Land utilization optimization method for multifunctional space integration

Abstract

The invention discloses a multifunctional space integrated land utilization optimization method, and relates to the technical field of land planning, and the method comprises the steps: taking a circulation end as a basic influence factor based on the integrated data of a multifunctional space terminal, and analyzing a correlation coefficient between the production data of a historical production end and the consumption data of a historical consumption end; determining the producible land area and the producible crop types, and obtaining the total production amount of a plurality of producible crops at the production end; based on the total production amount of a plurality of crops capable of being produced at the production end and the correlation coefficient between the production data of the historical production end and the consumption data of the historical consumption end, whether the current to-be-produced crops meet the income demand or not is judged, and if it is judged that the maximum income is not met, based on the integrated data of the multifunctional space terminal, the maximum income is obtained. The crop production decision management system and method have the advantages that the crop production income and the land utilization efficiency are improved.

Description

Technical Field

[0001] The invention relates to the technical field of land planning, and in particular to a land utilization optimization method for multifunctional space integration. Background Art

[0002] Land use optimization with multifunctional space integration refers to the efficient, orderly and sustainable use of land in different functional spaces (such as production, living and ecological spaces) through reasonable planning and layout of land resources to meet the multi-objective development needs of regional economic, social and environmental benefits.

[0003] Due to the existing land contracting system, contractors mainly produce rice or wheat as their main crops. However, due to fluctuations in rice and wheat prices, production costs are increased, and conventional experience in large-scale production tasks results in low returns and poor land utilization. Summary of the invention

[0004] In order to solve the above technical problems, a multifunctional space integrated land use optimization method is provided. This technical solution solves the above-mentioned problem that due to the existing land contracting system, contractors mainly produce rice or wheat as the main crops, but due to the fluctuations in the prices of rice and wheat, the production costs are increased, and the conventional experience is used to carry out large-scale generation tasks, resulting in low returns and poor land utilization.

[0005] In order to achieve the above purpose, the technical solution adopted by the present invention is:

[0006] Land use optimization methods for multifunctional space integration include:

[0007] Acquire integrated data of a multifunctional space terminal; the multifunctional space terminal includes a production end, a circulation end, and a consumption end;

[0008] Based on the integrated data of the multifunctional space terminal, the circulation end is taken as the basic influencing factor to analyze the correlation coefficient between the production data of the historical production end and the consumption data of the historical consumption end;

[0009] Determine the productive land area and the types of crops that can be produced, and obtain the total production of several types of crops that can be produced on the production side;

[0010] Based on the total production of several types of producible crops on the production side and the correlation coefficient between the historical production data on the production side and the historical consumption data on the consumption side, it is determined whether the current crops to be produced meet the profit requirements. If so, it is determined that the maximum profit is met; if not, it is determined that the maximum profit is not met;

[0011] If it is determined that the maximum profit is not met, a crop production decision-making management model is constructed based on the integrated data of the multi-functional space terminal to adjust the production tasks of the crops to be produced.

[0012] Preferably, based on the integrated data of the multifunctional space terminal, the circulation end is taken as the basic influencing factor, and the correlation coefficient between the production data of the historical production end and the consumption data of the historical consumption end is analyzed, specifically including:

[0013] Standardize the historical production data and the historical consumption data, and build a correlation curve between the sales volume of each crop produced on the production side and each consumption region on the consumption side.

[0014] Obtain several circulation influencing factors for each circulation end from the production end to the consumption end, and calculate the circulation influence coefficient I = V w between the production end and the consumption end V +E·w E +C·w C , where V, E, and C are circulation speed, circulation efficiency, and circulation cost respectively, and w V 、w E 、w C They are circulation speed weight, circulation efficiency weight and circulation cost weight;

[0015] Obtain the correlation curve between the sales volume of each production crop at the production end and each consumption area at the consumption end, take the circulation influence coefficient between the production end and the consumption end as the basic influence factor, calculate the linear regression coefficient between the production crops at the production end and the consumption area at the consumption end, and record it as the correlation coefficient between the production end and the consumption end;

[0016] The correlation coefficient between the production and consumption end is specifically:

[0017]

[0018] In the formula, G is the correlation coefficient between the production and consumption ends, P i is the total historical production of the i-th crop produced at the production end, R ij is the total sales volume of the i-th crop produced at the production end in the j-th consumer region at the consumer end, is the historical production mean of crops, is the average sales value of crops in the consumption area at the consumer end, I j is the circulation impact coefficient from the production end to the consumption end of the j-th consumption area.

