Computing","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128264781","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}
Reliable cost estimation is crucial to the planning process of a wastewater treatment plant (WWTP). Among the developed methods in literatures, not only the assumption of linearity but the existence of a great deal of uncertainty limits the actual application. In this paper, cost estimation of WWTPs in Taiwan region using BP neural network (NN) was investigated. The correlations between cost related variables and total construction cost and plant construction cost were obtained based on 26 collected data sets of design flow rate, influent BOD5 concentration and cost data etc. The study revealed that the proposed NN outperformed linear regression in respect to performance measures such as mean absolute error rate and coefficient of determination. Results from weight interpretation reflected the relative importance of input variables to costs. The NN-based approach can provide an economical and rapid means of cost estimation of WWTP.
{"title":"Application of BP Neural Network Approach for Cost Estimation of Wastewater Treatment Plants: A Case Study of Taiwan Region","authors":"R. Jiang, Hua-yue Zhu, Yuhua Chang","doi":"10.1109/CINC.2009.239","DOIUrl":"https://doi.org/10.1109/CINC.2009.239","url":null,"abstract":"Reliable cost estimation is crucial to the planning process of a wastewater treatment plant (WWTP). Among the developed methods in literatures, not only the assumption of linearity but the existence of a great deal of uncertainty limits the actual application. In this paper, cost estimation of WWTPs in Taiwan region using BP neural network (NN) was investigated. The correlations between cost related variables and total construction cost and plant construction cost were obtained based on 26 collected data sets of design flow rate, influent BOD5 concentration and cost data etc. The study revealed that the proposed NN outperformed linear regression in respect to performance measures such as mean absolute error rate and coefficient of determination. Results from weight interpretation reflected the relative importance of input variables to costs. The NN-based approach can provide an economical and rapid means of cost estimation of WWTP.","PeriodicalId":173506,"journal":{"name":"2009 International Conference on Computational Intelligence and Natural Computing","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126810358","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}
In this paper ceramic roller kiln temperature field uniformity is mainly researched using computational fluid dynamics tools and particle swarm optimization (PSO). In consideration of burning and burning temperature control is key technique of burning regime, in order to produce quality product, it is very important to get the correct ceramic kiln design parameters by simulation model computation. The relationship between ceramic roller kiln simulation model building parameters and temperature field uniformity is preliminary researched in this paper, and particle swarm optimization is used based on the result of research and some feasible conclusion is draw for the peer review.
{"title":"Particle Swarm Optimization of Ceramic Roller Kiln Temperature Field Uniformity Using Computational Fluid Dynamics Tools","authors":"Wenbi Rao, Peng Li","doi":"10.1109/CINC.2009.99","DOIUrl":"https://doi.org/10.1109/CINC.2009.99","url":null,"abstract":"In this paper ceramic roller kiln temperature field uniformity is mainly researched using computational fluid dynamics tools and particle swarm optimization (PSO). In consideration of burning and burning temperature control is key technique of burning regime, in order to produce quality product, it is very important to get the correct ceramic kiln design parameters by simulation model computation. The relationship between ceramic roller kiln simulation model building parameters and temperature field uniformity is preliminary researched in this paper, and particle swarm optimization is used based on the result of research and some feasible conclusion is draw for the peer review.","PeriodicalId":173506,"journal":{"name":"2009 International Conference on Computational Intelligence and Natural Computing","volume":"358 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114839854","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 north of Jiaozhou Bay has become the important region for the development strategy of Qingdao in China, because the development space of the old city district gets saturated. The Moshui River will become the main contaminated river of this area. Neural network was used to build the water quality prediction model of the discharge outlet of the river to predict the concentration of COD, ammonia nitrogen and mineral oil. According to the result, the harmful effects of the emission can be analyzed and the pollution receiving ability of this area can be identified, which can meet the pollution gross control after the completion of these new and high-tech industry regions.
