8results about How to "Ensure openness and transparency" patented technology

The invention discloses an intelligent bid evaluation expert extraction and management system, and relates to the technical field of expert extraction systems. Comprising a data cleaning and compression module, a database logic and table relation design module, an expert information collection standard and automation module, an information real-time updating and principal management module, an extraction algorithm design module, a safety and authority management module and a real-time monitoring and auditing function module. Through a self-adaptive sparse auto-encoder and a dynamic clustering technology in the data cleaning and compression module, abnormal values in a bid evaluation expert database can be detected and cleaned, data compression is performed by adopting a self-adaptive dictionary coding algorithm, and the storage efficiency and query performance of the database are improved; based on a multi-modal information fusion and reinforcement learning method, accurate collection, dynamic updating and intelligent management of expert information are realized. The randomness and fairness of the bid evaluation expert extraction process are ensured by using a mode of combining deep reinforcement learning and a quantum random number generator in an extraction algorithm design module.

The invention relates to the technical field of data processing and information security, in particular to a thermal management model sharing method based on a block chain and homomorphic encryption. Creating a point account, completing user identity information registration and block account application, and applying for a corresponding block chain account for the user after basic identity information registration is completed; issuing the shared heat management model, namely completing the issuing of the user shared heat management model in the block chain and the storage function of the model in the IPFS; downloading the shared model, retrieving the thermal management model, and after the credit is paid to the model provider, downloading the model by the user; a user issues a thermal management model through a block chain system, other users retrieve the issued thermal management model in the system through a block chain intelligent contract, and the user needs to pay a certain amount of points to a sharing party, so that joint simulation of digital models in different subject fields and repeated use of the models can be realized; and the problem of multi-functional demand modeling of a complex system can be solved.

The invention relates to the field of artificial intelligence, and provides an agricultural product risk control method and system based on production and fusion combination, and the method comprises the steps: carrying out the block chain storage of financial risk assessment data, agricultural product risk assessment data and real-time agricultural data, and obtaining public production and fusion data; utilizing a pre-trained agricultural product risk assessment model to perform risk assessment operation based on yield, market and natural disasters on agricultural product risk assessment data in the public production and fusion data to obtain an agricultural product risk assessment result; utilizing a pre-trained agricultural product risk control model to perform risk control policy prediction operation on the agricultural product risk assessment result and financial risk assessment data in the public production and fusion data to obtain a policy scheme; and according to the insurance policy scheme, constructing an insurance relationship between the target agricultural area and the financial institution. According to the method, the integration and transparency of agricultural data and financial data are improved, and a risk management and control scheme for benefits of an agricultural party and a financial party is constructed.

The invention discloses a coordinated scheduling method and device for a multi-energy complementary system, and a storage medium. The method comprises the steps of obtaining pre-scheduling data of multiple historical periods and pre-scheduling data of a next period chained on multiple target nodes in the multi-energy complementary system from a block chain; wherein the pre-scheduling data is data obtained by predicting power supply and demand conditions of all subjects in the multi-energy complementary system in each time period by a plurality of target nodes by using respective prediction models; the plurality of target nodes comprise a photovoltaic node, a wind power node, a thermal power node, an energy storage node and a power grid electricity purchasing node; determining scheduling data of all main bodies in the multi-energy complementary system in the next time period based on the pre-scheduling data of the plurality of historical time periods and the pre-scheduling data of the next time period; and uploading the scheduling data to the block chain, and performing coordinated scheduling on the power resources of the plurality of target nodes according to the scheduling data in the next time period.

The invention discloses an anonymous weighted decision-making electronic voting method based on a block chain and homomorphic encryption, and belongs to the technical field of block chain application. The method comprises the steps that a voting initiator initializes a smart contract; a voter obtains the encrypted public parameter through the smart contract, and generates a homomorphic encryption key; the voters obtain homomorphic encryption public keys of all the voters in the system, and an encryption public key is calculated; encrypting the decision content by using the encryption public key, generating a non-interactive zero-knowledge proof for the encrypted decision content and signing to obtain a final vote, and storing the final vote on the block chain; the voter generates a secret share and uploads the secret share to the smart contract; the voting initiator and all voters obtain secret shares and all legal votes through the intelligent contract, and a final voting result is obtained through calculation; and when an abnormal voter does not upload the secret share, entering an abnormal recovery stage. According to the method, the anonymity problem of safe voting after the weight of the voter is introduced into a weighted decision scene is solved.

The application discloses a kind of AI training data copyright protection method and system based on block chain, the method includes: extracting semantic feature vector to art work generates digital fingerprint, with using permission policy together write into block chain;AI training party extracts training data feature vector, with on-chain digital fingerprint Similarity comparison, compliance proof is generated based on zero-knowledge proof and is submitted to block chain;Smart contract is inquired according to matching result work permission, it is judged whether authorization, and digital license certificate or rejection log is generated;After training, compliance report is generated by summarizing digital license certificate, and AI model is bound and stored in block chain.Therefore, using zero-knowledge proof technology, under the premise that original training data set content is not disclosed, the compliance proof that can be verified is submitted to chain.And through smart contract, license agreement is converted into tamper-proof code logic, ensure that each authorized record is open and transparent, traceable and automatically executed.

The invention relates to the technical field of federated learning and block chains, in particular to a federated learning incentive method and system based on two-stage commitment and a block chain. According to the technical scheme, the federal learning excitation method based on the two-stage commitment and the block chain comprises the following steps: a reputation evaluation step: dividing interaction behaviors of a client into three conditions of positive interaction, negative interaction and uncertain interaction according to a deviation degree between each round of uploading model updating and a global updating direction of the client, the reputation value of the client is calculated by adopting a subjective logic-based Bayesian reasoning method, and the influence of long-term interaction on the reputation is weakened by introducing a time decay mechanism. By introducing the block chain and the dual-stage commitment mechanism, it is ensured that the server cannot deduct the deserved rewards of the client without being found, the publicity, transparency and fairness of the incentive process are ensured, and the trust of each participant is maintained.

The present invention discloses a high-security access control method and system based on blockchain, the method comprising: registering a user through a certificate issuing authority in a blockchain alliance chain organization, setting attribute information of an access right level for the user, and the user having a unique user identification; the user initiates a resource access request, and the user is double-signed according to a double signature mechanism; the blockchain alliance chain performs double verification according to the double signature; after the double verification is passed, responding to the access request and allowing the user to access. The system consists of a blockchain user layer, a blockchain interface layer, a blockchain core layer, and a blockchain infrastructure layer. Through the invented method and system, the stability and security of access control can be improved, the flexibility and scalability of access control can be improved, and public auditability and security can also be enhanced.