[0019] Preferably, based on the total production of several types of producible crops at the production end and the correlation coefficient between the historical production data of the production end and the historical consumption data of the consumption end, judging whether the current crops to be produced meet the income requirements specifically includes:

[0020] Based on the consumption data of the historical consumption end, the consumption data of each region is divided according to the unit time, and the historical crop consumption time series data of the consumption area of ​​the consumption end is obtained;

[0021] Based on the historical production data of the production side, the production costs of several types of crops on the production side are analyzed according to the area of ​​​​productive land and the types of crops that can be produced;

[0022] Based on the total production of several types of crops that can be produced on the production side and the predicted future crop value, estimate the expected income value of several types of crops that can be produced on the production side;

[0023] The actual profit value of each of the crops that can be produced is obtained by subtracting the production costs of the crops produced at the production end from the estimated profit values ​​of the crops that can be produced at the production end;

[0024] Based on the actual profit value of each producible crop, it is determined whether the current crop to be produced meets the maximum profit requirement. If so, it is determined that the maximum profit is met; if not, it is determined that the maximum profit is not met.

[0025] Preferably, based on the total production volume of several kinds of crops that can be produced at the production end and the predicted future crop value, estimating the expected revenue value of several kinds of crops that can be produced at the production end specifically includes:

[0026] Based on the consumption data of the historical consumption end, the consumption data of each region is divided according to the unit time, and the historical crop consumption time series data of the consumption area of ​​the consumption end is obtained;

[0027] According to the historical crop consumption time series data of the consumption areas at the consumer end, the transaction unit price of crops in each consumption area is used as the consumption attribute of the corresponding crops. The crop consumption time series data of the consumption areas are clustered according to the types of crops to obtain the consumption crop value time series data at the consumer end.

[0028] The time series data of the value of the agricultural products consumed at the consumer end is specifically as follows:

[0029]

[0030] Where list is the time series data of the value of agricultural products consumed at the consumer end, and F ij (t) is the transaction price of the i-th crop in the j-th consumption area in t unit time, C jk(t+1) is the i-th crop in t+1 unit time being divided into the k-th cluster center, and T is the total time length;

[0031] Based on ARIMA time series forecasting, a production crop value forecasting and analysis model is constructed;

[0032] Based on the production crop value prediction and analysis model, the correlation coefficient between the historical production data and the historical consumption data is used as the seasonal influencing factor between the production and consumption ends. The consumption crop value time series data of the consumption end is substituted into the production crop value prediction and analysis model. The historical crop transaction unit price data per unit time is used as the independent variable input, and the predicted future crop value is used as the dependent variable output;

[0033] The production crop value prediction and analysis model is specifically as follows:

[0034]

[0035] In the formula, is the predicted value of the i-th crop in t units of time, is the actual value of the i-th crop in t units of time, F ij (t-i') is the transaction price of the i-th crop in the j-th consumption area with the t-i'th autoregressive order, ∈(t) is the error term under t unit time, ∈(t-j') is the error term with the t-j'th moving average order, φ i' is the coefficient of the autoregressive term, θ j' is the coefficient of the moving average term.

[0036] Preferably, if it is determined that the maximum benefit is not met, a crop production decision management model is constructed based on the integrated data of the multifunctional space terminal, and the production tasks of the crops to be produced are adjusted, specifically including:

[0037] Based on the decision tree, a crop production decision management model is constructed;

[0038] Based on the actual profit value of each type of crop that can be produced, the objective function is to minimize the production cost and maximize the actual profit of each crop that can be produced in each quarter;

[0039] Obtain the correlation factors that affect the production cost and actual profit value of each producible crop as the division decision features of the cotyledon and branch nodes of the crop production decision management model, and form a random forest for crop production decision;

[0040] Based on the random forest of crop production decision, the integrated data of the multifunctional space terminal is taken as input under the constraint of the objective function, and the production task of the optimal crops to be produced is taken as output.

