逻辑数据模型的一般设计目标是正确性、一致性、非冗余和简单性。
The general design objectives of the logical data model are correctness, consistency, non-redundancy and simplicity.
从这一阶段开始，该解决方案就适用自底向上的方法了，这意味着这个逻辑数据模型中仅仅将最重要和紧迫的业务主题领域锁定为目标。
Starting from this stage, this solution is adapting the bottom-up approach, which means that only the most important and urgent business subject areas are targeted in this logical data model.
本节展示如何使用一个物理模型及其对象来实现这个目标——对于逻辑模型也可以使用类似的方法。
This section shows you how to do this using a physical model and its objects. A similar approach can be used for logical models as well.
如果要从同一个逻辑模型实现多个目标数据库，那么可以使用创建新模型的选项。
The option to create a new model is good to implement multiple target databases from the same logical model.
通信设计的目标是要为电子谈判媒体的逻辑空间定义电子谈判方案模型。
The goal of the communication design is to define electronic negotiation scenario models for the logic space of an electronic negotiation medium.
然后对系统展开需求分析和目标设计，确定了基于产品信用信息集成的产品信用管理信息系统的逻辑结构模型及功能。
Then studies the requirement analysis and object design, defines the logic structure model and function of product credit management information system base on product credit information integration.
理论家喜欢概念和模型，能看到全局的全貌，能感觉到智力的伸展，结构和清晰的目标和思想的逻辑表达。
Theorists like concepts and models, to see the overall picture, to feel intellectually stretched, structure and clear objectives and a logical presentation of ideas.
该模型具有考虑投标的多目标性、承包商的主观判断以及启发式逻辑相结合性以及对过去的工程项目和竞争者数据的低度依赖性等特征。
The established model has many characters, such as multi-objective for bidding, combined subjective opinion with enlightened logic as well as low leanness on data on past project and competitor.
针对卡尔曼滤波器对系统模型依赖性强、鲁棒性差和跟踪机动目标能力有限的问题，提出了一种新的利用混合模糊逻辑和标准卡尔曼滤波器的联合算法。
The Kalman filter has been commonly used in target tracking, however its performance may be degraded in presence of maneuver, low robustness and strong model dependence.
针对卡尔曼滤波器对系统模型依赖性强、鲁棒性差和跟踪机动目标能力有限的问题，提出了一种新的利用混合模糊逻辑和标准卡尔曼滤波器的联合算法。
The Kalman filter has been commonly used in target tracking, however its performance may be degraded in presence of maneuver, low robustness and strong model dependence.
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