CN111144695A - Intelligent commanding and scheduling brain method and system - Google Patents
Intelligent commanding and scheduling brain method and system Download PDFInfo
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Abstract
A method for intelligently commanding and scheduling a brain, comprising: s101, establishing a comprehensive situation by collecting, sorting and analyzing potential information of an emergency, an environment entity and a resource entity, and by utilizing a corresponding industry field knowledge map and a multi-source heterogeneous situation generation technology; s102, discovering an event target through a potential event intelligent discovery technology according to the comprehensive situation; s103, intelligently grading the event targets through an event target intelligent matching technology according to event constraint conditions and evaluation criteria, and determining corresponding action scheme decision preference; s104, generating a corresponding action scheme through an action scheme intelligent planning technology according to the decision preference; and S105, converting the action scheme into an instruction, issuing the action instruction by using an instruction real-time distribution technology, and monitoring and responding to the field entity to execute the related action. The invention can realize integrated and intelligent command and scheduling.
Description
Technical Field
The invention belongs to the technical field of intelligent command and scheduling, and particularly relates to a brain method and system for intelligent command and scheduling.
Background
In recent years, along with the deepening of urbanization construction, the contradiction between a public resource supply side and a public resource demand side is gradually intensified in a highly concentrated population, the problems of traffic jam, environmental pollution, security violation, difficulty in handling common people and the like in the urban treatment process are solved, so that the life of urban people is more happy, and many cities such as Hangzhou, Shanghai, Beijing, Guangzhou and the like start related projects similar to a 'city-wide brain', but the calling laws of people are different, such as the city brain, the city cloud brain, the city super brain, the city neural network and the like.
The core of the current 'urban brain' is to solve the resource optimization and management scheduling problems in the contradiction between supply and demand of cities through new-generation information technologies such as cloud computing, big data, artificial intelligence, Internet of things and the like, so that the social disorder interaction of entropy increment gradually moves to the order and harmony ecology of entropy reduction, which is the core content of intelligent command scheduling research.
According to the management activities proposed by an economic scientist Henry Fa praised as the father of modern management and management, the management system is composed of planning, organizing, commanding, coordinating and controlling. The command scheduling is to organically integrate different, mutually complementary, mutually independent and relatively independent command elements, execution force and related resources through fusion management and technology, so as to improve the working efficiency of city management and realize the goal of comprehensive city management.
The intelligent command and dispatch is a new stage of command and dispatch development, and the integration and the intellectualization are emphasized.
Disclosure of Invention
Based on the above technical problem, a method and a system for intelligently commanding and scheduling a brain are provided.
In order to solve the technical problems, the invention adopts the following technical scheme:
a method for intelligently commanding and scheduling a brain, comprising:
s101, establishing a comprehensive situation by collecting, sorting and analyzing potential information of an emergency, an environment entity and a resource entity, utilizing a corresponding industry field knowledge map and a multi-source heterogeneous situation generation technology;
s102, discovering an event target through a potential event intelligent discovery technology according to the comprehensive situation;
s103, intelligently grading the event targets through an event target intelligent matching technology according to event constraint conditions and evaluation criteria, and determining corresponding action scheme decision preference;
s104, generating a corresponding action scheme through an action scheme intelligent planning technology according to the decision preference;
and S105, converting the action scheme into an instruction, issuing the action instruction by using an instruction real-time distribution technology, and monitoring and responding to the field entity to execute the related action.
The method further includes feeding back the execution status information fed back by the field entity to step S104, and readjusting the action scheme.
The intelligent planning technology of the action scheme adopts an intelligent planning method of the action scheme based on HTN, or an intelligent planning method of the action scheme based on Bayesian network, or an intelligent planning method of the action scheme based on deep reinforcement learning.
The scheme also relates to an intelligent command and dispatch brain system which comprises a knowledge system, a situation system, an event system, a scheme system and an execution system;
the knowledge system forms an industry domain knowledge graph;
the situation system utilizes an industry field knowledge graph to construct a comprehensive situation by collecting, sorting and analyzing potential information of an emergency, an environment entity and a resource entity, and utilizes a corresponding industry field knowledge graph and a multi-source heterogeneous situation generation technology;
the event system discovers an event target through a potential event intelligent discovery technology according to the comprehensive situation; according to the event constraint conditions and the evaluation criteria, the event targets are intelligently graded through an event target intelligent matching technology, and corresponding action scheme decision preference is determined;
the scheme system generates a corresponding action scheme through an action scheme intelligent planning technology according to the decision preference;
the execution system converts the action scheme into instructions, issues action instructions by using an instruction real-time distribution technology, and simultaneously monitors and responds to the field entities to execute relevant actions.
And the execution system feeds back the execution condition information fed back by the field entity to the scheme system, and the scheme system readjusts the action scheme.