[0041] Compared with the prior art, the present invention has the following beneficial effects:

[0042] The present invention proposes a land utilization optimization scheme for multifunctional space integration. By integrating the data of multifunctional space terminals, taking the circulation end as the basic influencing factor, the historical data correlation coefficient between the production end and the consumption end is analyzed, and then the productive land area and the types of crops and their total production are determined. On the basis of judging whether the current crops to be produced meet the income requirements, if the maximum income is not met, a multi-factor comprehensive decision-making management model is constructed using the integrated data to dynamically adjust the production tasks. The beneficial effects are: achieving the optimal configuration of land use and improving the income and land utilization efficiency of crop production. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 Flowchart of land use optimization method for multifunctional space integration;

[0044] Figure 2 A flow chart of the method for analyzing the correlation coefficient between the production data of the historical production end and the consumption data of the historical consumption end;

[0045] Figure 3 A flow chart of a method for determining whether the current crops to be produced meet the income requirements;

[0046] Figure 4 To estimate the expected revenue value of several types of crops that can be produced on the production side;

[0047] Figure 5 To adjust the production tasks of crops to be produced. DETAILED DESCRIPTION

[0048] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are only examples, and those skilled in the art may think of other obvious variations.

[0049] Reference Figure 1 As shown in the figure, the land use optimization method of multifunctional space integration includes:

[0050] Acquire integrated data of a multifunctional space terminal; the multifunctional space terminal includes a production end, a circulation end, and a consumption end;

[0051] Based on the integrated data of the multifunctional space terminal, the circulation end is taken as the basic influencing factor to analyze the correlation coefficient between the production data of the historical production end and the consumption data of the historical consumption end;

[0052] Determine the productive land area and the types of crops that can be produced, and obtain the total production of several types of crops that can be produced on the production side;

[0053] Based on the total production of several types of producible crops on the production side and the correlation coefficient between the historical production data on the production side and the historical consumption data on the consumption side, it is determined whether the current crops to be produced meet the profit requirements. If so, it is determined that the maximum profit is met; if not, it is determined that the maximum profit is not met;

[0054] If it is determined that the maximum profit is not met, a crop production decision-making management model is constructed based on the integrated data of the multi-functional space terminal to adjust the production tasks of the crops to be produced.

[0055] This solution integrates the data of multifunctional space terminals, takes the circulation end as the basic influencing factor, analyzes the historical data correlation coefficient between the production end and the consumption end, and then determines the productive land area and crop types and their total production. On the basis of judging whether the current crops to be produced meet the profit requirements, if they do not meet the maximum profit, the integrated data is used to build a multi-factor comprehensive decision-making management model to dynamically adjust the production tasks. The beneficial effect is to achieve the optimal allocation of land use and improve the profit and land use efficiency of crop production.

[0056] Reference Figure 2 As shown in the figure, based on the integrated data of the multifunctional space terminal, the circulation end is taken as the basic influencing factor, and the correlation coefficient between the production data of the historical production end and the consumption data of the historical consumption end is analyzed. Specifically, it includes:

[0057] Standardize the historical production data and the historical consumption data, and build a correlation curve between the sales volume of each crop produced on the production side and each consumption region on the consumption side.

[0058] Obtain several circulation influencing factors for each circulation end from the production end to the consumption end, and calculate the circulation influence coefficient I = V w between the production end and the consumption end V +E·w E +C·w C , where V, E, and C are circulation speed, circulation efficiency, and circulation cost respectively, and w V 、w E 、w C They are circulation speed weight, circulation efficiency weight and circulation cost weight;

[0059] Obtain the correlation curve between the sales volume of each production crop at the production end and each consumption area at the consumption end, take the circulation influence coefficient between the production end and the consumption end as the basic influence factor, calculate the linear regression coefficient between the production crops at the production end and the consumption area at the consumption end, and record it as the correlation coefficient between the production end and the consumption end;

[0060] The correlation coefficient between the production and consumption end is specifically:

[0061]

[0062] In the formula, G is the correlation coefficient between the production and consumption ends, P i is the total historical production of the i-th crop produced at the production end, R ij is the total sales volume of the i-th crop produced at the production end in the j-th consumer region at the consumer end, is the historical production mean of crops, is the average sales value of crops in the consumption area at the consumer end, I j is the circulation impact coefficient from the production end to the consumption end of the j-th consumption area.

