Technology innovation and evolution process of library space for readers / 中华医学图书情报杂志

The change of library space is driven by various factors, such as technology innovation, users demand and the changing competitive environments. The evolution processes of library space were thus clarified by retrie-ving CNKI, namely from computer and IT to Internet and wide application of information and communication tech-nology, from physical space to virtual space, from space function to information commons, learning, pioneering work and social intercourse, which can eventually lead to the intelligent, individual and ubiquitous library space.

Modelling Method of Combination Forecast Model Based on Data Mining / 中国卫生统计

Objective Research on variable substitution to non-linear regression forecast model precision's influence, and seek the modelling method that can improve the forecast precision. Methods Based on the data mining,the transform in space and the weighted processing combined method, make full use of information that the primary data provide. Results Given modelling method of combination forecast model based on the data mining. Conclusion Based on data mining's combination forecast model's modelling method can reduce the serious influence that the variable substitution brings and has fully used useful information in the primary data. It obviously improved the accuracy of the prediction model.

A new method for calculating regression parameters of nonlinear biology model and its application / 重庆医科大学学报

Objective:To study the disturbance creatd by the variable transformation within regression parameters of nonlinear biology models and find a new method removing or reducing the disturbance.Methods:To use the space transformation,Taylor series and weight method to remove or reduce the serious disturbance created by the variable transformation within regression parameters of nonlinear biology models.Results:Giving a new method calculating regression parameters of nonlinear biology models.Conclusion:The new method can remove or reduce the serious disturbance created by the variable transformation and remain the advantage of variable transformation.It can not only improve regression precision of the nonlinear biology models but also can find problems hidden in the original data.