神经网络可以解决高炉专家系统最困难的知识获取与推理能力弱等问题，并适合于对高炉分布数据进行模式识别。
Neural network can solve some problems of blast furnace expert system such as knowledge getting and inference ability, and it is suitable for pattern recognition of blast furnace data distribution.
安全分布式数据库系统中，常会出现信息不一致现象，由此产生推理通道。
In a secure distributed database system, information inconsistency often exists, thus gives rise to inference channel.
最后，针对学者提出的“部分分布决定性定理(PD定理)”，本文论证了其推理过程中存在的问题，说明该定理是错误的。
Lastly, this paper finds a mistake in a theorem named deterministic theorem of the partial distribution (PD theorem) by its author, and explains the reason.
贝叶斯学习是一种基于已知的概率分布和观察到的数据进行推理，做出最优决策的概率手段。
Bayesian learning is a probability method that makes optimal decision based on known probability distribution and recently observed data.
神经元网络启发式的并行、分布特征和可学习性为专家系统的知识表达和获取、不确定性推理提供了新的途径。
The parallelism, distribution and capability of learning of neural net heuristics provide a new way for knowledge acquisition, knowledge representation and uncertainty reasoning in expert systems.
结合经验性参数趋势线、暴雨参数空间分布图与推理公式法确定无资料流域设计条件下最大清水洪峰流量和最大山洪洪峰流量。
According to the trend line formula of empirical and the chart of the spacial interpolation of hard rain parameter, maximum discharge of ungaged basins are confirm.
结合经验性参数趋势线、暴雨参数空间分布图与推理公式法确定无资料流域设计条件下最大清水洪峰流量和最大山洪洪峰流量。
According to the trend line formula of empirical and the chart of the spacial interpolation of hard rain parameter, maximum discharge of ungaged basins are confirm.
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