智能网络教学系统的应用改变了传统计算机辅助教学系统受到通信技术影响,而导致教师与学生之间无法交互的问题,在良好校园网络环境下,提出了基于人工智能网络的远程教学系统设计。依据系统各个模块功能,设计硬件结构。其中,学生学习模...智能网络教学系统的应用改变了传统计算机辅助教学系统受到通信技术影响,而导致教师与学生之间无法交互的问题,在良好校园网络环境下,提出了基于人工智能网络的远程教学系统设计。依据系统各个模块功能,设计硬件结构。其中,学生学习模块是由教学协调代理及多个其他代理组成的,负责具体教学材料呈现、问题解决,通过协作机制实现知识共享,为系统提供个性化教学依据。教师教学模块主要根据学习要求为学生提供相应教学策略,利用自身推理机制对教学过程中遇到的问题进行智能指导。评估模块是利用评估规则分析学生响应,对学生学习行为、态度、效果及能力等方面进行综合评估。人机界面是学生、教师与系统之间交流媒介,通过学生登录界面,完成个人登录操作。以SQL Server 2000为数据库服务器设计软件功能,在确定数据属性的情况下,进行数据在线评估,结合网络技术,完成远程教学。由仿真实验可知,该系统教学效率较高,能够为学生学习提供设备支持。展开更多
It is necessary for mine countermeasure systems to recognise the model of a water mine before destroying because the destroying measures to be taken must be determined according to mine model. In this paper, an immune...It is necessary for mine countermeasure systems to recognise the model of a water mine before destroying because the destroying measures to be taken must be determined according to mine model. In this paper, an immune neural network (INN) along with water mine model recognition system based on multi-agent system is proposed. A modified clonal selection algorithm for constructing such an INN is presented based on clonal selection principle. The INN is a two-layer Boolean network whose number of outputs is adaptable according to the task and the affinity threshold. Adjusting the affinity threshold can easily control different recognition precision, and the affinity threshold also can control the capability of noise tolerance.展开更多
文摘智能网络教学系统的应用改变了传统计算机辅助教学系统受到通信技术影响,而导致教师与学生之间无法交互的问题,在良好校园网络环境下,提出了基于人工智能网络的远程教学系统设计。依据系统各个模块功能,设计硬件结构。其中,学生学习模块是由教学协调代理及多个其他代理组成的,负责具体教学材料呈现、问题解决,通过协作机制实现知识共享,为系统提供个性化教学依据。教师教学模块主要根据学习要求为学生提供相应教学策略,利用自身推理机制对教学过程中遇到的问题进行智能指导。评估模块是利用评估规则分析学生响应,对学生学习行为、态度、效果及能力等方面进行综合评估。人机界面是学生、教师与系统之间交流媒介,通过学生登录界面,完成个人登录操作。以SQL Server 2000为数据库服务器设计软件功能,在确定数据属性的情况下,进行数据在线评估,结合网络技术,完成远程教学。由仿真实验可知,该系统教学效率较高,能够为学生学习提供设备支持。
文摘It is necessary for mine countermeasure systems to recognise the model of a water mine before destroying because the destroying measures to be taken must be determined according to mine model. In this paper, an immune neural network (INN) along with water mine model recognition system based on multi-agent system is proposed. A modified clonal selection algorithm for constructing such an INN is presented based on clonal selection principle. The INN is a two-layer Boolean network whose number of outputs is adaptable according to the task and the affinity threshold. Adjusting the affinity threshold can easily control different recognition precision, and the affinity threshold also can control the capability of noise tolerance.
