CN113515950A - Natural language processing semantic analysis method suitable for intelligent power dispatching - Google Patents
Natural language processing semantic analysis method suitable for intelligent power dispatching Download PDFInfo
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Abstract
The invention discloses a natural language processing semantic analysis method suitable for intelligent power dispatching, which comprises the steps that an intelligent agent sends an operation instruction to an operator according to information on an operation ticket; the operator receives the operation instruction, operates according to the operation instruction and sends operation information back to the intelligent seat; the intelligent seat analyzes the instruction on the original operation ticket and the received back instruction of the operator; and performing semantic comparison on the two instructions, and storing the passed instructions in a working log in a fixed format. The invention provides a method for processing according to natural language, which analyzes the part of speech of an operation order and a return instruction of a worker, divides the part of speech into importance levels, judges whether the parts of speech are the same on the importance level, does not need to ensure that the original instruction is completely consistent with the manual return instruction, can ensure that 1 operation instruction corresponds to a plurality of manual return instructions, greatly improves the scheduling efficiency and reduces the working pressure of the scheduling worker.
Description
Technical Field
The invention belongs to the technical field of information processing in the power field, and particularly relates to a natural language processing semantic analysis method suitable for power intelligent scheduling.
Background
Along with the continuous improvement of the automation and the intelligent degree of the society in China in recent years, the application of artificial intelligence is continuously developed in the field of electric power systems, the work with higher repeatability is replaced by the artificial intelligence, the working efficiency can be increased, and the working pressure can be reduced.
The natural language processing is related to the semantic analysis and matching process, the key of the natural language processing is that a computer 'understands' the natural language which we say, the computer has more similar understanding on an operation order instruction rather than the understanding of staying in a character string, the natural language processing can perform operations such as word segmentation, part of speech analysis and dependency relationship analysis on sentences, and then positioning words in the sentences according to the part of speech to analyze and compare and finally determine whether the semantics of the two sentences are consistent.
Disclosure of Invention
This section is for the purpose of summarizing some aspects of embodiments of the invention and to briefly introduce some preferred embodiments. In this section, as well as in the abstract and the title of the invention of this application, simplifications or omissions may be made to avoid obscuring the purpose of the section, the abstract and the title, and such simplifications or omissions are not intended to limit the scope of the invention.
The present invention has been made in view of the above-mentioned problems occurring in the conventional scheduling systems.
Therefore, the technical problem solved by the invention is as follows: the traditional intelligent agent can not judge whether the operation order is consistent with the return instruction, operation errors can be caused when the two instructions are inconsistent, the traditional agent does not have the knowledge of an image to the operation order, when the instructions are compared, two instructions can be judged to be the same no matter punctuation marks or characters are completely consistent, the universality of the use of the traditional agent is poor, and the consumed time is long.
In order to solve the technical problems, the invention provides the following technical scheme: the intelligent seat sends an operation instruction to an operator according to the information on the operation ticket; the operator receives the operation instruction, operates according to the operation instruction and sends operation information back to the intelligent seat; the intelligent seat analyzes the instruction on the original operation ticket and the received back instruction of the operator; and performing semantic comparison on the two instructions, and storing the passed instructions in a working log in a fixed format.
As an optimal scheme of the natural language processing semantic analysis method applicable to the intelligent power scheduling, the method comprises the following steps: the intelligent seat carries out preliminary semantic analysis on the operation order before sending the operation order to an operator according to the information on the operation order, and the analysis object comprises: word segmentation and part-of-speech analysis.
As an optimal scheme of the natural language processing semantic analysis method applicable to the intelligent power scheduling, the method comprises the following steps: the intelligent agent analyzes the return instruction of the operator, and the preliminary semantic analysis is carried out on the return instruction.
As an optimal scheme of the natural language processing semantic analysis method applicable to the intelligent power scheduling, the method comprises the following steps: the part-of-speech analysis comprises the steps of establishing a corresponding alphabet list of letters and parts-of-speech, dividing words of the operation instruction ticket and marking the parts-of-speech during semantic analysis, wherein the corresponding alphabet list comprises letters such as 'VV', 'CD', 'NN' and 'NR', and the letters respectively represent 'other verbs', 'numbers', 'common nouns' and 'proper nouns'.
