A Method of Medical Information Service Selection Based on Hybrid Optimal Algorithm
A technology for medical information and optimization algorithms, applied in the fields of medical informatization and artificial intelligence
Active Publication Date: 2021-06-01
SHAN DONG MSUN HEALTH TECH GRP CO LTD
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[0004] The invention provides a medical information service selection method based on a hybrid optimization algorithm, through the analysis of medical information services, using artificial intelligence technology to solve the problem of medical information service combination, and proposes a medical information service selection method based on a hybrid optimization algorithm
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[0041] Attached below Figure 1-2 The present invention will be further described.
[0042] 1. Extract the multi-dimensional attributes of medical information services, including service quality attributes and transaction attributes. Quality of Service (QoS) attributes are composed of some non-functional attributes, including service price, service response time, service availability and service reliability. The transaction attributes of services mainly include the following categories: compensable transaction attribute c, retryable transaction attribute r, hub transaction attribute p, and compensable and retryable transaction attribute cr.
[0043] Sets probabilistic priorities for transactional attributes of services. The priority is dynamically changed according to the change of the candidate service. (1) If the transaction attribute of service i is c, its alternative candidate service transaction attribute is c or cr. If the number of services whose attribute is c is h...
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A medical information service selection method based on hybrid optimization algorithm. Through the above methods, the multi-dimensional attributes of medical information services are extracted, and a model that meets the concurrent needs of users and multi-granularity is established. Compared with the existing models, this model considers the transaction properties of medical information services, and designs a probability-based adaptive priority. A multi-granularity recursive decomposition method is used to obtain the combination scheme. The hybrid optimization algorithm is used to solve the service selection problem, and the particle encoding method is mainly designed, which combines the particle swarm, the cross-mutation operator with priority and the simulated annealing method to obtain the optimal service. Among them, the crossover mutation operator with priority can avoid solutions that do not conform to transaction attributes, the particle swarm optimization algorithm can achieve fast global search, and the simulated annealing method can avoid falling into local optimal solutions. Different methods complement each other and learn from each other to obtain the optimal solution. Effect.
Description
technical field [0001] The invention relates to the field of medical information technology and the field of artificial intelligence technology, and designs a method for selecting medical information services based on a hybrid optimization algorithm. Background technique [0002] With the development of informatization in the medical industry and the introduction of the idea of "everything is a service", service-oriented computing and cloud computing have become mainstream computing models. Service-oriented computing is a computing method that uses services as the basic components to construct distributed software systems by combining technologies. Service composition is the main means to realize the integration of service resources in service-oriented architecture, which can synthesize related services scattered on the network into a large-grained and more usable service. When users choose services, they not only put forward functional constraints on the combined service...
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IPC IPC(8): G06Q10/04G16H40/20G06N3/00
CPCG06N3/006G06Q10/04G16H40/20
Inventor 樊昭磊吴军杨万春张伯政李涛
Owner SHAN DONG MSUN HEALTH TECH GRP CO LTD