CN110543667A - rural village tree planting pit application interval rough operation system - Google Patents
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Abstract
The invention discloses a rough operation system for operating tree pits in rural villages, which comprises the steps of obtaining numerical parameters of the tree pits in the rural village tree pits in normal operation and numerical parameters of the tree pits in reasonable operation, calculating distance values and providing a prediction system for operating the tree pits in the rural villages. The method has the advantage of improving the prediction accuracy of the operation rationality prediction model.
Description
Technical Field
the invention relates to the field of tree planting pit operation rationality prediction. More particularly, the invention relates to a system and a method for operating rough tree planting pits in rural villages.
Background
the heat tide of new rural construction is raised in China, and the new rural construction with strategic height can schedule water supply and drainage problems in rural areas and rural village regions. Because rural villages have fewer population and lower industrial development level, and different trees need to be planted in many times with professional performance, professional technicians are often not on duty, generally are local villagers and concurrent technical operators, the professional technology processing capacity of the technical operators is relatively low, and inconvenience is brought to operation and maintenance of tree planting pits of rural village tree planting pits.
Disclosure of Invention
in view of the above, the present invention provides a system and a system for controlling the application distance of tree pits in rural villages, which solves or partially solves the above problems;
In order to achieve the effect of the technical steps, the invention provides a rural village tree planting pit application interval rough operation system, which comprises a first operation unit, wherein the first operation unit comprises a recording module and an error reporting module, the recording module integrates a plurality of rural village tree planting pits, the plurality of recording modules record and display numerical parameters of the tree planting pits of one rural village, the plurality of error reporting modules send abnormal signals that the rural village tree planting pits are not matched with standards, and acquire numerical parameters when the tree planting pits are not matched with the standards from the recording module, each rural village tree planting pit is provided with an independent recording module and an error reporting module, the recording module derives the numerical parameters of the tree planting pits to the first operation unit, the error reporting module derives the numerical parameters when the tree planting pits are reasonably operated to the first operation unit, and the first operation unit integrates the numerical parameters when the tree planting pits of the same type are normally operated and the numerical parameters when the tree planting pits are reasonably operated; the first operation unit is used for coding to establish a first number set of a matrix type for obtaining parameters of tree planting pits collected by a reasonable rural village tree planting pit management system, calculating the distance between any numerical values in the first number set, wherein the distance calculation formula (1) is in the formula (1), dm represents the distance between any numerical values in the mth row in the first number set, DCmj represents the numerical value in the jth row in the mth row in the first number set, DCmh represents the numerical value in the mth row in the first number set, DCmmax represents the largest numerical value in the mth row in the first number set, and DCmmin represents the smallest numerical value in the mth row in the first number set; the first operation unit obtains numerical parameters collected by a rural village tree planting pit management system when tree planting pit operation is reasonable, encoding is carried out to establish a second number set of a matrix type, the number of rows of the matrix of the first number set is the same as that of the matrix of the second number set, the distance between any numerical value of the first number set and a corresponding numerical value of the second number set is calculated, the distance calculation formula (2) is in a formula (2), dmj represents the distance between the numerical value of the jth row of the mth row of the first number set and the numerical value of the 1 st row of the mth row of the second number set, DCmj represents the numerical value of the jth row of the mth row of the first number set, and Cm1 represents the numerical value of the 1 st row of the mth row of the second number set; the second operation unit is used for coding numerical parameter data of the tree planting pits of the rural village tree planting pits during normal operation, calculating the distance between numerical parameters during normal operation of the tree planting pits, coding numerical parameter data of the tree planting pits of the rural village tree planting pits during reasonable operation, calculating the distance between numerical parameters during reasonable operation and numerical parameters during normal operation of the tree planting pits, analyzing the correlation coefficient of the distance value of the rural village tree planting pits during normal operation and the distance value of the tree planting pits during reasonable operation, judging the correlation degree of the tree planting pit numerical parameters and the tree planting pits unmatched with the standard, extracting the tree planting pits with the correlation degree meeting the requirement, training the numerical parameters of the tree planting pits with the same rural village tree planting pit type and model, and establishing a prediction model of the reasonable operation of each tree planting pit of