Method, device and equipment for determining greenhouse environment parameters

Abstract

The invention provides a method, a device and equipment for determining greenhouse environment parameters, and belongs to the technical field of computer information processing. The greenhouse environment parameter determination method comprises the following steps: acquiring real-time data of temperature, humidity, illumination and carbon dioxide concentration of a greenhouse; processing real-time data of temperature, humidity, illumination and carbon dioxide concentration to obtain greenhouse environment parameters; inputting the greenhouse environment parameters into a greenhouse environment control model for processing to obtain greenhouse control parameters; the greenhouse environment control model processes the input vector through a control function to obtain an intermediate result, and the intermediate result is linearly weighted to obtain greenhouse control parameters; the greenhouse control parameters are used for controlling the operation state of the greenhouse environment regulation and control equipment. According to the technical scheme, the greenhouse environment parameters are monitored in real time, the regulation and control equipment is controlled to act in time, the regulation accuracy of the greenhouse temperature and humidity is improved, and the greenhouse environment control effect is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of computer information processing, and in particular to a method, device and equipment for determining greenhouse environmental parameters. Background Art

[0002] Temperature control in greenhouses presents complex and ever-changing challenges. Environmental factors such as temperature, humidity, and light interact with each other, making precise control difficult. First, temperature is affected not only by external climatic conditions but also by the uneven distribution of heat sources within the greenhouse. For example, areas near heating equipment experience higher temperatures, while those further away experience lower temperatures. Furthermore, greenhouse insulation varies greatly, and greenhouse coverings made of different materials offer significantly different insulating properties, making it difficult to maintain a stable indoor temperature. Humidity is closely linked to temperature. When temperature rises, water evaporation accelerates, leading to higher humidity; conversely, when temperature drops, humidity decreases. Furthermore, crop transpiration is a significant factor influencing humidity. Different crops have different transpiration rates, which vary throughout the day. This results in frequent and dynamic changes in greenhouse humidity, making it difficult to maintain a precise value. Regarding light, cloud cover and seasonal variations in the sun's altitude can cause fluctuations in the intensity and duration of light entering the greenhouse. Furthermore, light influences temperature. Intense light can rapidly increase greenhouse temperature, which in turn affects humidity. These environmental factors are intertwined and influence each other. Adjustment of any one factor may trigger a chain reaction of other factors. Therefore, it is very difficult to achieve precise control of greenhouse temperature, humidity, light and other environmental factors. Summary of the Invention

[0003] The present invention provides a method, device and equipment for determining greenhouse environmental parameters, which solve the problems of difficult greenhouse environmental control, low environmental parameter adjustment accuracy and poor greenhouse environmental control effect.

[0004] In order to solve the above technical problems, the technical solutions of the present invention are as follows:

[0005] An embodiment of the present invention provides a method for determining greenhouse environmental parameters, comprising:

[0006] Obtain real-time data on greenhouse temperature, humidity, light, and carbon dioxide concentration;

[0007] Processing the real-time data of temperature, humidity, light, and carbon dioxide concentration to obtain greenhouse environmental parameters;

[0008] Inputting the greenhouse environmental parameters into a greenhouse environmental control model for processing to obtain greenhouse control parameters; the greenhouse environmental control model processes the input vector through a control function to obtain an intermediate result, and linearly weighting the intermediate result to obtain the greenhouse control parameters;

[0009] The greenhouse control parameters are used to control the operating status of the greenhouse environment control equipment.

[0010] Optionally, obtaining real-time data on greenhouse temperature, humidity, light, and carbon dioxide concentration includes:

[0011] By installing multiple temperature sensors, humidity sensors, light sensors and carbon dioxide concentration sensors in the greenhouse, real-time data on temperature, humidity, light and carbon dioxide concentration in the greenhouse can be obtained.

[0012] Optionally, the real-time data of temperature, humidity, light, and carbon dioxide concentration are processed to obtain greenhouse environmental parameters, including:

[0013] The real-time data of temperature, humidity, light and carbon dioxide concentration are standardized to obtain greenhouse environmental parameters, wherein the standardization includes deleting duplicate or redundant data and interpolating and filling missing data.