[0063] It is understandable that the greater the correlation coefficient between the production data on the production side and the consumption data on the consumption side, the greater the preference of the output crops on the production side for consumers on the consumption side. Therefore, by analyzing the audience size of the output crops on the production side, the optimal output crop combination can be screened to improve land use efficiency while ensuring maximum benefits.

[0064] Reference Figure 3 As shown, based on the total production of several types of crops that can be produced at the production end and the correlation coefficient between the historical production data of the production end and the historical consumption data of the consumption end, it is judged whether the current crops to be produced meet the income requirements, specifically including:

[0065] Based on the consumption data of the historical consumption end, the consumption data of each region is divided according to the unit time, and the historical crop consumption time series data of the consumption area of ​​the consumption end is obtained;

[0066] Based on the historical production data of the production side, the production costs of several types of crops on the production side are analyzed according to the area of ​​​​productive land and the types of crops that can be produced;

[0067] Based on the total production of several types of crops that can be produced on the production side and the predicted future crop value, estimate the expected income value of several types of crops that can be produced on the production side;

[0068] The actual profit value of each of the crops that can be produced is obtained by subtracting the production costs of the crops produced at the production end from the estimated profit values ​​of the crops that can be produced at the production end;

[0069] Based on the actual profit value of each producible crop, it is determined whether the current crop to be produced meets the maximum profit requirement. If so, it is determined that the maximum profit is met; if not, it is determined that the maximum profit is not met.

[0070] Through precise data analysis and calculation, this solution provides a basis for crop production decision-making, helps optimize production structure, improve agricultural production efficiency, and ensure that crop production can meet market demand while maximizing profits.

[0071] Reference Figure 4 As shown in the figure, based on the total production of several kinds of crops that can be produced on the production side and the predicted future crop value, the estimated profit values ​​of several kinds of crops that can be produced on the production side include:

[0072] Based on the consumption data of the historical consumption end, the consumption data of each region is divided according to the unit time, and the historical crop consumption time series data of the consumption area of ​​the consumption end is obtained;

[0073] According to the historical crop consumption time series data of the consumption areas at the consumer end, the transaction unit price of crops in each consumption area is used as the consumption attribute of the corresponding crops. The crop consumption time series data of the consumption areas are clustered according to the types of crops to obtain the consumption crop value time series data at the consumer end;

[0074] The time series data of the value of agricultural products consumed at the consumer end is specifically as follows:

[0075]

[0076] Where list is the time series data of the value of agricultural products consumed at the consumer end, and F ij (t) is the transaction price of the i-th crop in the j-th consumption area in t unit time, C jk (t+1) is the i-th crop in t+1 unit time being divided into the k-th cluster center, and T is the total time length;

[0077] Based on ARIMA time series forecasting, a production crop value forecasting and analysis model is constructed;

[0078] Based on the production crop value prediction and analysis model, the correlation coefficient between the historical production data and the historical consumption data is used as the seasonal influencing factor between the production and consumption ends. The consumption crop value time series data of the consumption end is substituted into the production crop value prediction and analysis model. The historical crop transaction unit price data per unit time is used as the independent variable input, and the predicted future crop value is used as the dependent variable output;

[0079] The production crop value prediction and analysis model is specifically as follows:

[0080]

[0081] In the formula, is the predicted value of the i-th crop in t units of time, is the actual value of the i-th crop in t units of time, F ij (t-i') is the transaction price of the i-th crop in the j-th consumption area with the t-i'th autoregressive order, ∈(t) is the error term under t unit time, ∈(t-j') is the error term with the t-j'th moving average order, φ i' is the coefficient of the autoregressive term, θ j' is the coefficient of the moving average term.

