In human concept learning, people can naturally combine a handful of labeled data with
abundant unlabeled data when they make classification decisions, which is also known as …

Artificial intelligence technology has made important progress in machine learning and
problem-solving with relatively determined boundary conditions. However, the more …

针对深度神经网络AI 研究的可解释性瓶颈, 指出刚性逻辑(数理形式逻辑) 和二值神经元等价,
二值神经网络可转换成逻辑表达式, 有强可解释性. 深度神经网络一味增加中间层数来拟合大 …

问题智能处理是人工智能领域具有挑战性和交叉性的课题. 大数据与人工智能技术背景下,
为了给具有较高普遍性的开放性问题求解提供新的理论支撑, 对因素空间与可拓学做了对比分析 …

Distance learning, a new style of teaching, can create a strong sensation of presence
through real and vivid communication. It is set to reach a communication effect of deep …

汪培庄, 周红军, 何华灿, 等. 因素表示的信息空间与广义概率逻辑[J]. 智能系统学报, 2019, 14
(5): 843-852. DOI: 10.11992/tis. 201810021.WANG Peizhuang, ZHOU Hongjun, HE Huacan …

The power load forecasting plays an important role in the economical and safe operation of
the modern power system. However, the characteristics of power load such as non …

In the process of system operation, the ability to complete the predetermined function is
changing, which is uncertain for the system designer. In order to study the uncertainty of …

为保障煤矿工作面液压支架安全高效运行, 提高供液系统智能化水平, 通过分析供液系统多层
智能控制目标, 借鉴高等人工智能原理中的意识–情感–智能三位一体思想 …

为解决人工智能中莫拉维克悖论提出的问题, 基于因素空间思想提出一种人工智能样本选择策略
. 首先通过因素空间论证了莫拉维克悖论的证确定. 其次论述了人的选择过程即是比较过程的 …