[0014] Optionally, the greenhouse environmental parameters are input into a greenhouse environmental control model for processing to obtain greenhouse control parameters, including:

[0015] The greenhouse environmental parameters are combined according to the time of collection to obtain an input vector.

[0016] The input vector is input into a greenhouse environment control model for processing to obtain greenhouse control parameters.

[0017] Optionally, the greenhouse environment control model is trained through the following process:

[0018] Obtaining greenhouse environment historical data and training set data of historical operating status parameters of greenhouse environment control equipment;

[0019] Performing feature extraction processing on the training set data to obtain multiple input vectors;

[0020] Inputting the input vector into the input layer of the greenhouse environment control model;

[0021] The output of the input layer is input into multiple intermediate layers of the greenhouse environment control model for local response processing to obtain multiple intermediate layer outputs;

[0022] Inputting the outputs of the multiple intermediate layers into the output layer of the greenhouse environment control model for linear weighted processing to obtain the output of the network;

[0023] Get the error between the network output and each sample in the training set;

[0024] The multiple weight values ​​in the middle layer are increased or decreased until the error is within a preset range, thereby obtaining the greenhouse environment control model.

[0025] Optionally, the greenhouse environment control model processes the input vector through a control function to obtain an intermediate result, and linearly weights the intermediate result to obtain a greenhouse control parameter, including:

[0026] The greenhouse environment control model is controlled by the following function:

[0027]

[0028] Processing the input vector to obtain a first intermediate result;

[0029] pass:

[0030]

[0031] Get the error of the intermediate results;

[0032] pass:

[0033]

[0034] Correct the weight to obtain the modified positive weight;

[0035] According to the modified positive weight, the input vector is processed again to obtain a second intermediate result;

[0036] pass:

[0037]

[0038] Get greenhouse control parameters;

[0039] in, is the first intermediate result, g(x) is the control function, and g(x)=(1+e -x ) -1 , X i is the i-th input vector; Q ij is the initial weight; E j is the error of the intermediate result, T j is the expected output value of the j-th input vector; Q' ij is the modified weight; λ is the preset learning efficiency value; Y k is the kth greenhouse control parameter; is the second intermediate result, n is the number of intermediate layers, and k is the number of network output layers.

[0040] Optionally, the method for determining greenhouse environmental parameters further includes:

[0041] generating a pulse control signal according to the greenhouse control parameter;

[0042] According to the pulse control signal, the operating state of the greenhouse environment control equipment is controlled.

[0043] An embodiment of the present invention further provides a device for determining greenhouse environmental parameters, comprising:

[0044] Acquisition module, used to obtain real-time data of greenhouse temperature, humidity and light;

[0045] A processing module is used to process the real-time data of temperature, humidity and light to obtain greenhouse environmental parameters; the greenhouse environmental parameters are input into a greenhouse environmental control model for processing to obtain greenhouse control parameters; the greenhouse environmental control model processes the input vector through a control function to obtain an intermediate result, and linearly weights the intermediate result to obtain greenhouse control parameters; the greenhouse control parameters are used to control the operating state of the greenhouse environmental control equipment.

[0046] An embodiment of the present invention further provides a computing device, comprising: a processor and a memory storing a computer program, wherein the computer program executes the above method when executed by the processor.

[0047] An embodiment of the present invention further provides a computer-readable storage medium storing instructions, which, when executed on a computer, enable the computer to execute the above method.

[0048] The above solution of the present invention includes at least the following beneficial effects:

[0049] The solution of the present invention obtains real-time data on temperature, humidity, light, and carbon dioxide concentration in a greenhouse; processes the real-time data on temperature, humidity, light, and carbon dioxide concentration to obtain greenhouse environmental parameters; inputs the greenhouse environmental parameters into a greenhouse environmental control model for processing to obtain greenhouse control parameters; the greenhouse environmental control model processes the input vector through a control function to obtain an intermediate result, and linearly weights the intermediate result to obtain greenhouse control parameters; the greenhouse control parameters are used to control the operating state of the greenhouse environmental control equipment, thereby realizing timely action of the control equipment based on real-time monitoring of the greenhouse environmental parameters, improving the adjustment accuracy of the greenhouse temperature and humidity, and enhancing the greenhouse environmental control effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 is a flow chart of a method for determining greenhouse environmental parameters provided by an embodiment of the present invention;

