41 results about "Uncertainty interval" patented technology

The invention relates to a service recommendation method based on user risk preferences. According to the service recommendation method based on the user risk preferences, an attribute extracting method based on the user risk preferences and the service recommendation method based on the user risk preferences are used. The attribute extracting method based on the user risk preferences is a simplifying method according to the characteristic of multiple attributes of services. According to the service recommendation method based on the user risk preference, considering that different users have different inclinations to take risks of unknown services, the users are classified according to the different user risk preferences, corresponding rules are adopted for different types of users, effective attributes better meeting requirements of the different types of users are extracted from multiple non-functional attributes from the services, similarity calculation is conducted, and a recommendation is formed finally. By the adoption of the service recommendation method based on the user risk preferences, simplification of the multiple attributes of services is achieved, a solution to the problem that uncertain intervals exists when the non-functional attributes of the services are grated during service recommendation is provided, in this way, recommendation results can better meet the requirements of the different types of users, and a powerful method and tool are provided for service recommendation.

A method and device are useful for enabling a trust relationship using an expired public key infrastructure (PKI) certificate. The method includes determining at a relying party a maximum permissible grace period during which the PKI certificate can be conditionally granted a valid status (step 905). Next, at the relying party an uncertainty interval is determined, during which the relying party is unable to detect a revocation of the PKI certificate (step 910). A certificate grace period is then determined at the relying party from a function of the maximum permissible grace period, the uncertainty interval and at least one attribute defined in the PKI certificate (step 915). Using the PKI certificate, a trust relationship is then enabled between the relying party and a certificate holder of the PKI certificate, after determining the grace period and before an expiration of the grace period (step 920).

A method applied to recognizing vulnerabilities of single-event soft errors in processor systems includes: based on influences of single-event soft error protective design upon system performance and resources, establishing an importance function module for vulnerability recognition model analytic protection; according to an operating principle of compilation instructions, dividing an element circuit node (a specific function / subfunction module used for pre-compiling codes or instruction sequences) from code level of design, extracting vulnerability factors of the element circuit node from instruction level by compile mapping relation, and performing grade domain division; finally, subjecting uncertainty intervals (gray level intervals) of vulnerability factor grading for the element circuit node to credibility evaluation according to a gray level system theory, and acquiring computation results according to grade credibility sorting. The method has the advantages that the simple vulnerability analysis method for processor systems is provided, system cost and performance loss are reduced on the premise of implementing reliability, and system protection effect is improved.

A system that facilitates reducing uncertainty in a quantized signal. During operation, the system measures a quantized output signal from a sensor. Next, the system obtains an initial value for an uncertainty interval for the quantized output signal. The system then margins the quantized output signal high by introducing a controlled increase in the mean of the quantized output signal to produce a high-margined quantized output signal. Next, the system measures the high-margined quantized output signal from the sensor. The system then uses information obtained from the high-margined quantized output signal to reduce the uncertainty interval for the quantized output signal.

The invention discloses a validation method of a non-probabilistic Bayesian model for an aircraft structure. The validation method comprises the following steps: firstly deducing a non-probabilistic Bayesian theory according to a proposed interval inclusion degree theory; then updating and validating an uncertainty numerical simulation model based on the proposed non-probabilistic Bayesian theory and in combination with validated test data and an uncertainty interval propagation algorithm. The validation method disclosed by the invention is performed under a Bayesian probability theory framework, prior information can be fully utilized, and the reliability of the numerical simulation model can be given; the model validation can be performed aiming at the situations of poor information and less data, so that the problem that a large amount of experimental data is needed when a traditional model confirmation method is utilized is solved.