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Received:February 19, 2012 Revised:April 02, 2012
Received:February 19, 2012 Revised:April 02, 2012
中文摘要: 针对从固定认知结构中生成认知模型的局限性,提出在认知元素固定而认知结构不固定的学习中使用贝叶斯推理方法和PFNET理论从以往学习者的样本信息中按学习者的要求生成“最佳Ki结点集合”和“最优Ki认知链”,获得B-P认知模型；对B-P认知模型的生成原理进行说明并通过实例验证该模型的有效性和可行性。
Abstract:Aiming at the limitation of generating cognitive model from fixed cognitive structure, this paper proposes that in the learning process of fixed cognitive elements and not fixed cognitive structure using bayesian inference method and PFNET theory to generate “the optimal Ki set of nodes” and “the optimal Ki cognitive link” according to the learner requirement from the sample information of previous learners, and get the B-P cognitive model; explaining the generation principle of B-P cognitive model and verifying the effectiveness and feasibility of the model by example.
keywords: B-P cognitive model cognitive structure the optimal Ki set of nodes the optimal Ki cognitive link
文章编号： 中图分类号： 文献标志码：
基金项目:
| Author Name | Affiliation |
| FU Yong-Gui | College of Information Management, Shanxi University of Finance and Economics, Taiyuan 030031, China |
| Author Name | Affiliation |
| FU Yong-Gui | College of Information Management, Shanxi University of Finance and Economics, Taiyuan 030031, China |
引用文本：
付永贵.基于贝叶斯推理与PFNET理论的认知模型.计算机系统应用,2012,21(7):186-190
FU Yong-Gui.Cognitive Model Based on Bayesian Inference and PFNET Theory.COMPUTER SYSTEMS APPLICATIONS,2012,21(7):186-190
付永贵.基于贝叶斯推理与PFNET理论的认知模型.计算机系统应用,2012,21(7):186-190
FU Yong-Gui.Cognitive Model Based on Bayesian Inference and PFNET Theory.COMPUTER SYSTEMS APPLICATIONS,2012,21(7):186-190