[0051] Figure 2 is a schematic diagram of the architecture of a greenhouse environment control model in an embodiment of the present invention;

[0052] Figure 3 is a schematic diagram of the thermal area of ​​a greenhouse provided by an embodiment of the present invention;

[0053] Figure 4 This is a temperature control effect diagram of the method for determining greenhouse environmental parameters provided by an embodiment of the present invention;

[0054] Figure 5 is a structural diagram of a device for determining greenhouse environmental parameters provided by an embodiment of the present invention;

[0055] Figure 6 is a schematic diagram of the structure of a computing device provided by an embodiment of the present invention;

[0056] Among them, 1. Heating system; 2. Crop growing area; 3. Greenhouse side windows and blackout curtains; 4. Greenhouse top; 5. Greenhouse external environment. DETAILED DESCRIPTION

[0057] Exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present invention are shown in the accompanying drawings, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present invention and to fully convey the scope of the present invention to those skilled in the art.

[0058] like Figure 1 As shown, an embodiment of the present invention provides a method for determining greenhouse environmental parameters, including:

[0059] Step 11, obtaining real-time data on temperature, humidity, light, and carbon dioxide concentration in the greenhouse;

[0060] Step 12, processing the real-time data of temperature, humidity, light, and carbon dioxide concentration to obtain greenhouse environmental parameters;

[0061] Step 13: Inputting the greenhouse environmental parameters into a greenhouse environmental control model for processing to obtain greenhouse control parameters; the greenhouse environmental control model processes the input vector using a control function to obtain an intermediate result, and linearly weighting the intermediate result to obtain the greenhouse control parameters;

[0062] Step 14: The greenhouse control parameters are used to control the operating state of the greenhouse environment control equipment.

[0063] In this embodiment, in order to achieve precise control of greenhouse environmental parameters, it is first necessary to obtain real-time data on the greenhouse's temperature, humidity, light, and carbon dioxide concentration. This can be achieved by arranging multiple temperature sensors, humidity sensors, light sensors, and carbon dioxide concentration sensors in the greenhouse. The temperature sensor and humidity sensor can be digital temperature and humidity sensors, such as DHT11 and DHT22, which have integrated temperature and humidity measurement functions and can communicate with the controller through a digital interface to obtain real-time temperature and humidity data. The light sensor can be a photoresistor or a digital light sensor, such as BH1750, which measures changes in light intensity, converts it into an electrical signal output, and connects to the controller to achieve light data collection. Arranging multiple temperature and humidity sensors and light sensors in different areas of the greenhouse can comprehensively collect greenhouse environmental parameters.

[0064] After obtaining the real-time data of greenhouse temperature, humidity, light, and carbon dioxide concentration, it is necessary to process it to obtain greenhouse environmental parameters. This is because the data directly obtained by the sensor may contain duplication, missing or abnormal values. Therefore, it is necessary to perform necessary standardization before calculation to remove noise and outliers. The standardized data are combined together to form an input vector.

[0065] Inputting an input vector into a greenhouse environment control model for processing to obtain greenhouse control parameters; the greenhouse environment control model processes the input vector using a control function to obtain an intermediate result, and linearly weighting the intermediate result to obtain the greenhouse control parameters;

[0066] After obtaining the greenhouse control parameters, a control signal is formed according to its value to drive the actuator to perform corresponding control actions, such as turning on or off the ventilation equipment, starting or stopping the humidification equipment, etc.

[0067] This technical solution controls the operating status of greenhouse environmental control equipment based on greenhouse control parameters. Based on real-time collected temperature, humidity, and light data, it automatically determines whether the greenhouse needs cooling or humidification. Based on the judgment results, it executes the corresponding control strategy, achieving intelligent management of the greenhouse environment, providing optimal environmental conditions for crop growth, and improving crop yield and quality. At the same time, through data accumulation and analysis, the control model and control strategy are continuously optimized, achieving adaptive and intelligent greenhouse environmental control, reducing manual intervention, and improving management efficiency.

