CN114862233A - Intelligent decision method and intelligent decision system - Google Patents
Intelligent decision method and intelligent decision system Download PDFInfo
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- CN114862233A CN114862233A CN202210560891.0A CN202210560891A CN114862233A CN 114862233 A CN114862233 A CN 114862233A CN 202210560891 A CN202210560891 A CN 202210560891A CN 114862233 A CN114862233 A CN 114862233A
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Abstract
The invention relates to the technical field of artificial intelligence and discloses an intelligent decision method, which comprises the following steps: responding to user created operations, such as searching of decision results; responding to the operation created by the user, acquiring input information data to be created, and converting the input information data into information which can be understood by a computer and personnel; responding to the operation created by the user, and creating a decision index required by the user by using an inference machine and artificial expert inference based on the acquired input data information; responding to the operation created by the user, and performing comparative analysis based on the decision index created by the inference machine and the artificial expert inference so as to determine the optimal decision index; and responding to the operation created by the user, and displaying the optimal decision and the divergence result to the user based on the obtained optimal decision and divergence result. According to the invention, through adopting big data processing and manual detailed processing of the computer, the advantages of more detailed decision results given to the user through manual supply while decision results in a large direction can be absorbed by the computer.
Description
Technical Field
The invention relates to the technical field of artificial intelligence, in particular to an intelligent decision method and an intelligent decision system.
Background
Before decision making, information for decision making generally needs to be collected first, and as big data technologies are increasingly popularized nowadays, more and more information and more abundant forms can be used for decision making. This requires that the decision-making product support flexible and versatile data formats and good scalability. Decision products in the current stage are mostly limited by a rule-centered design idea, are poor in compatibility and adaptation to a machine learning model capable of processing complex long-tail variables, and are free from open sources, often far away from the actual requirements of customers, and need more development and maintenance costs. And because the decision-making product exists depending on the database, when there are information differences and errors in the database, the change can not be made, resulting in the fact that the final decision-making result is far from what the user needs, therefore the drawback is greater, and some already commercialized decision-making products are oriented to the specific business scene at first because of the design, cause the business attribute to couple seriously, can't become the decision-making product of universalization. In view of this, there is a need for an intelligent decision product that is more versatile, can adapt to complex and diverse service scenarios, and has higher decision accuracy and stability.
Disclosure of Invention
Technical problem to be solved
Aiming at the defects of the prior art, the invention provides an intelligent decision method and an intelligent decision system, which have the advantages of absorbing the decision result of a computer in a large direction and providing a user with a more detailed decision result through manual supply, and solve the problems that the existing decision products depend on a database, and can not be flexible when information difference and errors exist in the database, so that the finally obtained decision result is far from the requirement of the user, and the defect is large.
(II) technical scheme
In order to achieve the purpose that the invention absorbs the decision result of a computer in a large direction and simultaneously provides a decision structure for a user to carry out more refinement through manual work, the invention provides the following technical scheme: an intelligent decision method, comprising:
s1, responding to the operation created by the user, such as searching the decision result, according to the scene range defined by the user, thereby defining the input information operated by the user, and mapping the input information of the scene range with the information in the database
S2, responding to the operation created by the user, acquiring the input information data to be created, and looping the input information data into information that can be understood by the computer and the personnel, which is specifically: (1) converting information input by a user into digital information which can be understood by a computer according to a decision scene range defined by the user, (2) converting the information input by the user into character information which can be understood by a worker according to the decision scene range defined by the user;
