Many studies have shown that knowledge resources have been the real source of innovation and competitiveness of real estate enterprises. Therefore, it is the basic work to establish the real estate enterprise knowledg...Many studies have shown that knowledge resources have been the real source of innovation and competitiveness of real estate enterprises. Therefore, it is the basic work to establish the real estate enterprise knowledge resources framework for implementing knowledge management（KM）,and it should be given enough attention. A sort of the real estate enterprise knowledge resources framework system has been built in this paper based on the thought of Clark ＆ Henderson＇s enterprise knowledge classification, and the contents have been analyzed and expounded. Thus, the real estate enterprises can grasp clearly the basic contents of its knowledge resources, then depict the knowledge system, in the end the solid foundation should be settled for implementing knowledge management.展开更多
In this work, biologically-inspired computing framework is developed for HIV infection of CD4＋ T-cell model using feed-forward artificial neural networks （ANNs）, genetic algorithms （GAs）, sequential quadratic pro...In this work, biologically-inspired computing framework is developed for HIV infection of CD4＋ T-cell model using feed-forward artificial neural networks （ANNs）, genetic algorithms （GAs）, sequential quadratic programming （SQP） and hybrid approach based on GA-SQP. The mathematical model for HIV infection of CD4＋ T-cells is represented with the help of initial value problems （IVPs） based on the system of ordinary differential equations （ODEs）. The ANN model for the system is constructed by exploiting its strength of universal approximation. An objective function is developed for the system through unsupervised error using ANNs in the mean square sense. Training with weights of ANNs is carried out with GAs for effective global search supported with SQP for efficient local search. The proposed scheme is evaluated on a number of scenarios for the HIV infection model by taking the different levels for infected cells, natural substitution rates of uninfected cells, and virus particles. Comparisons of the approximate solutions are made with results of Adams numerical solver to establish the correctness of the proposed scheme. Accuracy and convergence of the approach are validated through the results of statistical analysis based on the sufficient large number of independent runs.展开更多
基金Jiangsu Planned Projects for Postdoctoral Research Funds(No.0802076C)
文摘Many studies have shown that knowledge resources have been the real source of innovation and competitiveness of real estate enterprises. Therefore, it is the basic work to establish the real estate enterprise knowledge resources framework for implementing knowledge management（KM）,and it should be given enough attention. A sort of the real estate enterprise knowledge resources framework system has been built in this paper based on the thought of Clark ＆ Henderson＇s enterprise knowledge classification, and the contents have been analyzed and expounded. Thus, the real estate enterprises can grasp clearly the basic contents of its knowledge resources, then depict the knowledge system, in the end the solid foundation should be settled for implementing knowledge management.
文摘In this work, biologically-inspired computing framework is developed for HIV infection of CD4＋ T-cell model using feed-forward artificial neural networks （ANNs）, genetic algorithms （GAs）, sequential quadratic programming （SQP） and hybrid approach based on GA-SQP. The mathematical model for HIV infection of CD4＋ T-cells is represented with the help of initial value problems （IVPs） based on the system of ordinary differential equations （ODEs）. The ANN model for the system is constructed by exploiting its strength of universal approximation. An objective function is developed for the system through unsupervised error using ANNs in the mean square sense. Training with weights of ANNs is carried out with GAs for effective global search supported with SQP for efficient local search. The proposed scheme is evaluated on a number of scenarios for the HIV infection model by taking the different levels for infected cells, natural substitution rates of uninfected cells, and virus particles. Comparisons of the approximate solutions are made with results of Adams numerical solver to establish the correctness of the proposed scheme. Accuracy and convergence of the approach are validated through the results of statistical analysis based on the sufficient large number of independent runs.