[0068] In an optional embodiment, the embodiment of the present invention provides that step 12 may include:

[0069] Step 121 , normalizing the real-time data of temperature, humidity, light and carbon dioxide concentration to obtain greenhouse environmental parameters, wherein the normalization includes deleting duplicate or redundant data and interpolating missing data.

[0070] In this embodiment, after obtaining the real-time data of greenhouse temperature, humidity, light, and carbon dioxide concentration, it is necessary to perform standardization processing on them to obtain greenhouse environmental parameters. This is because the data directly obtained by the sensors may contain duplication, missing data, or abnormal values. Therefore, necessary standardization processing is required before calculation to remove noise and abnormal values. Specifically, the standardization processing includes deleting duplicate or redundant data of the operating parameters and interpolating and filling missing data. The processed data is stored in a database to obtain a standard database, and the data storage format and structure are determined for subsequent analysis and application.

[0071] Among them, the processing of missing values ​​includes: identifying missing values ​​in the data; filling missing values ​​using methods such as mean, median, and interpolation (such as linear interpolation and polynomial interpolation);

[0072] Outlier processing includes: identifying outliers in the data, usually based on IQR (interquartile range) or other statistical methods; deciding whether to retain, replace, or delete outliers based on domain knowledge or statistical methods;

[0073] Data standardization includes: standardizing the data according to Z = (X-μ) / σ; where X is the value of the original data or the original sample; μ is the average value or mean of the original data; σ is the standard deviation of the original data; and Z is the new value obtained after standardization.

[0074] The data normalization process includes: normalizing the data according to x'=[x-min(x)] / [max(x)-min(x)]; where x is the value of the original data or original sample; min(x) is the minimum value in the data set; max(x) is the maximum value in the data set; and x' is the new value obtained after normalization.

[0075] In an optional embodiment, the embodiment of the present invention provides that step 13 may include:

[0076] Step 131, the greenhouse environmental parameters are combined according to the collection time to obtain an input vector,

[0077] Step 132: Input the input vector into the greenhouse environment control model for processing to obtain greenhouse control parameters.

[0078] In this embodiment, the greenhouse environmental parameters are first merged and processed according to the time of collection to obtain an input vector; the input vector is then input into a greenhouse environmental control model for processing to obtain greenhouse control parameters; wherein the greenhouse environmental control model can be trained based on training set data including greenhouse temperature, humidity and light historical data and greenhouse environmental control equipment operating status historical parameters; Figure 2 As shown in Figure 1, the greenhouse environment control model consists of m input layers, n intermediate layers, and k output layers. The training process includes:

[0079] Step 21, obtaining greenhouse environment historical data and training set data of historical operating status parameters of greenhouse environment control equipment;

[0080] Step 22: performing feature extraction processing on the training set data to obtain multiple input vectors;

[0081] Step 23, inputting the input vector into the input layer of the greenhouse environment control model;

[0082] Step 24, inputting the output of the input layer into multiple hidden layers of the greenhouse environment control model for local response processing to obtain multiple hidden layer outputs;

[0083] Step 25, inputting the multiple hidden layer outputs into the output layer of the greenhouse environment control model for linear weighted processing to obtain the network output;

[0084] Step 26, obtaining the error between the network output and each sample in the training set;

[0085] Step 27: Increase or decrease the multiple weight values ​​in the hidden layer until the error is within a preset range, thereby obtaining the greenhouse environment control model.

[0086] In this embodiment, the greenhouse environment historical data includes: greenhouse temperature, humidity, light and carbon dioxide concentration historical data; the greenhouse environment control equipment operating status historical parameters include: heating equipment historical operating data, spray cooling equipment historical operating data, heating equipment historical operating data, drying and dehumidification equipment historical operating data;