s3, responding to the operation created by the user, and creating the decision index required by the user by using an inference machine and a manual expert inference based on the acquired input data information, wherein the operation is specifically as follows: (1) acquiring data from a model database management system, a method database management system and a knowledge base management system through an inference machine according to computer digital information converted from information input by a user, and screening out data required by the user to form a decision index obtained by a computer, (2) acquiring data from the model database management system, the method database management system and the knowledge base management system through manual expert inference according to character information of workers converted from the information input by the user, and screening out data required by the user to obtain the decision index obtained by a manual expert;
s4, responding to the operation created by the user, performing comparative analysis based on the decision index created by the inference engine and the artificial expert inference to determine the optimal decision index, performing comparative analysis on the decision index obtained by the computer and the artificial expert according to the information input by the user operation to obtain the overlapping performance and difference between the decision indexes of the computer and the artificial expert, and performing optimization analysis on the decision indexes obtained by the computer and the artificial expert to obtain the optimized decision index;
s5, responding to the operation created by the user, based on the obtained optimal decision and divergence result, all showing to the user, making the inference engine and artificial expert contrast information and optimal decision result transparent while giving the user the selection space, all showing the decision index obtained by the computer, the decision index obtained by the artificial expert, the optimal decision index obtained by the computer and artificial expert contrast and divergence result obtained by the computer and artificial expert decision index to the user, giving the user the self-selection, and simultaneously facilitating the user to carry out differentiation analysis on the decision index obtained by the computer and artificial expert
The invention also provides an intelligent decision-making system, which comprises a human-computer interaction interface and a natural language processing system, wherein the human-computer interaction interface and the natural language processing system are used for creating different decision-making scenes by a user and converting information input by the user into digital and literal information which can be understood by a computer and a human;
the problem processing system is used for identifying and analyzing problems, designing a solving scheme, calling resources such as data, models, methods, knowledge and the like in four libraries for solving the problems, and triggering an inference engine to make inference or new knowledge deduction on semi-structured or unstructured problems;
the model base management system, the database management system, the method base management system and the knowledge base management system are used for storing expert knowledge and experience which can not be represented by data or described by a model method, namely decision knowledge and experience knowledge of decision experts, and also comprises special knowledge of some specific problem fields.
Preferably, the problem processing system comprises an interpreter, a first comprehensive database, a second comprehensive database, a comparison system, an inference engine and an artificial expert reasoning, wherein the inference engine and the artificial expert reasoning are used for repeatedly matching rules in the knowledge base aiming at conditions or known information of a current problem to obtain a new conclusion so as to obtain a problem solving result, and the first comprehensive database and the second comprehensive database are specially used for storing original data, intermediate results and final conclusions required in the inference process of the inference engine and the artificial expert as temporary storage areas of decision indexes. The interpreter can explain the conclusion and the solving process according to the questions of the user, so that the solving process is more emotional.
(III) advantageous effects
Compared with the prior art, the invention provides an intelligent decision method and an intelligent decision system, which have the following beneficial effects:
the intelligent decision method and the intelligent decision system disclosed by the invention have the advantages that by adding the artificial module into the problem processing system, the comparison of the decision results of the artificial experts and the decision results of the computer can be carried out when the user puts forward different scene decision information, so as to carry out differentiation and overlapping analysis on the manual decision result and the computer decision result, further screening the decision results of workers and the decision results of a computer, thereby achieving a more optimized decision result, absorbing the decision result of the computer in a large direction and providing a user with a more detailed decision structure by manual work, thereby reducing the problem that the existing decision-making product can not be changed depending on the existence of a database, leading the finally obtained decision-making result to be far from the requirement of a user, therefore, the optimal decision effect of the decision product is closer to the selection of the user under the condition of larger defects.