As an optimal scheme of the natural language processing semantic analysis method applicable to the intelligent power scheduling, the method comprises the following steps: the intelligent agent analyzes the instruction on the original operation order and the received return instruction of the operator, and the intelligent agent compares the instruction on the original operation order with the words in the received return instruction of the operator one by one according to the words corresponding to the parts of speech and the priorities of different parts of speech and the priorities of the parts of speech.
As an optimal scheme of the natural language processing semantic analysis method applicable to the intelligent power scheduling, the method comprises the following steps: the priorities of different parts of speech include that verbs are of a first importance level, proper nouns are of a second importance level, and numbers are of a third importance level.
As an optimal scheme of the natural language processing semantic analysis method applicable to the intelligent power scheduling, the method comprises the following steps: the preliminary semantic analysis comprises that the preliminary semantic analysis consists of 10 corpora, including "as, cityu, cnc, ctb, msr, pku, sxu, udc, wtb, zx", and different corpora can generate different effects when carrying out word segmentation.
As an optimal scheme of the natural language processing semantic analysis method applicable to the intelligent power scheduling, the method comprises the following steps: the passing instruction comprises the step of comparing the operation order with the returned instruction according to the part of speech, and when the words of the first, second and third importance levels in the instruction are consistent, the instruction is judged to be a passing instruction.
The invention has the beneficial effects that: the invention provides a method for processing according to natural language, which analyzes the part of speech of an operation order and a return instruction of a worker, divides the part of speech into importance levels, judges whether the parts of speech are the same on the importance level, does not need to ensure that the original instruction is completely consistent with the manual return instruction, can ensure that 1 operation instruction corresponds to a plurality of manual return instructions, greatly improves the scheduling efficiency and reduces the working pressure of the scheduling worker.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise. Wherein:
fig. 1 is a schematic basic flow chart of a natural language processing semantic analysis method suitable for intelligent power scheduling according to a first embodiment of the present invention;
fig. 2 is a basic flowchart of a natural language processing semantic analysis method suitable for power intelligent scheduling according to a first embodiment of the present invention.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, specific embodiments accompanied with figures are described in detail below, and it is apparent that the described embodiments are a part of the embodiments of the present invention, not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making creative efforts based on the embodiments of the present invention, shall fall within the protection scope of the present invention.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, but the present invention may be practiced in other ways than those specifically described and will be readily apparent to those of ordinary skill in the art without departing from the spirit of the present invention, and therefore the present invention is not limited to the specific embodiments disclosed below.
Furthermore, reference herein to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one implementation of the invention. The appearances of the phrase "in one embodiment" in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments.
The present invention will be described in detail with reference to the drawings, wherein the cross-sectional views illustrating the structure of the device are not enlarged partially in general scale for convenience of illustration, and the drawings are only exemplary and should not be construed as limiting the scope of the present invention. In addition, the three-dimensional dimensions of length, width and depth should be included in the actual fabrication.
Meanwhile, in the description of the present invention, it should be noted that the terms "upper, lower, inner and outer" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are only for convenience of describing the present invention and simplifying the description, but do not indicate or imply that the referred device or element must have a specific orientation, be constructed in a specific orientation and operate, and thus, cannot be construed as limiting the present invention. Furthermore, the terms first, second, or third are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
The terms "mounted, connected and connected" in the present invention are to be understood broadly, unless otherwise explicitly specified or limited, for example: can be fixedly connected, detachably connected or integrally connected; they may be mechanically, electrically, or directly connected, or indirectly connected through intervening media, or may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
Example 1
Referring to fig. 1, for an embodiment of the present invention, a natural language processing semantic analysis method suitable for power intelligent scheduling is provided, including:
s1: and the intelligent seat sends an operation instruction to an operator according to the information on the operation ticket. In which it is to be noted that,
the manual intelligent scheduling seat is used for automatically generating an operation ticket and sending a text operation instruction to an operator, so that the work of a dispatcher can be replaced to a certain extent, and the burden of the dispatcher is reduced.