[0087] Arrange the above parameters to obtain multiple learning samples; the i-th learning sample can be expressed as (X i , t i ), where X i is a vector consisting of 4 elements, X i =[a i1 ,a i2 ,a i3 ,a i4 ], a i1 is the i-th temperature history data, ai2 is the i-th humidity historical data, a i3 is the i-th illumination history data, a i4 is the historical data of carbon dioxide concentration at the i-th time, X i The data of each element in t are obtained in the same time interval; i is a vector consisting of 4 elements, t i =[b i1 ,b i2 ,b i3 ,b i4 ], b i1 is the historical operating data of the heating equipment, b i2 is the historical operation data of the i-th spray cooling equipment, b i3 is the historical operating data of the i-th heating equipment, b i4 is the historical operation data of the i-th drying and dehumidification equipment;

[0088] For the i-th learning sample (X i , t i ), through the control function: Compute the middle layer output of the greenhouse environmental control model Then pass: Calculate the error of the intermediate result; then according to the error of the intermediate result, through: The weight matrix is ​​modified, that is, the modified positive weights are obtained; the input vector is processed again according to the modified positive weights to obtain a second intermediate result; according to the second intermediate result, by: Get greenhouse control parameters;

[0089] in, is the first intermediate result, g(x) is the control function, and g(x)=(1+e -x ) -1 , X i is the i-th input vector; Q ij is the initial weight; E j is the error of the intermediate result, T j is the expected output value of the j-th input vector; Q' ij is the modified weight; λ is the preset learning efficiency value; Y k is the kth greenhouse control parameter; is the second intermediate result, n is the number of intermediate layers; k is the number of network output layers;

[0090] Initial weight Q ij Use a random number generator to generate the number in the range of [-0.5, 0.5], and the learning efficiency λ is 0.64;

[0091] In this embodiment, the error between the output of the network and each sample in the training set is calculated; the number of hidden layers is increased or decreased according to the distance between each sample and each hidden layer and the error, and multiple weight values ​​in the hidden layer are adjusted to obtain an insulation parameter model with a final error within a preset range.

[0092] In an optional embodiment, the embodiment of the present invention provides that step 14 may include:

[0093] Step 141, generating a pulse control signal according to the greenhouse control parameter;

[0094] Step 142: Control the operating state of the greenhouse environment control device according to the pulse control signal.

[0095] In this embodiment, a pulse control signal is generated based on the various greenhouse control parameters obtained, and the operating state of the greenhouse environment control equipment is controlled based on the pulse control signal. For example, when the greenhouse temperature is lower than the set value, the algorithm will calculate the heating power that needs to be increased based on the operating data of the heating equipment and convert it into a corresponding pulse control signal. The frequency and duty cycle of this signal (i.e., the ratio of the high-level time of the pulse signal in one cycle to the entire cycle time) will be adjusted according to specific control requirements. For spray cooling equipment, if the temperature is higher than the set value, the control system will generate an appropriate pulse control signal to adjust the frequency and duration of the spraying based on factors such as the difference between the current temperature and the set value and the operating data of the spray equipment. Similarly, for drying and dehumidification equipment, a pulse control signal will be generated based on humidity data and equipment operating data to accurately control the operation of the equipment.

[0096] After the heating device receives the pulse control signal, its control module will adjust the operating status of the heating device according to the frequency and duty cycle of the signal; if the signal indicates that the heating power needs to be increased, the control module may increase the current or voltage of the heating element, so that the heating device can operate at a higher power and increase the greenhouse temperature; after the control unit of the spraying device receives the pulse control signal, it controls the opening and closing time and spraying intensity of the nozzle according to the signal parameters; for example, if the signal requires an increase in the spraying frequency, the control unit will shorten the closing time interval of the nozzle, so that the spraying is carried out more frequently to achieve a better cooling effect; after the drying and dehumidification device receives the pulse control signal, the control module will adjust the operating mode of the device, such as speeding up the air circulation speed, increasing the working intensity of the dehumidifier, etc.; if the signal indicates that the humidity needs to be reduced, the device will increase the dehumidification intensity and reduce the humidity of the greenhouse by absorbing or condensing water vapor.

[0097] A specific embodiment of the method for determining greenhouse environmental parameters provided by the embodiment of the present invention is as follows:

[0098] Step 1: Obtain real-time data on greenhouse temperature, humidity, light intensity, and carbon dioxide concentration;

[0099] The greenhouse used for the experiment is a medium-sized 108m 2 , its thermal region model is as follows Figure 3 As shown in Figure 1, considering the coupling effect of various parameters in the greenhouse, the greenhouse is divided into five sub-areas. Relevant sensors are set up for each area to collect data. The sensor types and collected data categories are shown in Table 1.