The intelligent planning technology of the action scheme adopts an intelligent planning method of the action scheme based on HTN, or an intelligent planning method of the action scheme based on Bayesian network, or an intelligent planning method of the action scheme based on deep reinforcement learning.
The invention can realize integrated and intelligent command and scheduling.
Drawings
The invention is described in detail below with reference to the following figures and detailed description:
FIG. 1 is a flow chart of an embodiment of the present invention.
Detailed Description
As shown in fig. 1, a brain method for intelligent command and dispatch includes:
s101, establishing a comprehensive situation by collecting, sorting and analyzing potential information of an emergency, an environment entity and a resource entity, and by utilizing a corresponding industry field knowledge map and a multi-source heterogeneous situation generation technology.
Wherein, the emergency generally refers to a similar robbery event, a fraud event, a dispute event, a disaster event, etc., and generally includes information such as location, degree, scale and complexity; the environmental entity refers to the environmental state of the scene of the emergency, such as the road, the building, the traffic, the personnel, the weather, the accessory key units, and the like, and generally comprises the position, the scale, the current state, and the like; resource entities, and potentially information, refer to resources other than those mentioned above, such as disposal personnel, supplies, vehicles, guns, communication resources, and the like, typically including location, quantity, and current status.
The multi-source heterogeneous situation generation technology can adopt a multi-source heterogeneous information real-time fusion technology, a situation target tracking technology or a mass data rarefying and graph plotting technology.
And S102, discovering the event target through a potential event intelligent discovery technology according to the comprehensive situation.
The discovery of the event target refers to the discovery of the forming event through the characteristics formed by the event, and the event target refers to the target or object which needs to be completed for handling the event, and has specificity, scalability, rationality, time correlation and the like.
The latent event intelligent discovery technology can adopt Bayesian inference technology or deep neural network technology based on supervised learning.
S103, intelligently grading the event targets through an event target intelligent matching technology according to the event constraint conditions and the evaluation criteria, and determining corresponding action scheme decision preference.
The event constraint conditions and the evaluation criteria are preset manually, for example, the evaluation criteria of a certain emergency event: 1) the life safety is ensured, and casualties are reduced; 2) the emergency situation is stabilized, and the event deterioration is prevented; 3) the environmental pollution is reduced; 4) the above criteria are met simultaneously.
The intelligent grading refers to the step number of the event determined by intelligent matching of technical conditions, for example, the emergency response grades are divided into I, II, III and IV grades according to controllability, severity and influence range.
The final result of the decision preference is the evaluation criterion as described above.
The event target intelligent matching technique can adopt an expert system, Bayesian reasoning or a neural network.
And S104, generating a corresponding action scheme through an action scheme intelligent planning technology according to the decision preference.
The intelligent planning technology of the action scheme adopts an intelligent planning method of the action scheme based on HTN, or an intelligent planning method of the action scheme based on Bayesian network, or an intelligent planning method of the action scheme based on deep reinforcement learning.
And S105, converting the action scheme into an instruction, issuing the action instruction by using an instruction real-time distribution technology, and monitoring and responding to the field entity to execute the related action.
The field entities generally refer to field dispositioners, vehicles, robots, signal lights, inductive screens, and various intelligent terminals.
The real-time instruction distribution technique may employ a distributed real-time message processing technique.
Preferably, the present invention further includes step S106, feeding back the execution status information fed back by the field entity to step S104, and readjusting the action plan.
The invention can realize integrated and intelligent command and scheduling.
The scheme also relates to an intelligent command and dispatch brain system which consists of five systems, namely a knowledge system, a situation system, an event system, a scheme system and an execution system.
The knowledge system forms an industry domain knowledge graph.
The situation system utilizes the industry field knowledge graph to build a comprehensive situation by collecting, sorting and analyzing potential information of emergency, environment entities and resource entities, and utilizes the corresponding industry field knowledge graph and a multi-source heterogeneous situation generation technology.
Wherein, the emergency generally refers to a similar robbery event, a fraud event, a dispute event, a disaster event, etc., and generally includes information such as location, degree, scale and complexity; the environmental entity refers to the environmental state of the scene of the emergency, such as the road, the building, the traffic, the personnel, the weather, the accessory key units, and the like, and generally comprises the position, the scale, the current state, and the like; resource entities, and potentially information, refer to resources other than those mentioned above, such as disposal personnel, supplies, vehicles, guns, communication resources, and the like, typically including location, quantity, and current status.
The multi-source heterogeneous situation generation technology can adopt a multi-source heterogeneous information real-time fusion technology, a situation target tracking technology or a mass data rarefying and graph plotting technology.