Drawings
FIG. 1 is a block diagram of an intelligent decision making system of the present invention;
FIG. 2 is a block flow diagram of a problem handling system of the present invention;
FIG. 3 is a flow chart of an intelligent decision method according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The first embodiment is as follows:
referring to fig. 1-3, the intelligent decision method includes:
s1, responding to the operation created by the user, such as searching of decision results, according to the scene range defined by the user, thereby defining the input information operated by the user, and mapping the input information of the scene range with the information in the database;
s2, responding to the operation created by the user, acquiring the input information data to be created, and converting the data into information which can be understood by the computer and personnel, (1) converting the information input by the user into digital information which can be understood by the computer according to the decision scene range defined by the user, and (2) converting the information input by the user into character information which can be understood by the staff according to the decision scene range defined by the user;
s3, in response to the operation created by the user, based on the acquired input data information, using an inference engine and a human expert to infer and thereby create a decision index required by the user, (1) converting the input information into computer numerical information according to the user, the inference engine collects data from the model database management system, the method library management system and the knowledge library management system, screens out the data required by the user, so as to form decision index obtained by computer, (2) according to the worker's literal information converted from the information inputted by user, collecting data from a model database management system, a method library management system and a knowledge library management system through artificial expert reasoning, and screening out data required by a user so as to obtain a decision index obtained by an artificial expert;
s4, responding to the operation created by the user, performing comparative analysis based on the decision index created by the inference engine and the artificial expert inference to determine the optimal decision index, performing comparative analysis on the decision index obtained by the computer and the artificial expert according to the information input by the user operation to obtain the overlapping performance and difference between the decision indexes of the computer and the artificial expert, and performing optimization analysis on the decision indexes obtained by the computer and the artificial expert to obtain the optimized decision index;
s5, responding to the operation created by the user, displaying the optimal decision and the divergence result to the user based on the obtained optimal decision and the divergence result, enabling the inference engine and the artificial expert to compare information and the optimal decision result to be transparent while providing the user with a selection space, displaying the decision index obtained by the computer, the decision index obtained by the artificial expert, the optimal decision index obtained by the computer and the artificial expert and the divergence result obtained by the computer and the artificial expert, and providing the user with the decision index to be selected independently, and facilitating the user to carry out differentiation analysis on the decision index obtained by the computer and the artificial expert.
Example two:
referring to fig. 1-3, on the basis of the first embodiment, the intelligent decision method includes:
s1, responding to the operation created by the user, such as searching of decision results, according to the scene range defined by the user, thereby defining the input information operated by the user, and mapping the input information of the scene range with the information in the database;
s2, responding to the operation created by the user, acquiring the input information data to be created, and converting the data into information which can be understood by the computer and personnel, (1) converting the information input by the user into digital information which can be understood by the computer according to the decision scene range defined by the user, and (2) converting the information input by the user into character information which can be understood by the staff according to the decision scene range defined by the user;
s3, responding to the operation created by the user, creating the decision index required by the user by using an inference machine and artificial expert inference based on the acquired input data information, acquiring data from a model database management system, a method library management system and a knowledge library management system through the inference machine according to the computer digital information converted from the information input by the user, and screening out the data required by the user, thereby forming the decision index obtained by the computer;
s4, responding to the operation created by the user, displaying the decision result of the computer to the user based on the obtained decision result, enabling the decision result of the inference engine to be transparent while providing the user with a selection space, presenting the decision index obtained by the computer to the user, providing the user with the decision index for the user to select independently, and facilitating the user to carry out differential analysis on the decision index of the computer.
By comparing the first embodiment with the second embodiment, after the user specifically creates the decision input information, it can be known that, when a computer plus manual expert processing mode is adopted, the differentiation between the decision result and the result required by the user can be reduced, and a single computer decision processing mode can only provide the result in the large direction of the user decision, and cannot provide the user with a more accurate result of the required result.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (8)
1. An intelligent decision method, comprising:
s1: responding to user created operations, such as searching of decision results;
s2, responding to the operation created by the user, obtaining the input information data to be created, and converting the input information data into information which can be understood by the computer and the personnel;
s3: responding to the operation created by the user, and creating a decision index required by the user by using an inference machine and artificial expert inference based on the acquired input data information;
s4: responding to the operation created by the user, and performing comparative analysis based on the decision index created by the inference machine and the artificial expert inference so as to determine the optimal decision index;
s5: responding to the operation created by the user, and displaying the obtained optimal decision and the divergence result to the user, so that the inference engine and the artificial expert can compare information and the optimal decision result are transparent while giving the user a selection space.
2. The intelligent decision-making method according to claim 1, wherein the operation given to the user by S1 comprises the following specific steps:
according to the scene range defined by the user, the input information operated by the user is defined, and the input information of the scene range is mapped with the information in the database.