[0100] Table 1 Data collection categories and quantities for each area of ​​the greenhouse

[0101]

[0102] Obtaining real-time data on greenhouse temperature, humidity, light, and carbon dioxide concentration; this real-time data can be obtained through multiple sensors installed in the greenhouse and used to determine whether the greenhouse needs to be cooled or humidified;

[0103] Step 2: Processing the real-time data of temperature, humidity, light, and carbon dioxide concentration to obtain greenhouse environmental parameters;

[0104] Standardizing the real-time data of temperature, humidity, light, and carbon dioxide concentration to remove noise and outliers; combining the standardized data to obtain greenhouse environmental parameters;

[0105] Step 3, inputting the greenhouse environmental parameters into a greenhouse environmental control model for processing to obtain greenhouse control parameters;

[0106] The model has four inputs: the current temperature, humidity, light, and real-time data of the greenhouse's carbon dioxide concentration. It also has four outputs: control signals for four actuators. The model has a three-layer structure: one input layer, one middle layer, and one output layer. The input layer has four neurons, corresponding to the four inputs; the output layer has four neurons, corresponding to the control signals for the four actuators.

[0107] Step 4: Control the operating state of the greenhouse environment control equipment according to the greenhouse control parameters.

[0108] After obtaining the greenhouse control parameters, a pulse control signal is generated, and the operation of the greenhouse environment control device is controlled according to the pulse control signal as an input parameter of the power amplifier device;

[0109] Comparison of temperature control effects using PID control and greenhouse environment control model Figure 4As shown in the figure, the results show that the indoor temperature and humidity changes are smoother when the greenhouse environment control model is used than when the conventional PID control is used. This shows that the model method effectively avoids the hysteresis and overshoot caused by the large inertia and hysteresis of the entire control system, and the system stability is enhanced.

[0110] The above-mentioned embodiments of the present invention control the operating status of the greenhouse environment control equipment according to the greenhouse control parameters, realize the timely operation of the control equipment based on real-time monitoring of the greenhouse environment parameters, improve the adjustment accuracy of the greenhouse temperature and humidity, and enhance the greenhouse environment control effect.

[0111] like Figure 5 As shown, an embodiment of the present invention provides a device 50 for determining greenhouse environmental parameters, comprising:

[0112] Acquisition module 51, used to obtain real-time data of temperature, humidity and light intensity in the greenhouse;

[0113] The processing module 52 is used to process the real-time data of temperature, humidity and light to obtain greenhouse environmental parameters; input the greenhouse environmental parameters into the greenhouse environmental control model for processing to obtain greenhouse control parameters; the greenhouse environmental control model processes the input vector through a control function to obtain an intermediate result, and linearly weights the intermediate result to obtain greenhouse control parameters; the greenhouse control parameters are used to control the operating state of the greenhouse environmental control equipment.

[0114] Optionally, the acquisition module 51 is specifically configured to:

[0115] By installing multiple temperature sensors, humidity sensors, light sensors and carbon dioxide concentration sensors in the greenhouse, real-time data on temperature, humidity, light and carbon dioxide concentration in the greenhouse can be obtained.

[0116] Optionally, the processing module 52 is specifically configured to:

[0117] The real-time data of temperature, humidity, light and carbon dioxide concentration are standardized to obtain greenhouse environmental parameters, wherein the standardization includes deleting duplicate or redundant data and interpolating and filling missing data.

[0118] Optionally, the processing module 52 is further specifically configured to:

[0119] The greenhouse environmental parameters are combined according to the time of collection to obtain an input vector.

[0120] The input vector is input into a greenhouse environment control model for processing to obtain greenhouse control parameters.