Further, before sending an operation instruction to an operator, preliminary semantic analysis needs to be performed on the operation order, and the analysis objects include: the term, part of speech analysis and others are respectively marked as 1, 2 and 3, when 1 is selected, only the term operation is performed on the operation instruction, in this embodiment, as an example, a "place is closed to a10 kV cloud-radix-line-radix-branch 24-pole a10 switch'", when the term function is selected, referring to fig. 2, when semantic analysis is performed, the terms of the operation instruction ticket are divided and part of speech is labeled according to the established alphabet corresponding to the letter and part of speech, and the obtained analysis result is: "[ 'on', '10', 'kV', 'scutellaria line', 'tai-ash', 'branch', '24', 'sign', 'rod', 'a10', 'switch' ]; if 2 is selected, the part-of-speech analysis function pops up "[ ' on ', ' VV ' ], [ '10', ' CD ', [ ' kV ', ' NN ', ' NOI ', [ ' clouds line ', ' NR ', ] too much ', ' NR ', [ ' branch ', ' NN ', '24', ' CD ', (' number ', ' M '), (' pole ', ' NOI '), [ ' a10', ' NN ', ' switch ', ' NN ' ]", wherein letters "VV", "CD", "NN" and "NR" indicate the part of speech of the word, respectively "other", "number", "verb", "general noun" and "proper noun", and the function 2 is selected by default in general for part-of-speech analysis, and a better effect can be obtained by switching the function flexibly according to the actual situation.
S2: and the operator receives the operation instruction, operates according to the operation instruction and sends operation information back to the intelligent seat. In which it is to be noted that,
and the operator receives the operation instruction sent by the intelligent seat, operates according to the instruction, and sends a return instruction to the intelligent seat according to the operation instruction and the action of the operator.
Furthermore, the intelligent agent performs preliminary semantic analysis on the returned instruction, and the selection of the analysis object is consistent with the operation instruction.
S3: and the intelligent seat analyzes the instruction on the original operation order and the received back instruction of the operator. In which it is to be noted that,
and comparing the command on the original operation ticket with the received words in the command sent back by the operator one by one according to the words corresponding to the parts of speech and the priorities of different parts of speech.
Further, the priorities of different parts of speech include that verbs are of a first importance level, proper nouns are of a second importance level, and numbers are of a third importance level, such as verbs "open" and "close", proper nouns "cloud line", numbers: the device number/number, e.g. "24" in "24-pole" and "110" in "110 kV" represents the voltage magnitude and device number, respectively.
S4: and performing semantic comparison on the two instructions, and storing the passed instructions in a working log in a fixed format. In which it is to be noted that,
and comparing the part of speech of the operation order instruction with that of the return instruction, and judging that the operation order passes the instruction when the words of the first, second and third importance levels in the instruction are consistent.
The state conversion purpose of the equipment, various parameters of the power grid and the operation instructions divided according to the part of speech and the dependency relationship are stored in the power dispatching work log, and the operation corresponding to the state conversion of various equipment is stored in the work log along with the accumulation of time, so that the intelligent dispatching agent has more similar knowledge on the operation instructions, and more excellent and more convenient data are provided for the automatic generation of the operation tickets of the subsequent intelligent power dispatching agent.
Further, in performing the preliminary semantic analysis, the preliminary semantic analysis is composed of 10 corpora including "as, cityu, cnc, ctb, msr, pku, sxu, udc, wtb, zx", different corpora may have different effects when performing the segmentation, for example, performing two different segmentation styles on "on 10kV cloud line and 24 size rod a10 switch" may result in "[" on ', "10'," kV ', "cloud line'," too much ', "branch'," 24', "sign'," rod ', "a 10'," switch '] "and" [ "on'," 10', "k'," V ', "cloud'," line ', "too much'," cloud ', "24'," rod '10', "switch ']", and "kV', etc. because of the two different segmentation styles, when the corpus of cnc is analyzed, the word segmentation granularity is fine, and the method is suitable for occasions with high precision requirements.
Example 2
Referring to another embodiment of the present invention, in order to verify and explain the technical effects adopted in the method, the present embodiment adopts the traditional dialing telephone propagation operation order and the traditional scheduling seat to perform a comparison test with the method of the present invention, and compares the test results by means of scientific demonstration to verify the real effect of the method.