{"title":"Water Quality Prediction of Moshui River in China Based on BP Neural Network","authors":"Q. Miao, Hui Yuan, Changfei Shao, Zhiqiang Liu","doi":"10.1109/CINC.2009.176","DOIUrl":"https://doi.org/10.1109/CINC.2009.176","url":null,"abstract":"The north of Jiaozhou Bay has become the important region for the development strategy of Qingdao in China, because the development space of the old city district gets saturated. The Moshui River will become the main contaminated river of this area. Neural network was used to build the water quality prediction model of the discharge outlet of the river to predict the concentration of COD, ammonia nitrogen and mineral oil. According to the result, the harmful effects of the emission can be analyzed and the pollution receiving ability of this area can be identified, which can meet the pollution gross control after the completion of these new and high-tech industry regions.","PeriodicalId":173506,"journal":{"name":"2009 International Conference on Computational Intelligence and Natural Computing","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127748197","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 proposes a new Fuzzy tuned Inertia weight Particle Swarm Optimization (FIPSO) which remarkably outperforms the standard PSO, previous fuzzy as well as adaptive based PSO methods. Two benchmark functions with asymmetric initial range settings are used to validate the proposed algorithm and compare its performance with those of the other tuned parameter PSO algorithms. Numerical results indicate that FIPSO is competitive due to its ability to increase search space diversity as well as finding the functions’ global optima and a better convergence performance.
{"title":"A New Fuzzy Inertia Weight Particle Swarm Optimization","authors":"P. Yadmellat, S. Salehizadeh, M. Menhaj","doi":"10.1109/CINC.2009.180","DOIUrl":"https://doi.org/10.1109/CINC.2009.180","url":null,"abstract":"This paper proposes a new Fuzzy tuned Inertia weight Particle Swarm Optimization (FIPSO) which remarkably outperforms the standard PSO, previous fuzzy as well as adaptive based PSO methods. Two benchmark functions with asymmetric initial range settings are used to validate the proposed algorithm and compare its performance with those of the other tuned parameter PSO algorithms. Numerical results indicate that FIPSO is competitive due to its ability to increase search space diversity as well as finding the functions’ global optima and a better convergence performance.","PeriodicalId":173506,"journal":{"name":"2009 International Conference on Computational Intelligence and Natural Computing","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122003219","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}
In this paper, we study the classical portfolio selection problem and extend the Brownian motion about the noises involved in the dynamics of wealth to a short-range fractional Brownian motion. Instead of using the classical tool of optimal control as optimization engine, we convert the stochastic optimal control problem into a non-random optimization by using Hamilton and Lagrange multiplier, and conclude the solution of the initial problem. Based on deterministic optimal control principle, we obtain the explicit solution of the optimal strategies. Finally, we present a simulation and analyze the sensitivity of the fractional order to the optimal strategy.
{"title":"Optimal Portfolio Selection under the Short-range Fractional Brownian Motion","authors":"Jian-wei Gao","doi":"10.1109/CINC.2009.159","DOIUrl":"https://doi.org/10.1109/CINC.2009.159","url":null,"abstract":"In this paper, we study the classical portfolio selection problem and extend the Brownian motion about the noises involved in the dynamics of wealth to a short-range fractional Brownian motion. Instead of using the classical tool of optimal control as optimization engine, we convert the stochastic optimal control problem into a non-random optimization by using Hamilton and Lagrange multiplier, and conclude the solution of the initial problem. Based on deterministic optimal control principle, we obtain the explicit solution of the optimal strategies. Finally, we present a simulation and analyze the sensitivity of the fractional order to the optimal strategy.","PeriodicalId":173506,"journal":{"name":"2009 International Conference on Computational Intelligence and Natural Computing","volume":"838 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132049484","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 introduces an automatic liver parenchyma segmentation algorithm that can delineate liver in abdominal CT images. The proposed approach consists of three main steps. Firstly, a texture analysis is applied onto input abdominal CT images to extract pixel level features. Here, two main categories of features, namely Wavelet coefficients and Haralick texture descriptors are investigated. Secondly, support vector machines (SVM) are implemented to classify the data into pixel-wised liver or non-liver. Finally, specially combined morphological operations are designed as a post processor to remove noise and to delineate the liver. Our unique contributions to liver segmentation are twofold: one is that it has been proved through experiments that wavelet features present better classification than Haralick texture descriptors when SVMs are used; the other is that the combination of morphological operations with a pixel-wised SVM classifier can delineate volumetric liver accurately. The algorithm can be used in an advanced computer-aided liver disease diagnosis and surgical planning systems. Examples of applying the algorithm on real CT data are presented with performance validation based on the automatically segmented results and that of manually segmented ones.