[0121] Optionally, the greenhouse environment control model is trained through the following process:

[0122] Obtaining greenhouse environment historical data and training set data of historical operating status parameters of greenhouse environment control equipment;

[0123] Performing feature extraction processing on the training set data to obtain multiple input vectors;

[0124] Inputting the input vector into the input layer of the greenhouse environment control model;

[0125] The output of the input layer is input into multiple intermediate layers of the greenhouse environment control model for local response processing to obtain multiple intermediate layer outputs;

[0126] Inputting the outputs of the multiple intermediate layers into the output layer of the greenhouse environment control model for linear weighted processing to obtain the output of the network;

[0127] Get the error between the network output and each sample in the training set;

[0128] The multiple weight values ​​in the middle layer are increased or decreased until the error is within a preset range, thereby obtaining the greenhouse environment control model.

[0129] Optionally, the greenhouse environment control model processes the input vector through a control function to obtain an intermediate result, and linearly weights the intermediate result to obtain a greenhouse control parameter, including:

[0130] The greenhouse environment control model is controlled by the following function:

[0131]

[0132] Processing the input vector to obtain a first intermediate result;

[0133] pass:

[0134]

[0135] Get the error of the intermediate results;

[0136] pass:

[0137]

[0138] Correct the weight to obtain the modified positive weight;

[0139] According to the modified positive weight, the input vector is processed again to obtain a second intermediate result;

[0140] pass:

[0141]

[0142] Get greenhouse control parameters;

[0143] in, is the first intermediate result, g(x) is the control function, and g(x)=(1+e -x ) -1 , X i is the i-th input vector; Q ij is the initial weight; E j is the error of the intermediate result, T j is the expected output value of the j-th input vector; Q' ij is the modified weight; λ is the preset learning efficiency value; Y k is the kth greenhouse control parameter; is the second intermediate result, n is the number of intermediate layers, and k is the number of network output layers.

[0144] Optionally, the processing module 52 is further specifically configured to:

[0145] generating a pulse control signal according to the greenhouse control parameter;

[0146] According to the pulse control signal, the operating state of the greenhouse environment control equipment is controlled.

[0147] It should be noted that this device is a device corresponding to the above method, and all implementation methods in the above method embodiment are applicable to this embodiment and can achieve the same technical effect.

[0148] like Figure 6 As shown, an embodiment of the present invention further provides a computing device 60, comprising a processor 61, a memory 62, and a program or instruction stored in the memory 62 and executable on the processor 61. When executed by the processor 61, the program or instruction implements the various processes of the embodiment of the method for determining greenhouse environmental parameters described above, and can achieve the same technical effects. To avoid repetition, the details are not described here. It should be noted that the computing device in the embodiment of the present invention includes the mobile electronic device and the non-mobile electronic device described above.

[0149] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present invention.

[0150] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0151] In the embodiments provided by the present invention, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be through some interface, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0152] Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0153] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0154] Stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or the portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the method of the present invention. The aforementioned storage medium includes: USB flash drives, mobile hard drives, ROM, RAM, magnetic disks, optical disks, and other media that can store program code.

[0155] In addition, it should be noted that, in the apparatus and method of the present invention, it is obvious that each component or each step can be decomposed and / or recombined. These decompositions and / or recombinations should be regarded as equivalent schemes of the present invention. Moreover, the steps of performing the above-mentioned series of processing can naturally be performed in chronological order according to the order of description, but it is not necessary to perform them in chronological order, and some steps can be performed in parallel or independently of each other. For those of ordinary skill in the art, it will be understood that all or any steps or components of the method and apparatus of the present invention can be implemented in any computing device (including processors, storage media, etc.) or a network of computing devices in hardware, firmware, software or a combination thereof, which can be achieved by those of ordinary skill in the art using their basic programming skills after reading the description of the present invention.

[0156] Therefore, the purpose of the present invention can also be achieved by running a program or a group of programs on any computing device. The computing device can be a well-known general-purpose device. Therefore, the purpose of the present invention can also be achieved simply by providing a program product containing program code for implementing the method or device. That is to say, such a program product also constitutes the present invention, and the storage medium storing such a program product also constitutes the present invention. Obviously, the storage medium can be any well-known storage medium or any storage medium developed in the future. It should also be pointed out that in the device and method of the present invention, it is obvious that each component or each step can be decomposed and / or recombined. These decompositions and / or recombinations should be regarded as equivalent schemes of the present invention. In addition, the steps of performing the above-mentioned series of processing can naturally be performed in chronological order according to the order of description, but do not necessarily need to be performed in chronological order. Certain steps can be performed in parallel or independently of each other.

