Based on the characteristics of ATM system and the special requirement of financial transaction, an overall design of hardware and software structure of ATM was made. For software structure, the pattern of modules and...Based on the characteristics of ATM system and the special requirement of financial transaction, an overall design of hardware and software structure of ATM was made. For software structure, the pattern of modules and table? drive is adopted to realize the security of financial transaction and the diagnosis of communication fault. A new method, which is based on the application layer, transport layer and network layer, is used for diagnosing communication fault. Supporting both magnetic card and IC card, the system has been put into use in real financial systems, and has brought about both economic and social effects.展开更多
A novel configuration performance prediction approach with combination of principal component analysis(PCA) and support vector machine(SVM) was proposed.This method can estimate the performance parameter values of a n...A novel configuration performance prediction approach with combination of principal component analysis(PCA) and support vector machine(SVM) was proposed.This method can estimate the performance parameter values of a newly configured product through soft computing technique instead of practical test experiments,which helps to evaluate whether or not the product variant can satisfy the customers' individual requirements.The PCA technique was used to reduce and orthogonalize the module parameters that affect the product performance.Then,these extracted features were used as new input variables in SVM model to mine knowledge from the limited existing product data.The performance values of a newly configured product can be predicted by means of the trained SVM models.This PCA-SVM method can ensure that the performance prediction is executed rapidly and accurately,even under the small sample conditions.The applicability of the proposed method was verified on a family of plate electrostatic precipitators.展开更多
For modeling and simulation of distillation process, there are lots of special purpose simulators along with their model libraries, such as Aspen Plus and HYSYS. However, the models in these tools lack of flexibility ...For modeling and simulation of distillation process, there are lots of special purpose simulators along with their model libraries, such as Aspen Plus and HYSYS. However, the models in these tools lack of flexibility and are not open to the end-user. Models developed in one tool can not be conveniently used in others because of the barriers among these simulators. In order to solve those problems, a flexible and extensible distillation system model library is constructed in this study, based on the Modelica and Modelica-supported platform MWorks, by the object-oriented technology and level progressive modeling strategy. It supports the reuse of knowledge on different granularities： physical phenomenon, unit model and system model. It is also an interface-friendly, accurate, fast PC-based and easily reusable simulation tool, which enables end-user to customize and extend the framework to add new functionality or adapt the simulation behavior as required. It also allows new models to be composed programmatically or graphically to form more complex models by invoking the existing components. A conventional air distillation column model is built and calculated using the library, and the results agree well with that simulated in Anen Plus.展开更多
Various binary similarity measures have been employed in clustering approaches to make homogeneous groups of similar entities in the data. These similarity measures are mostly based only on the presence or absence of ...Various binary similarity measures have been employed in clustering approaches to make homogeneous groups of similar entities in the data. These similarity measures are mostly based only on the presence or absence of features. Binary similarity measures have also been explored with different clustering approaches （e.g., agglomera- tive hierarchical clustering） for software modularization to make software systems understandable and manageable. Each similarity measure has its own strengths and weaknesses which improve and deteriorate the clustering results, respectively. We highlight the strengths of some well-known existing binary similarity measures for software mod- ularization. Furthermore, based on these existing similarity measures, we introduce several improved new binary similarity measures. Proofs of the correctness with illustration and a series of experiments are presented to evaluate the effectiveness of our new binary similarity measures.展开更多
文摘Based on the characteristics of ATM system and the special requirement of financial transaction, an overall design of hardware and software structure of ATM was made. For software structure, the pattern of modules and table? drive is adopted to realize the security of financial transaction and the diagnosis of communication fault. A new method, which is based on the application layer, transport layer and network layer, is used for diagnosing communication fault. Supporting both magnetic card and IC card, the system has been put into use in real financial systems, and has brought about both economic and social effects.
基金Project(9140A18010210KG01) supported by the Departmental Pre-Research Fund of China
文摘A novel configuration performance prediction approach with combination of principal component analysis(PCA) and support vector machine(SVM) was proposed.This method can estimate the performance parameter values of a newly configured product through soft computing technique instead of practical test experiments,which helps to evaluate whether or not the product variant can satisfy the customers' individual requirements.The PCA technique was used to reduce and orthogonalize the module parameters that affect the product performance.Then,these extracted features were used as new input variables in SVM model to mine knowledge from the limited existing product data.The performance values of a newly configured product can be predicted by means of the trained SVM models.This PCA-SVM method can ensure that the performance prediction is executed rapidly and accurately,even under the small sample conditions.The applicability of the proposed method was verified on a family of plate electrostatic precipitators.
基金Supported by the Major State Basic Research Development Program of China (2011CB706502)
文摘For modeling and simulation of distillation process, there are lots of special purpose simulators along with their model libraries, such as Aspen Plus and HYSYS. However, the models in these tools lack of flexibility and are not open to the end-user. Models developed in one tool can not be conveniently used in others because of the barriers among these simulators. In order to solve those problems, a flexible and extensible distillation system model library is constructed in this study, based on the Modelica and Modelica-supported platform MWorks, by the object-oriented technology and level progressive modeling strategy. It supports the reuse of knowledge on different granularities： physical phenomenon, unit model and system model. It is also an interface-friendly, accurate, fast PC-based and easily reusable simulation tool, which enables end-user to customize and extend the framework to add new functionality or adapt the simulation behavior as required. It also allows new models to be composed programmatically or graphically to form more complex models by invoking the existing components. A conventional air distillation column model is built and calculated using the library, and the results agree well with that simulated in Anen Plus.
基金supported by the Office of Research,Innovation,Commercialization and Consultancy(ORICC)Universiti Tun Hussein Onn Malaysia(UTHM),Malaysia(No.U063)
文摘Various binary similarity measures have been employed in clustering approaches to make homogeneous groups of similar entities in the data. These similarity measures are mostly based only on the presence or absence of features. Binary similarity measures have also been explored with different clustering approaches （e.g., agglomera- tive hierarchical clustering） for software modularization to make software systems understandable and manageable. Each similarity measure has its own strengths and weaknesses which improve and deteriorate the clustering results, respectively. We highlight the strengths of some well-known existing binary similarity measures for software mod- ularization. Furthermore, based on these existing similarity measures, we introduce several improved new binary similarity measures. Proofs of the correctness with illustration and a series of experiments are presented to evaluate the effectiveness of our new binary similarity measures.