the rural village tree planting pits; the third operation unit stores operation rationality prediction models of various types of tree planting pits, numbers the tree planting pits of rural village tree planting pits, judges the operation rationality possibility of the tree planting pits of rural village trees by uploading numerical parameters of the tree planting pits of rural village trees, outputs an operation rationality prediction result of the tree planting pits of rural village trees, and displays operation rationality prompt; the first operation unit records the distance between any numerical value in the first number set as a third number set, records the distance between any numerical value in the first number set and a corresponding numerical value in the second number set as a fourth number set, analyzes the correlation between the third number set and the fourth number set to obtain the correlation coefficient of the third number set and the fourth number set, performs significance test, and judges the relevance of the numerical parameter of the rural village tree planting pit and the tree planting pit which are not matched with the standard, and records the relevance as r; the second operation unit selects a tree planting pit with r being greater than 0.5, trains numerical parameters of tree planting pits of rural villages with the same type number during normal operation and numerical parameters of tree planting pit operation rationality to serve as input data xi, sets a sample training number set D { (xi, yi) | i { (1, 2,3,. 9, n }, xi is input data, yi is output data, n is a sample number, and constructs a rationality model, wherein a rationality model formula (3) is a formula (3), λ ═ p (p2-1) is a fitting function described according to nonlinearity of data, b is an offset value, p is a relative error, e is a prediction mean value, and γ is a correction factor; the third operation unit is used for setting an operation rationality prediction model of each model tree planting pit of the tree planting pits in rural villages, the operation rationality prediction model formula (4) is obtained by a least square method according to the values of alpha and beta, and a and b are random calculation generation numbers and are calculation mean values; the third operation unit inputs the operation rationality prediction model in each model tree planting pit of the rural village tree planting pits into the decision tree node, inputs the tree planting pit of each rural village tree planting pit into the decision tree classifier, one decision tree classifier corresponds to one rural village tree planting pit, the numerical parameters of the tree planting pit of the rural village tree planting pit are processed and then input into the branch of the decision tree node, the decision tree node outputs an operation rationality prediction result of the model tree planting pit, each decision tree classifier calculates the operation rationality prediction result of each rural village tree planting pit, the output result of each decision tree classifier is transmitted to the combiner, and the combiner outputs the operation rationality prediction result of the rural village tree planting pits.
Detailed Description
In order to make the technical problems, technical steps and advantageous effects of the present invention more apparent, the present invention will be described in detail with reference to the following embodiments. It should be noted that the specific embodiments described herein are only for illustrating the present invention and are not to be construed as limiting the present invention, and products that can achieve the same functions are included in the scope of the present invention. The specific method comprises the following steps:
Example 1: a rough operation system for tree planting pits in rural villages by using spacing comprises the following steps: s1, obtaining numerical parameters collected by a rural village tree planting pit management system during normal operation, coding to establish a first number set of a matrix type, calculating the distance between any numerical values in the first number set, wherein the distance calculation formula (1) is a formula, dm represents the distance between any numerical values in the mth row in the first number set, DCmj represents the numerical value in the jth row in the mth row in the first number set, DCmh represents the numerical value in the mth row in the first number set, DCmmax represents the maximum numerical value in the mth row in the first number set, DCmmin represents the minimum numerical value in the mth row in the first number set, judging the distance value of the numerical parameters during normal operation of each tree planting pit, processing a large amount of operation data during daily operation, and reducing uncertainty due to less samples;
The numerical parameter of the tree planting pit collected by the rural village tree planting pit management system during the operation rationality is obtained, the first operation unit obtains the numerical parameter of the tree planting pit collected by the rural village tree planting pit management system during the operation rationality, the first operation unit encodes the numerical parameter to establish a matrix type second number set, the number of rows of the matrix of the first number set is the same as that of the matrix of the second number set, the distance between any numerical value of the first number set and the corresponding numerical value of the second number set is calculated, and the distance calculation formula (2) is a formula, dmj represents the distance between the value of the jth row of the mth row of the first number set and the value of the 1 st row of the mth row of the second number set, DCmj represents the value of the jth row of the mth row of the first number set, Cm1 represents the value of the 1 st row of the mth row of the second number set, the distance between the numerical parameter when the tree planting pit is judged to be reasonable in operation and the numerical parameter when the tree planting pit is normally operated is calculated by adopting a matrix algorithm and the data of the same tree planting pit and the same tree planting pit;