[0082] This plan comprehensively considers the historical consumption data on the consumer side and the historical production data on the production side, combines seasonal influencing factors, and uses the ARIMA model to predict the future value of crops, accurately grasp market demand and price trends, formulate more reasonable production plans, and maximize land use efficiency.

[0083] Reference Figure 5 As shown in the figure, if it is determined that the maximum benefit is not met, a crop production decision management model is constructed based on the integrated data of the multifunctional space terminal, and the production tasks of the crops to be produced are adjusted, including:

[0084] Based on the decision tree, a crop production decision management model is constructed;

[0085] Based on the actual profit value of each type of crop that can be produced, the objective function is to minimize the production cost and maximize the actual profit of each crop that can be produced in each quarter;

[0086] Obtain the correlation factors that affect the production cost and actual profit value of each producible crop as the division decision features of the cotyledon and branch nodes of the crop production decision management model, and form a random forest for crop production decision;

[0087] Based on the random forest of crop production decision, the integrated data of the multifunctional space terminal is taken as input under the constraint of the objective function, and the production task of the optimal crops to be produced is taken as output.

[0088] This solution constructs a crop production decision-making management model and combines it with the predictive ability of random forests. It can comprehensively consider multiple influencing factors, accurately evaluate the production benefits of different crops, provide scientific decision-making support for agricultural production, and maximize agricultural production benefits.

[0089] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions only describe the principles of the present invention. The present invention may be subject to various changes and improvements without departing from the spirit and scope of the present invention. These changes and improvements fall within the scope of the present invention. The scope of protection claimed by the present invention is defined by the attached claims and their equivalents.

Claims

1. A land use optimization method for multifunctional space integration, characterized in that: include: Obtain integrated data from multifunctional space terminals; The multifunctional space terminal includes a production end, a circulation end, and a consumption end; Based on the integrated data of the multifunctional space terminal, the circulation end is taken as the basic influencing factor to analyze the correlation coefficient between the production data of the historical production end and the consumption data of the historical consumption end; Determine the productive land area and the types of crops that can be produced, and obtain the total production of several types of crops that can be produced on the production side; Based on the total production of several types of producible crops on the production side and the correlation coefficient between the historical production data on the production side and the historical consumption data on the consumption side, it is determined whether the current crops to be produced meet the profit requirements. If so, it is determined that the maximum profit is met; if not, it is determined that the maximum profit is not met; If it is determined that the maximum profit is not met, a crop production decision-making management model is constructed based on the integrated data of the multi-functional space terminal to adjust the production tasks of the crops to be produced.

2. The multifunctional space integrated land use optimization method according to claim 1, characterized in that: Based on the integrated data of the multifunctional space terminal, taking the circulation end as the basic influencing factor, the correlation coefficient between the production data of the historical production end and the consumption data of the historical consumption end is analyzed, including: Standardize the historical production data and the historical consumption data, and build a correlation curve between the sales volume of each crop produced on the production side and each consumption region on the consumption side. Obtain several circulation influencing factors for each circulation end from the production end to the consumption end, and calculate the circulation influence coefficient I = V w between the production end and the consumption end V +E·w E +C·w C , where V, E, and C are circulation speed, circulation efficiency, and circulation cost respectively, and w V 、w E 、w C They are circulation speed weight, circulation efficiency weight and circulation cost weight; In the correlation curve diagram obtained between the sales volume of each production crop on the production side and each consumption area on the consumption side, the circulation influence coefficient between the production side and the consumption side is taken as the basic influencing factor, and the linear regression coefficient between the production crops on the production side and the consumption area on the consumption side is calculated, which is recorded as the correlation coefficient between the production side and the consumption side.

3. The land utilization optimization method of multifunctional space integration according to claim 2 is characterized in that: The correlation coefficient between the production and consumption end is specifically: In the formula, G is the correlation coefficient between the production and consumption ends, P i is the total historical production of the i-th crop produced at the production end, R ij is the total sales volume of the i-th crop produced at the production end in the j-th consumer region at the consumer end, is the historical production mean of crops, is the average sales value of crops in the consumption area at the consumer end, I j is the circulation impact coefficient from the production end to the consumption end of the j-th consumption area.

