Abstract: Disclosed are a power demand side speech interaction method and system. The method includes: obtaining original demand information, the original demand information including user's basic information, user demand information, and a user demand time; converting the original demand information into first information in text format; performing text statistical analysis based on an industry term on the first information in text format, to obtain second information; searching for corresponding user's actual information from a database according to the second information; outputting the user's actual information; searching for a corresponding forecasting model from the database, according to the second information and the user's basic information; calculating, according to a policy limit value of latest policy information in the database, a time for which the model corresponding to the user's basic information reaches the policy limit value; and transmitting an early warning message.

Abstract: Disclosed are a power demand side speech interaction method and system. The method includes: obtaining original demand information, the original demand information including user's basic information, user demand information, and a user demand time; converting the original demand information into first information in text format; performing text statistical analysis based on an industry term on the first information in text format, to obtain second information; searching for corresponding user's actual information from a database according to the second information; outputting the user's actual information; searching for a corresponding forecasting model from the database, according to the second information and the user's basic information; calculating, according to a policy limit value of latest policy information in the database, a time for which the model corresponding to the user's basic information reaches the policy limit value; and transmitting an early warning message.

Abstract: A method including: receiving verification information returned according to a verification request, wherein the verification information comprises a verification question corresponding to a verification target; displaying the verification question; determining a sliding distance according to the sliding indication and determining a verification answer according to the verification target corresponding to the sliding distance; and determining a verification result according to the verification question and the verification answer. According to the techniques of the present disclosure, a verification target such as a picture is gradually displayed with a sliding operation, which is not only difficult to obtain the answer through static analysis but also difficult to be done through a machine operation, thus improving verification accuracy.

Abstract: A method includes: obtaining training texts; for each of the training texts, performing the following operations: obtaining a word vector of each word in the current training text as a parameter of a first quantum circuit to obtain quantum states; inputting each of the quantum states to second, third, and fourth quantum circuits and performing measurement; calculating one group of weight values corresponding to each word to obtain a feature vector corresponding to the current training text; inputting the feature vector to a neural network model to obtain a prediction value; and determining a value of loss function based on the prediction value and a label value, and adjusting parameters corresponding to the second, third, and fourth quantum circuits and the neural network model based on the value of the loss function.

Abstract: A method and device for processing quantum data are provided, which are related to the field of quantum computation. The method includes: determining a quantum data set and category information characterizing a data type of the quantum data set; applying a local quantum circuit to a quantum data point contained in the quantum data set, wherein the local quantum circuit is obtained after part of qubits are selected from a plurality of qubits contained in a parameterized quantum circuit; acquiring state information of qubits in the local quantum circuit after being applied to the quantum data point through measurement, and taking the state information and the category information as training data for training a classical neural network to obtain a trained classical neural network, wherein a data type of a quantum data set to be processed can be identified by the trained classical neural network.