recording the distance between any numerical value in the first number set as a third number set, recording the distance between any numerical value in the first number set and a corresponding numerical value in the second number set as a fourth number set, analyzing the correlation between the third number set and the fourth number set to obtain the correlation coefficient of the third number set and the fourth number set, performing significance test, judging the correlation degree of the numerical parameter of the tree planting pit in the rural village and the unmatched tree planting pit with the standard, recording the correlation degree as r, and eliminating the tree planting pit of which the numerical parameter is irrelevant to the reasonability of the tree planting pit operation, so that the accuracy of the prediction model of the reasonability of the operation is improved;
s2, a second operation unit selects a tree planting pit with r being greater than 0.5, a numerical parameter when the tree planting pit of each rural village with the same type number normally operates and a numerical parameter when the tree planting pit operates reasonably are trained to serve as input data xi, a sample training number set D { (xi, yi) | i ═ 1,2,3,. once, n }, yi is set to serve as output data, n serves as a sample number, a reasonable model is constructed, a reasonable model formula (3) is a formula, λ ═ p (p2-1) is a fitting function described according to nonlinearity of the data, b is a deviation value, p is a relative error, e is a prediction average value, and γ is a correction factor;
Obtaining an operation rationality prediction model of each model tree planting pit of the tree planting pits in rural villages through mathematical calculation, wherein the operation rationality prediction model formula (4) is obtained by a least square method according to values of alpha and beta, and a and b are random calculation generation numbers and are calculation mean values;
S3, inputting the operation rationality prediction model in each model tree planting pit of the rural village tree planting pits into a decision tree node, inputting the tree planting pit of each rural village tree planting pit into a decision tree classifier, enabling one decision tree classifier to correspond to one rural village tree planting pit, processing the numerical parameters of the tree planting pits of the rural village tree planting pits and inputting the numerical parameters into branches of the decision tree node, outputting the operation rationality prediction result of each model tree planting pit by the decision tree node, calculating the operation rationality prediction result of each rural village tree planting pit by each decision tree classifier, transmitting the output result of each decision tree classifier to a combiner, and outputting the operation rationality prediction result of the rural village tree planting pits by the combiner.
the first operation unit is used for integrating the recording modules and the error reporting modules of a plurality of rural village tree planting pits, one recording module records and displays numerical parameters of all the tree planting pits of one rural village tree planting pit, one error reporting module sends abnormal signals that the rural village tree planting pits are not matched with standards and acquires the numerical parameters when the tree planting pits are not matched with the standards from the recording module, each rural village tree planting pit is provided with an independent recording module and an error reporting module, the recording module derives the numerical parameters of all the tree planting pits to the first operation unit, the error reporting module derives the numerical parameters when the tree planting pits are reasonably operated to the first operation unit, and the first operation unit integrates the numerical parameters when the tree planting pits of the same type are normally operated and the numerical parameters when the tree planting pits are reasonably operated;
A second operation unit, which encodes the numerical parameter data of the tree-planting pits of rural village tree-planting pits during normal operation, calculates the distance between the numerical parameter data of the tree-planting pits during normal operation, encodes the numerical parameter data of the tree-planting pits of rural village tree-planting pits during reasonable operation, calculates the distance between the numerical parameter of reasonable operation and the numerical parameter of normal operation of the tree-planting pits, analyzes the correlation coefficient between the distance value of the rural village tree-planting pits during normal operation and the distance value of the tree-planting pits during reasonable operation, judges the correlation between the numerical parameter of the tree-planting pits and the standard, extracts the tree-planting pits with the correlation meeting the requirement, trains the numerical parameter of the tree-planting pits with the same type and model of the rural village tree-planting pits during normal operation and the numerical parameter of reasonable operation of the tree-planting pits, establishing an operation rationality prediction model of each tree planting pit of the tree planting pits in rural villages;
and the third operation unit is used for storing the operation rationality prediction model of each tree planting pit, numbering each tree planting pit of the rural village tree planting pits, judging the operation rationality possibility of the tree planting pits of the rural village trees by uploading the numerical parameters of the tree planting pits of the rural village trees, outputting the operation rationality prediction result of the tree planting pits of the rural village trees, and displaying the operation rationality prompt.