{"title":"A Liver Segmentation Algorithm Based on Wavelets and Machine Learning","authors":"S. Luo, Jesse S. Jin, S. Chalup, G. Qian","doi":"10.1109/CINC.2009.225","DOIUrl":"https://doi.org/10.1109/CINC.2009.225","url":null,"abstract":"This paper introduces an automatic liver parenchyma segmentation algorithm that can delineate liver in abdominal CT images. The proposed approach consists of three main steps. Firstly, a texture analysis is applied onto input abdominal CT images to extract pixel level features. Here, two main categories of features, namely Wavelet coefficients and Haralick texture descriptors are investigated. Secondly, support vector machines (SVM) are implemented to classify the data into pixel-wised liver or non-liver. Finally, specially combined morphological operations are designed as a post processor to remove noise and to delineate the liver. Our unique contributions to liver segmentation are twofold: one is that it has been proved through experiments that wavelet features present better classification than Haralick texture descriptors when SVMs are used; the other is that the combination of morphological operations with a pixel-wised SVM classifier can delineate volumetric liver accurately. The algorithm can be used in an advanced computer-aided liver disease diagnosis and surgical planning systems. Examples of applying the algorithm on real CT data are presented with performance validation based on the automatically segmented results and that of manually segmented ones.","PeriodicalId":173506,"journal":{"name":"2009 International Conference on Computational Intelligence and Natural Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132236553","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}
Value based management (VBM) aims to promote value of enterprise. In the management process, value of enterprise is changed dynamically and the value change corresponds to an event which happens to the enterprise, such as success of new product development, fall of share price and so on. In other words, an event indicates a change of enterprise value. In this paper, the concepts of enterprise event, value-event node, and value-event path are proposed and defined formally. A process of VBM can be looked upon as a value-event path. A good management process is a value-event path along which value increases with the event sequence, otherwise value decreases with the event sequence. Furthermore, Value-Event Path Based Policy Management Model is also proposed in this paper. In the model, a policy is a management activity which is driven by an enterprise event, and the execution result of the policy is a new event. Finally, two typical examples are given to show that Value-Event Path Based Policy Management Model is a novel policy-based tool of VBM planning and decision support.
{"title":"Value-Event Path Based Policy Management Model","authors":"Fenglin Peng, Xuping Jiang","doi":"10.1109/CINC.2009.45","DOIUrl":"https://doi.org/10.1109/CINC.2009.45","url":null,"abstract":"Value based management (VBM) aims to promote value of enterprise. In the management process, value of enterprise is changed dynamically and the value change corresponds to an event which happens to the enterprise, such as success of new product development, fall of share price and so on. In other words, an event indicates a change of enterprise value. In this paper, the concepts of enterprise event, value-event node, and value-event path are proposed and defined formally. A process of VBM can be looked upon as a value-event path. A good management process is a value-event path along which value increases with the event sequence, otherwise value decreases with the event sequence. Furthermore, Value-Event Path Based Policy Management Model is also proposed in this paper. In the model, a policy is a management activity which is driven by an enterprise event, and the execution result of the policy is a new event. Finally, two typical examples are given to show that Value-Event Path Based Policy Management Model is a novel policy-based tool of VBM planning and decision support.","PeriodicalId":173506,"journal":{"name":"2009 International Conference on Computational Intelligence and Natural Computing","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133891937","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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