Traditional phone call propagates operation ticket, needs the scheduling personnel shift to the scheduling personnel need artifical rephrase 4 times with operating personnel just can ensure the operation content errorless, and work efficiency is lower, consumes a large amount of manpowers, and traditional dispatch seat is operating the dispatch, when carrying out operation ticket instruction contrast, needs to compare each word, and only when all be the same in each aspect, just can confirm for passing, and the accuracy of its judgement is lower.
In order to verify the beneficial effects of the invention, 500 original operation order instructions are randomly extracted from a database to carry out experiments on three methods, when the experiments are carried out, firstly, the operation order instructions are provided for operators in a mode of dialing a telephone, after the operators complete the instruction operation, a deployment staff manually confirms the operators for 4 times, the accuracy of receiving the instructions is ensured, the final reply information of 500 operators is recorded, the 500 original operation order instructions and 500 reply information are used as the experimental data of the traditional scheduling seat and the method of the invention, the analysis accuracy of the traditional scheduling seat and the traditional scheduling seat is judged, and the experimental results are shown in the following table 1:
table 1: and analyzing and comparing results of the operation tickets.
As can be seen from the table, compared with the traditional method, the method of the invention is obviously shorter than the traditional method for transmitting the operation order by telephone in time, the analysis accuracy is obviously higher than that of the traditional scheduling seat, and the analysis accuracy is basically close to that of the method for transmitting the operation order by telephone, thereby meeting the requirement of daily work, saving a large amount of manpower and time and having higher use value.
It should be noted that the above-mentioned embodiments are only for illustrating the technical solutions of the present invention and not for limiting, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, which should be covered by the claims of the present invention.
Claims (8)
1. A natural language processing semantic analysis method suitable for intelligent power scheduling is characterized by comprising the following steps:
the intelligent seat sends an operation instruction to an operator according to the information on the operation ticket;
the operator receives the operation instruction, operates according to the operation instruction and sends operation information back to the intelligent seat;
the intelligent seat analyzes the instruction on the original operation ticket and the received back instruction of the operator;
and performing semantic comparison on the two instructions, and storing the passed instructions in a working log in a fixed format.
2. The natural language processing semantic analysis method suitable for intelligent power scheduling of claim 1, wherein: the intelligent seat sends an operation instruction to an operator according to the information on the operation order,
performing preliminary semantic analysis on the operation order, wherein the analysis object comprises: word segmentation and part-of-speech analysis.
3. The natural language processing semantic analysis method suitable for intelligent power scheduling of claim 2, wherein: the return instructions of the intelligent agent analysis operator comprise,
and performing the preliminary semantic analysis on the sent-back instruction.
4. The natural language processing semantic analysis method suitable for power intelligent scheduling according to claim 2 or 3, characterized by comprising the following steps: the part-of-speech analysis includes,
establishing a corresponding alphabet list of letters and parts of speech, dividing words of the operation instruction ticket and marking the parts of speech when performing semantic analysis, wherein the corresponding alphabet list comprises letters such as ' VV ', ' CD ', ' NN ' and ' NR ', and the letters represent ' other verbs ', ' numbers ', ' common nouns ' and ' proper nouns respectively.
5. The natural language processing semantic analysis method suitable for intelligent power dispatching as claimed in any one of claims 1 to 3, wherein the method comprises the following steps: the intelligent seat analyzes the instructions on the original operation order and receives the returned instructions of the operator,
and comparing the command on the original operation order with the received words in the returned command of the operator one by one according to the words corresponding to the parts of speech and the priorities of different parts of speech.
6. The natural language processing semantic analysis method suitable for intelligent power scheduling of claim 5, wherein: the priority of the different parts of speech includes,
verbs are of first importance, proper nouns are of second importance, and numbers are of third importance.
7. The natural language processing semantic analysis method suitable for intelligent power scheduling of claim 5, wherein: the preliminary semantic analysis includes a preliminary semantic analysis of the semantic content,
the preliminary semantic analysis consists of 10 corpora, including "as, cityu, cnc, ctb, msr, pku, sxu, udc, wtb, zx", and different corpora produce different effects when performing segmentation.
8. The utility model provides a natural language processing semantic analysis system of electric power intelligent scheduling which characterized in that: the instructions for the passing include instructions for passing the,
and comparing the operation order with the returned order according to the part of speech, and judging as a passing order when the words of the first, second and third importance levels in the order are consistent.
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