Selecting thirty rural village tree planting pits from a tree planting pit management system, extracting numerical parameters of the tree planting pits of the rural village tree planting pits, wherein the time span is 2015-2018, 120 groups of data are obtained, performing matrix division on the data, recording the data as a first number set, and calculating a distance value between the numerical parameters of the tree planting pits when one tree planting pit normally operates;
Extracting numerical parameters of thirty tree planting pits in rural villages with the time span of 2015-2018 when the tree planting pits operate reasonably, carrying out matrix division on the data, recording the data as a second number set, and calculating the distance value between the numerical parameters of one tree planting pit when the tree planting pit operates reasonably and the numerical parameters of the tree planting pit when the tree planting pit operates normally;
recording the distance between any numerical value in the first number set as a third number set, recording the distance between any numerical value in the first number set and a corresponding numerical value in the second number set as a fourth number set, analyzing the correlation between the third number set and the fourth number set to obtain the correlation coefficient of the third number set and the fourth number set, performing significance test, and judging the correlation degree of the numerical parameter of the planting pit and the standard mismatch;
inputting numerical parameters of tree planting pit data in rural villages with satisfactory relevance to perform sample training, outputting results, performing mathematical calculation, outputting an operation reasonableness prediction model of each model of tree planting pit, making a decision on the operation reasonableness prediction model by using a decision tree classifier, outputting an operation reasonableness prediction result of each tree planting pit in rural villages by using a decision tree combiner, and arranging technical personnel to perform targeted re-planning.
The above description is only for the preferred embodiment of the present invention, and should not be used to limit the scope of the claims of the present invention. While the foregoing description will be understood and appreciated by those skilled in the relevant art, other equivalents may be made thereto without departing from the scope of the claims.
Has the advantages that: and judging the correlation between the numerical parameter when the tree planting pit is normal and the numerical parameter when the tree planting pit is reasonable in operation, establishing a prediction model of the rationality of operation, screening out irrelevant tree planting pits which cannot predict the rationality of operation in real time, and improving the prediction accuracy of the prediction model of the rationality of operation. Additional advantages, objects, and features of the invention will be set forth in part in the description which follows and in part will become apparent to those having ordinary skill in the art upon examination of the following or may be learned from practice of the invention.
Claims (1)
1. A rural village tree planting pit application interval rough operation system is characterized by comprising: the first operation unit comprises a recording module and an error reporting module, wherein the recording module and the error reporting module are used for integrating a plurality of rural village tree planting pits, the plurality of recording modules record and display numerical parameters of the tree planting pits of one rural village, the plurality of error reporting modules send abnormal signals that the rural village tree planting pits are not matched with the standard and acquire the numerical parameters when the tree planting pits are not matched with the standard from the recording module, each rural village tree planting pit is provided with an independent recording module and an error reporting module, the recording module derives the numerical parameter of each tree planting pit to the first operation unit, the error reporting module derives the numerical parameter of the tree planting pit during the rationality of operation to the first operation unit, the first operation unit integrates the numerical parameter of each rural village tree planting pit with the same model when the tree planting pit normally operates and the numerical parameter of each rural village tree planting pit when the tree planting pit operates reasonably; the first operation unit is used for coding to establish a first number set of a matrix type for obtaining parameters of tree planting pits collected by a reasonable rural village tree planting pit management system, calculating the distance between any numerical values in the first number set, wherein the distance calculation formula (1) is in the formula (1), dm represents the distance between any numerical values in the mth row in the first number set, DCmj represents the numerical value in the jth row in the mth row in the first number set, DCmh represents the numerical value in the mth row in the first number set, DCmmax represents the largest numerical value in the mth row in the first number set, and DCmmin represents the smallest numerical value in the mth row in the first number set; the first operation unit