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1)  deterministic parsers
决策式算法
2)  decision-making algorithm
决策算法
1.
Research on decision-making algorithm of offensive players’behavior in football match
足球比赛中进攻方队员行为决策算法研究
2.
A decision-making algorithm based on class algorithms is provided by which many ruleless and random data can be classified.
提出基于分类思想的性能判定决策算法,对大量的无规则的杂乱的网关经验数据进行分类。
3.
Aiming at this problem,multi-sensor data fusion algorithm and minimum risk decision-making algorithm are studied to meet the needs of HVAC system to make a reasonable decision-making.
针对HVAC(Heating Ventilation and Air Conditioning)系统检测装置和控制系统存在的时间滞后,使人体舒适性得不到很好的满足,并且有额外的能量消耗,进而研究了多传感器数据融合算法及基于D-S证据理论的最小风险决策算法以满足HVAC系统做出合理的决策。
3)  decision algorithm
决策算法
1.
An adaptation decision algorithm was also presented which was realized by retaining most of the higher quality layers, and dropping lower quality layers as far as possible.
264/AVC视频适配模型和系统,并设计了多媒体资源适配引擎,提出了相应的资源适配决策算法,即在满足网络可用带宽的约束条件下,丢弃低感知质量层的视频帧,而尽可能多地保留高感知质量层的视频帧。
2.
Then,according to the features of the generalized information table,the algorithms of acquiring minimal attribute reduction,attribute value reduction and minimum decision algorithm are put forward.
首先介绍了决策表、广义信息表的构造及特点,然后给出了求决策表的最小属性约简及最小决策算法的计算方法。
3.
It includes a behavior-based two-layer dynamic agent architecture, a behavior-based decision algorithm, and a role-based dynamic multi-agent cooperation model.
针对机器人足球仿真比赛,提出了一种新的多智能体系统结构,它包括基于行为的双层动态智能体结构和决策算法以及基于角色的动态多智能体协作模型。
4)  distributed decision tree algorithm
分布式决策树算法
5)  decision tree arithmetic
决策树算法
1.
Difficulty degrees of roof coal caving in 30 collieries are assorted by decision tree arithmetic in data mining technology.
为解决以往顶煤冒放性评价方法存在的计算过程复杂,不能生成评价规则而不便于推广的缺点,采用数据挖掘技术中决策树算法对30个矿井的顶煤冒放性进行分类研究,在此基础上生成了一棵顶煤冒放性评价决策树,并由此形成了一系列评价规则,最后就该算法的应用效果进行评价。
6)  decision tree algorithm
决策树算法
1.
Two layers decision tree algorithm of SQL Server 2000/Analysis Service is created by class count table and depth first strategy.
微软的SQL Server2000是当今最流行的数据库管理软件之一,研究了在SQL Server 2000上数据挖掘实现方面的决策树算法。
2.
Secondly, the paper analyzes the extremely concerned problem about the loss of customers in telecommunications industry, then introduces decision tree algorithm and analyzes its application in details, that is customer churn warning model,including the definition and the establishment of model,presentation and interpretation of results, etc.
其次对电信行业极为关心的客户流失问题进行分析,进而引入决策树算法,并对决策树算法的应用——客户流失预警模型进行了详尽的分析,包括模型的定义、模型建立和结果展现与解释等等。
3.
This thesis compares and analyzes the typical decision tree algorithms, the ID3 algorithm and C4.
本文比较和分析了几种典型的决策树算法,着重对ID3算法和C4。
补充资料:BP算法
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性质:又称逆推学习算法,简称BP算法,是1986年鲁梅哈特(D. E. Rumelhart)和麦克莱朗德(J. L. McClelland)提出来的。用样本数据训练人工神经网络(一种模仿人脑的信息处理系统),它自动地将实际输出值和期望值进行比较,得到误差信号,再根据误差信号从后(输出层)向前(输入层)逐层反传,调节各神经层神经元之间的连接权重,直至误差减至满足要求为止。反向传播算法的主要特征是中间层能对输出层反传过来的误差进行学习。这种算法不能保证训练期间实现全局误差最小,但可以实现局部误差最小。BP算法在图像处理、语音处理、优化等领域得到应用。

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