6 results about "Entropy model" patented technology

An apparatus includes first and second circuitry, such as a first memory and a second memory. The first circuitry is configured to store compressed information representing a set of distribution functions associated with a set of entropy models. The second circuitry is configured to store mappings of requests for subsets of the set of distribution functions to one or more offsets in the first circuitry corresponding to the compressed information representing the subsets. The apparatus also includes circuitry that implements the set of entropy models. This circuitry is configured to perform entropy coding based on the subsets and a first entropy model selected from the set of entropy models. This circuitry can include one or more entropy engines that have a set of ports for encoding or decoding one or more streams of bits or symbols. Multiple streams can therefore be encoded or decoded concurrently or in parallel.

An apparatus includes first and second circuitry, such as a first memory and a second memory. The first circuitry is configured to store compressed information representing a set of distribution functions associated with a set of entropy models. The second circuitry is configured to store mappings of requests for subsets of the set of distribution functions to one or more offsets in the first circuitry corresponding to the compressed information representing the subsets. The apparatus also includes circuitry that implements the set of entropy models. This circuitry is configured to perform entropy coding based on the subsets and a first entropy model selected from the set of entropy models. This circuitry can include one or more entropy engines that have a set of ports for encoding or decoding one or more streams of bits or symbols. Multiple streams can therefore be encoded or decoded concurrently or in parallel.

The application discloses a kind of based on physical event anchoring and space-time decoupling's sea transport freight right fraud real-time blocking system, comprising: physical event four-dimensional tensor construction module: for building the physical event including space coordinates, time series, equipment signature and event type four-dimensional data tensor representation;Quantum fingerprint anchoring module: for generating anti-copy unique identification to physical event data by 12-bit quantum circuit;Helve space-time topology engine: for calculating the continuity score of the physical event of generating anti-copy unique identification;Three-level risk response execution module: for automatically triggering on-chain blocking operation according to physical event continuity score, three-level risk response is judged;Self-evolution risk control system: for dynamically optimizing rule weight and freight right entropy model by fraud mode clustering, generates the defense mechanism of triggering on-chain blocking operation.The system marks that international trade trust mechanism has entered the trend and possibility of new era of quantum level credibility.

This invention relates to the field of intelligent supervision and early warning management, proposing a work supervision and early warning management method and system based on multi-dimensional risk sources. A multi-dimensional risk entropy model is designed, and supervision and spot checks are conducted based on complex multi-dimensional risk data items. Through kernel density estimation of risk entropy calculation, dynamic spot check probability calculation, and cumulative probability stratified sampling, efficient extraction of high-risk items is achieved, while improving the coverage balance of sampling, reducing the time consumed in a single sampling, and improving the overall efficiency of supervision and spot checks. Furthermore, a multi-level fuzzy evaluation algorithm based on AHP-entropy weight combination is designed. Through AHP-entropy weight combination, the influence of subjective bias or data noise is avoided, and the weights are adaptively adjusted according to changes in data distribution, improving the accuracy and stability of early warning monitoring. This invention improves the efficiency and stability of work supervision and early warning management methods based on multi-dimensional risk sources.

The application discloses a cluster task capability evaluation method, device and system and a storage medium. The method proposes a cluster structure negative entropy model to describe the influence degree of a cluster static structure on cluster task capability. The correlation between single machine behavior decision and the cluster structure negative entropy model is considered, and then a cluster dynamic behavior negative entropy task capability evaluation model based on behavior decision is proposed to realize the purpose of evaluating cluster task capability. In view of the proposed cluster task capability measurement index, the application analyzes the influence factor sensitivity of the index from the angles of a cluster control structure, a cluster size, a task node ratio and a cluster link capability change, and verifies the correctness and accuracy of the index in describing the cluster task capability.

This invention provides a method, medium, and system for constructing a predictive model for suitable habitats of the peach aphid, belonging to the field of peach aphid prediction technology. This invention obtains peach aphid distribution points from the Global Biodiversity Information Facility and obtains an effective set of coordinate points through spatial filtering. It then selects bioclimatic variables from the WorldClim database and obtains an effective set of variables through variance inflation factor screening and principal component analysis. The above data is input into the model to output the suitability probability. The uncertainty of the multi-climate model set is then modeled as a continuous probability density field to generate a probability suitability map. Simultaneously, the suitability probability and the effective variable set are input into a maximum entropy model and combined with elastic network regularization to output a habitat suitability index. Finally, spatial cross-validation is used to evaluate the accuracy, and the suitability zone classification and spatiotemporal change identification are completed based on the Jenks natural discontinuity classification method. This invention solves the technical problem that climate uncertainty cannot be continuously propagated in AI-driven species suitability zone prediction.