3. The intelligent decision-making method and system according to claim 1, wherein the step of S2 obtaining the input information data to be created comprises the following steps:
(1) converting the information input by the user into digital information which can be understood by a computer according to the decision scene range defined by the user;
(2) and converting the information input by the user into text information which can be understood by a worker according to the decision scene range defined by the user.
4. The intelligent decision-making method according to claim 1, wherein the step S3 of creating the decision index required by the user by using an inference engine and a human expert to infer based on the acquired input data information comprises the following steps:
(1) acquiring data from a model database management system, a method management system and a knowledge base management system through an inference machine according to computer digital information converted from information input by a user, and screening out data required by the user so as to form a decision index obtained by a computer;
(2) and acquiring data from the model database management system, the method database management system and the knowledge base management system through manual expert reasoning according to the character information of the working personnel converted from the information input by the user, and screening out the data required by the user so as to obtain a decision index obtained by the manual expert.
5. The intelligent decision-making method according to claim 1, wherein the step S4, in response to the operation created by the user, performs a comparative analysis based on the decision-making indicators created by the inference engine and the artificial expert inference, so as to determine the optimal decision-making indicator, comprises the following specific steps:
the decision indexes obtained by the computer and the artificial experts according to the information input by the user operation are compared and analyzed, so that the overlapping performance and the difference in the aspect of the decision indexes of the computer and the artificial experts are obtained, and the decision indexes obtained by the computer and the artificial experts are optimized and analyzed, so that the optimized decision index is obtained.
6. The intelligent decision method according to claim 1, wherein the S5 comprises the following steps based on the obtained optimal decision and branch result:
the decision index obtained by the computer, the decision index obtained by the artificial expert, the optimal decision index obtained by the comparison of the computer and the artificial expert and the divergence result obtained by the decision index obtained by the computer and the artificial expert are presented to the user, so that the user can independently select the optimal decision index and the divergence result obtained by the decision index obtained by the computer and the artificial expert, and the user can conveniently carry out differential analysis on the decision indexes obtained by the computer and the artificial expert.
7. The intelligent decision making system according to claim 1, comprising:
a human-computer interaction interface and a natural language processing system, which are used for creating different decision scenes by a user and converting information input by the user into digital and literal information which can be understood by a computer and a human;
the problem processing system is used for identifying and analyzing problems, designing a solving scheme, calling resources such as data, models, methods, knowledge and the like in four libraries for solving the problems, and triggering an inference engine to make inference or new knowledge deduction on semi-structured or unstructured problems;
the model base management system, the database management system, the method base management system and the knowledge base management system are used for storing expert knowledge and experience which can not be represented by data or described by a model method, namely decision knowledge and experience knowledge of decision experts, and also comprises special knowledge of some specific problem fields.
8. The intelligent decision method and system according to claim 7, wherein: the problem processing system comprises an interpreter, a first comprehensive database, a second comprehensive database, a comparison system, an inference engine and an artificial expert reasoning system, wherein the inference engine and the artificial expert reasoning system are used for repeatedly matching rules in a knowledge base aiming at conditions or known information of a current problem to obtain a new conclusion so as to obtain a problem solving result, and the first comprehensive database and the second comprehensive database are specially used for storing original data, intermediate results and final conclusions required in the inference process of the inference engine and the artificial expert as temporary storage areas of decision indexes. The interpreter can explain the conclusion and the solving process according to the questions of the user, so that the solving process is more emotional.
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| CN117290462A (en) * | 2023-11-27 | 2023-12-26 | 北京滴普科技有限公司 | Intelligent decision system and method for large data model |
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| CN117290462A (en) * | 2023-11-27 | 2023-12-26 | 北京滴普科技有限公司 | Intelligent decision system and method for large data model |
| CN117290462B (en) * | 2023-11-27 | 2024-04-05 | 北京滴普科技有限公司 | Intelligent decision system and method for large data model |
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