Risk assessment of ballast water with the application of standard additive model;
运用标准可加性模型对船舶压载水进行风险评价
The standard additive model proposed by Kosko in the beginning of 1990 s is the most important part of the additive fuzzy systems.
在对可加性模糊系统的最重要的组成部分标准可加性模型（SAM）进行研究的基础上,把SAM系统与神经网络相结合,并推导出适合此网络结构的简化的隶属函数参数的学习算法,从仿真结果可知该方法简单、学习次数少、逼近精度高。
In addition, following standard additive model theory, strategies model based on negotiation agent was designed.
此外,应用标准可加性模型原理设计了谈判Agent的策略模型,从而构建了应用范围广泛的自动化谈判Agent模型。
Possibilistic linear model based on possibility theory has a pivotal role in fuzzy modeling and has been widely studied.
基于可能性理论的可能性线性模型在模糊建模方面有着非常重要的作用,并已得到了广泛的研究。
Fuzzy neural network based on the SAM system
基于标准可加性模型的模糊神经网络
Certificate-based hybrid encryption scheme in the standard model
标准模型下基于认证的混合加密算法
On the Strongly Unforgeable Digital Signatures in the Standard Model
标准模型下强不可伪造数字签名研究
Risk Acceptability Criterion and Index Model for Oil and Gas Pipelines
油气管道风险可接受准则与指标模型
Study of security of proxy multi-signature under standard model
标准模型下的代理多重签名的安全性
The Accuracy of Risk Measurement model Base on Standard Residuals;
基于标准残差的极值风险模型准确性研究
Chosen Ciphertext Secure Identity-based Encryption in the Standard Model
标准模型下选择密文安全的基于身份加密方案
Generic Construction of Certificate-based Encryption Scheme in the Standard Model
标准模型下基于证书的加密方案的通用构造
A New Hierarchical Identity-Based Encryption in the Standard Model
标准模型下一种新的基于身份的分级加密方案
The FIPS-ZZ40-ZZ cryptographic module limits security FIPS-ZZ40-ZZ functions to those approved by the United States Federal Government's internal standards.
加密模块可以把安全性功能限制为美国联邦政府内部标准认可的那些功能。
Researsch of Analog Circuit Functionality Test Module Based on IEEE1149.4 Standard
基于IEEE 1149.4标准的模拟电路功能性测试模型研究
The SS7 standard maps onto the OSI 7-Layer Reference Model, and consists of the following layers:
SS7标准可映射到OSI7层参考模型，并由下列层组成：
New provably secure identification protocol in standard model
新的在标准模型中可证安全身份鉴别协议
Efficient identification protocol provably secure in standard model
高效的标准模型下可证安全的身份鉴别协议
Based on the field measurement data, the least squaresmethod and the direct optimization method are compared for a realistic system load modeling.
对一实际工业用户负荷模型参数辨识表明，步长加速法优于常用的标准格式线性最小二乘法。
Results The accuracy and precision of standardized phantom were ?0.1%? and 8.6%.
结果自制标准体模精确性和准确性分别是0．1％和8．6％，性能可靠。
Robust stability analysis of delayed discrete-time standard neural network model
离散时滞标准神经网络模型的鲁棒稳定性分析
The Application Analysis of Logistics Standardization in Enterprise and the Model of Informational Share Game
物流标准化应用性分析及信息共享博弈模型