4. The land utilization optimization method of multifunctional space integration according to claim 3 is characterized in that: Based on the total production of several types of crops that can be produced on the production side and the correlation coefficient between the historical production data on the production side and the historical consumption data on the consumption side, it is determined whether the crops to be produced currently meet the income requirements, including: Based on the consumption data of the historical consumption end, the consumption data of each region is divided according to the unit time, and the historical crop consumption time series data of the consumption area of ​​the consumption end is obtained; Based on the historical production data of the production side, the production costs of several types of crops on the production side are analyzed according to the area of ​​​​productive land and the types of crops that can be produced; Based on the total production of several types of crops that can be produced on the production side and the predicted future crop value, estimate the expected income value of several types of crops that can be produced on the production side; The actual profit value of each of the crops that can be produced is obtained by subtracting the production costs of the crops produced at the production end from the estimated profit values ​​of the crops that can be produced at the production end; Based on the actual profit value of each producible crop, it is determined whether the current crop to be produced meets the maximum profit requirement. If so, it is determined that the maximum profit is met; if not, it is determined that the maximum profit is not met.

5. The land utilization optimization method of multifunctional space integration according to claim 4 is characterized in that: Based on the total production of several types of crops that can be produced on the production side and the predicted future crop value, the estimated revenue value of several types of crops that can be produced on the production side is estimated, including: Based on the consumption data of the historical consumption end, the consumption data of each region is divided according to the unit time, and the historical crop consumption time series data of the consumption area of ​​the consumption end is obtained; According to the historical crop consumption time series data of the consumption areas at the consumer end, the transaction unit price of crops in each consumption area is used as the consumption attribute of the corresponding crops. The crop consumption time series data of the consumption areas are clustered according to the types of crops to obtain the consumption crop value time series data at the consumer end.

6. The land utilization optimization method of multifunctional space integration according to claim 5 is characterized in that: The time series data of the value of agricultural products consumed at the consumer end are specifically as follows: Where list is the time series data of the value of agricultural products consumed at the consumer end, and F ij (t) is the transaction price of the i-th crop in the j-th consumption area in t unit time, C jk (t+1) is the i-th crop in t+1 unit time being divided into the k-th cluster center, and T is the total time length; Based on ARIMA time series forecasting, a production crop value forecasting and analysis model is constructed; Based on the production crop value prediction and analysis model, the correlation coefficient between the historical production data and the historical consumption data is used as the seasonal influencing factor between the production and consumption ends. The consumption crop value time series data of the consumption end is substituted into the production crop value prediction and analysis model. The historical crop transaction unit price data per unit time is used as the independent variable input, and the predicted future crop value is used as the dependent variable output; The production crop value prediction and analysis model is specifically as follows: In the formula, is the predicted value of the i-th crop in t units of time, is the actual value of the i-th crop in t units of time, F ij (t-i') is the transaction price of the i-th crop in the j-th consumption area with the t-i'th autoregressive order, ∈(t) is the error term under t unit time, ∈(t-j') is the error term with the t-j'th moving average order, φ i' is the coefficient of the autoregressive term, θ j' is the coefficient of the moving average term.

7. The multifunctional space integrated land utilization optimization method according to claim 6 is characterized in that: If it is determined that the maximum benefit is not met, a crop production decision management model is constructed based on the integrated data of the multifunctional space terminal to adjust the production tasks of the crops to be produced, including: Based on the decision tree, a crop production decision management model is constructed; Based on the actual profit value of each type of crop that can be produced, the objective function is to minimize the production cost and maximize the actual profit of each crop that can be produced in each quarter; Obtain the correlation factors that affect the production cost and actual profit value of each producible crop as the division decision features of the cotyledon and branch nodes of the crop production decision management model, and form a random forest for crop production decision; Based on the random forest of crop production decision, the integrated data of the multifunctional space terminal is taken as input under the constraint of the objective function, and the production task of the optimal crops to be produced is taken as output.

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