obtains numerical parameters collected by a rural village tree planting pit management system when tree planting pit operation is reasonable, encoding is carried out to establish a second number set of a matrix type, the number of rows of the matrix of the first number set is the same as that of the matrix of the second number set, the distance between any numerical value of the first number set and a corresponding numerical value of the second number set is calculated, the distance calculation formula (2) is in a formula (2), dmj represents the distance between the numerical value of the jth row of the mth row of the first number set and the numerical value of the 1 st row of the mth row of the second number set, DCmj represents the numerical value of the jth row of the mth row of the first number set, and Cm1 represents the numerical value of the 1 st row of the mth row of the second number set; a second operation unit, which encodes the numerical parameter data of the tree-planting pits of rural village tree-planting pits during normal operation, calculates the distance between the numerical parameter data of the tree-planting pits during normal operation, encodes the numerical parameter data of the tree-planting pits of rural village tree-planting pits during reasonable operation, calculates the distance between the numerical parameter of reasonable operation and the numerical parameter of normal operation of the tree-planting pits, analyzes the correlation coefficient between the distance value of the rural village tree-planting pits during normal operation and the distance value of the tree-planting pits during reasonable operation, judges the correlation between the numerical parameter of the tree-planting pits and the standard, extracts the tree-planting pits with the correlation meeting the requirement, trains the numerical parameter of the tree-planting pits with the same type and model of the rural village tree-planting pits during normal operation and the numerical parameter of reasonable operation of the tree-planting pits, establishing an operation rationality prediction model of each planting tree pit of the tree pits in rural villages; the third operation unit stores operation rationality prediction models of various types of tree planting pits, numbers the tree planting pits of rural village tree planting pits, judges the operation rationality possibility of the tree planting pits of rural village trees by uploading numerical parameters of the tree planting pits of rural village trees, outputs an operation rationality prediction result of the tree planting pits of rural village trees, and displays operation rationality prompt; the first operation unit records the distance between any numerical value in the first number set as a third number set, records the distance between any numerical value in the first number set and a corresponding numerical value in the second number set as a fourth number set, analyzes the correlation between the third number set and the fourth number set to obtain the correlation coefficient of the third number set and the fourth number set, performs significance test, and judges the relevance of the numerical parameter of the rural village tree planting pit and the tree planting pit which are not matched with the standard, and records the relevance as r; the second operation unit selects the tree planting pit with r >0.5, trains the numerical parameter of the tree planting pit in each rural village with the same type number during normal operation and the numerical parameter of the tree planting pit during reasonable operation, sets a sample training number set D { (xi, yi) | i { (xi, 2,3,. once, n }, xi is input data, yi is output data, n is sample number, constructs a reasonable model, the formula (3) of the reasonable model is a formula (3), and λ ═ p (p2-1),
a fitting function described according to the nonlinearity of the data, b is a deviation value, p is a relative error, e is a predicted mean value, and gamma is a correction factor; the third operation unit is used for setting an operation rationality prediction model of each model tree planting pit of the tree planting pits in rural villages, the operation rationality prediction model formula (4) is obtained by a least square method according to the values of alpha and beta, and a and b are random calculation generation numbers and are calculation mean values; the third operation unit inputs the operation rationality prediction model in each model tree planting pit of the rural village tree planting pits into the decision tree node, inputs the tree planting pit of each rural village tree planting pit into the decision tree classifier, one decision tree classifier corresponds to one rural village tree planting pit, the numerical parameters of the tree planting pit of the rural village tree planting pit are processed and then input into the branch of the decision tree node, the decision tree node outputs the operation rationality prediction result of the model tree planting pit, each decision tree classifier calculates the operation rationality prediction result of each rural village tree planting pit, the output result of each decision tree classifier is transmitted to the combiner, and the combiner outputs the operation rationality prediction result of the rural village tree planting pits.
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