The event system discovers an event target through a potential event intelligent discovery technology according to the comprehensive situation; and intelligently grading the event targets through an event target intelligent matching technology according to the event constraint conditions and the evaluation criteria, and determining corresponding action scheme decision preference.
The discovery of the event target refers to the discovery of the forming event through the characteristics formed by the event, and the event target refers to the target or object which needs to be completed for handling the event, and has specificity, scalability, rationality, time correlation and the like.
The latent event intelligent discovery technology can adopt Bayesian inference technology or deep neural network technology based on supervised learning.
The event constraint conditions and the evaluation criteria are preset manually, for example, the evaluation criteria of a certain emergency event: 1) the life safety is ensured, and casualties are reduced; 2) the emergency situation is stabilized, and the event deterioration is prevented; 3) the environmental pollution is reduced; 4) the above criteria are met simultaneously.
The intelligent grading refers to the step number of the event determined by intelligent matching of technical conditions, for example, the emergency response grades are divided into I, II, III and IV grades according to controllability, severity and influence range.
The final result of the decision preference is the evaluation criterion as described above.
The event target intelligent matching technique can adopt an expert system, Bayesian reasoning or a neural network.
And the scheme system generates a corresponding action scheme through an action scheme intelligent planning technology according to the decision preference.
The intelligent planning technology of the action scheme adopts an intelligent planning method of the action scheme based on HTN, or an intelligent planning method of the action scheme based on Bayesian network, or an intelligent planning method of the action scheme based on deep reinforcement learning.
The execution system converts the action scheme into an instruction, issues the action instruction by using an instruction real-time distribution technology, and simultaneously monitors and responds to the field entity to execute the related action.
The field entities generally refer to field disposers, vehicles, robots, signal lamps, guidance screens and various intelligent terminals.
The real-time instruction distribution technique may employ a distributed real-time message processing technique.
Preferably, the execution system feeds back the execution situation information fed back by the field entity to the scheme system, and the scheme system readjusts the action scheme.
The invention can realize integrated and intelligent command and scheduling.
However, those skilled in the art should realize that the above embodiments are illustrative only and not limiting to the present invention, and that changes and modifications to the above described embodiments are intended to fall within the scope of the appended claims, as long as they fall within the true spirit of the present invention.
Claims (6)
1. A brain method for intelligent command and scheduling is characterized by comprising the following steps:
s101, establishing a comprehensive situation by collecting, sorting and analyzing potential information of an emergency, an environment entity and a resource entity, and by utilizing a corresponding industry field knowledge map and a multi-source heterogeneous situation generation technology;
s102, discovering an event target through a potential event intelligent discovery technology according to the comprehensive situation;
s103, intelligently grading the event targets through an event target intelligent matching technology according to event constraint conditions and evaluation criteria, and determining corresponding action scheme decision preference;
s104, generating a corresponding action scheme through an action scheme intelligent planning technology according to the decision preference;
and S105, converting the action scheme into an instruction, issuing the action instruction by using an instruction real-time distribution technology, and monitoring and responding to the field entity to execute the related action.
2. The brain method for intelligent command and dispatch of claim 1, further comprising feeding back the performance information fed back by the field entity to step S104 to readjust the action plan.
3. The brain method for intelligent command and dispatch according to claim 1 or 2, wherein the intelligent planning technique for action plan adopts an intelligent planning method for action plan based on HTN, or an intelligent planning method for action plan based on Bayesian network, or an intelligent planning method for action plan based on deep reinforcement learning.
4. An intelligent command and dispatch brain system is characterized by comprising a knowledge system, a situation system, an event system, a scheme system and an execution system;
the knowledge system forms an industry domain knowledge graph;
the situation system utilizes an industry field knowledge graph to construct a comprehensive situation by collecting, sorting and analyzing potential information of an emergency, an environment entity and a resource entity, utilizing the corresponding industry field knowledge graph and utilizing a multi-source heterogeneous situation generation technology;
the event system discovers an event target through a potential event intelligent discovery technology according to the comprehensive situation; according to the event constraint conditions and the evaluation criteria, the event targets are intelligently graded through an event target intelligent matching technology, and corresponding action scheme decision preference is determined;
the scheme system generates a corresponding action scheme through an action scheme intelligent planning technology according to the decision preference;
the execution system converts the action scheme into instructions, issues action instructions by using an instruction real-time distribution technology, and simultaneously monitors and responds to the field entities to execute relevant actions.
5. The brain system for intelligent command and dispatch of claim 4, wherein the executive system feeds back executive status information fed back by the field entities to the project system, and the project system readjusts the action project.
6. The brain system for intelligent command and dispatch according to claim 4 or 5, wherein the intelligent planning technique for action plan is based on HTN intelligent planning method or Bayesian network intelligent planning method or deep reinforcement learning intelligent planning method.
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