Abstract: Provided are an energy-saving control method and device for a self-service device. The method includes: acquiring to-be-learned sample information from historical usage data of users of the self-service device, where the sample information indicates the number of users which use the self-service device in each of different sub-periods of a period of time; learning the to-be-learned sample information by using a preset Bayesian prior probability model, to obtain a learning result; updating the Bayesian prior probability model based on the learning result; predicting the number of users in each of sub-periods of a preset period of time by using the updated Bayesian prior probability model, to obtain the predicted number of users at the self-service device; and modifying a sleep interval of the self-service device in each of the sub-periods based on the predicted number of users.

Abstract: Provided are a method and device for authenticating an identity based on fusion of multiple biological characteristics. The method includes: collecting at least two types of biological characteristic identity information of a to-be-identified user; performing characteristic extraction on each type of the collected biological characteristic identify information, to obtain characteristic information corresponding to the type; establishing characteristic matrixes based on the characteristic information; performing normalization processing on each of the characteristic matrixes; performing dynamic weighting fusion on all of the normalized characteristic matrixes, to obtain a fused characteristic matrix; matching the fused characteristic matrix with a preset standard matrix, to obtain a matching score; and obtaining an identity identification result of the to-be-identified user based on a Bayesian decision model and the matching score.

Abstract: Provided are an energy-saving control method and device for a self-service device. The method includes: acquiring to-be-learned sample information from historical usage data of users of the self-service device, where the sample information indicates the number of users which use the self-service device in each of different sub-periods of a period of time; learning the to-be-learned sample information by using a preset Bayesian prior probability model, to obtain a learning result; updating the Bayesian prior probability model based on the learning result; predicting the number of users in each of sub-periods of a preset period of time by using the updated Bayesian prior probability model, to obtain the predicted number of users at the self-service device; and modifying a sleep interval of the self-service device in each of the sub-periods based on the predicted number of users.

Abstract: Provided are a method and device for authenticating an identity based on fusion of multiple biological characteristics. The method includes: collecting at least two types of biological characteristic identity information of a to-be-identified user; performing characteristic extraction on each type of the collected biological characteristic identify information, to obtain characteristic information corresponding to the type; establishing characteristic matrixes based on the characteristic information; performing normalization processing on each of the characteristic matrixes; performing dynamic weighting fusion on all of the normalized characteristic matrixes, to obtain a fused characteristic matrix; matching the fused characteristic matrix with a preset standard matrix, to obtain a matching score; and obtaining an identity identification result of the to-be-identified user based on a Bayesian decision model and the matching score.