[0157] The above is a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for determining greenhouse environmental parameters, characterized in that: include: Obtain real-time data on greenhouse temperature, humidity, light, and carbon dioxide concentration; Processing the real-time data of temperature, humidity, light, and carbon dioxide concentration to obtain greenhouse environmental parameters; Inputting the greenhouse environmental parameters into a greenhouse environmental control model for processing to obtain greenhouse control parameters; the greenhouse environmental control model processes the input vector through a control function to obtain an intermediate result, and linearly weighting the intermediate result to obtain the greenhouse control parameters; The greenhouse control parameters are used to control the operating status of the greenhouse environment control equipment.

2. The method for determining greenhouse environmental parameters according to claim 1, characterized in that: The acquisition of real-time data on greenhouse temperature, humidity, light, and carbon dioxide concentration includes: By installing multiple temperature sensors, humidity sensors, light sensors and carbon dioxide concentration sensors in the greenhouse, real-time data on temperature, humidity, light and carbon dioxide concentration in the greenhouse can be obtained.

3. The method for determining greenhouse environmental parameters according to claim 1, characterized in that: The real-time data of temperature, humidity, light, and carbon dioxide concentration are processed to obtain greenhouse environmental parameters, including: The real-time data of temperature, humidity, light and carbon dioxide concentration are standardized to obtain greenhouse environmental parameters, wherein the standardization includes deleting duplicate or redundant data and interpolating and filling missing data.

4. The method for determining greenhouse environmental parameters according to claim 1, characterized in that: The greenhouse environmental parameters are input into the greenhouse environmental control model for processing to obtain greenhouse control parameters, including: The greenhouse environmental parameters are combined according to the time of collection to obtain an input vector. The input vector is input into a greenhouse environment control model for processing to obtain greenhouse control parameters.

5. The method for determining greenhouse environmental parameters according to claim 1, characterized in that: The greenhouse environment control model is trained through the following process: Obtaining greenhouse environment historical data and training set data of historical operating status parameters of greenhouse environment control equipment; Performing feature extraction processing on the training set data to obtain multiple input vectors; Inputting the input vector into the input layer of the greenhouse environment control model; The output of the input layer is input into multiple intermediate layers of the greenhouse environment control model for local response processing to obtain multiple intermediate layer outputs; Inputting the outputs of the multiple intermediate layers into the output layer of the greenhouse environment control model for linear weighted processing to obtain the output of the network; Get the error between the network output and each sample in the training set; The multiple weight values ​​in the middle layer are increased or decreased until the error is within a preset range, thereby obtaining the greenhouse environment control model.

6. The method for determining greenhouse environmental parameters according to claim 1, characterized in that: The greenhouse environment control model processes the input vector through the control function to obtain an intermediate result, and linearly weights the intermediate result to obtain the greenhouse control parameters, including: The greenhouse environment control model is controlled by the following function: Processing the input vector to obtain a first intermediate result; pass: Get the error of the intermediate results; pass: Correct the weight to obtain the modified positive weight; According to the modified positive weight, the input vector is processed again to obtain a second intermediate result; pass: Get greenhouse control parameters; in, is the first intermediate result, g(x) is the control function, and g(x)=(1+e -x ) -1 , X i is the i-th input vector; Q ij is the initial weight; E j is the error of the intermediate result, T j is the expected output value of the j-th input vector; Q' ij is the modified weight; λ is the preset learning efficiency value; Y k is the kth greenhouse control parameter; is the second intermediate result, n is the number of intermediate layers, and k is the number of network output layers.

7. The method for determining greenhouse environmental parameters according to claim 1, characterized in that: Also includes: generating a pulse control signal according to the greenhouse control parameter; According to the pulse control signal, the operating state of the greenhouse environment control equipment is controlled.

8. A device for determining greenhouse environmental parameters, characterized in that: include: Acquisition module, used to obtain real-time data of greenhouse temperature, humidity and light; A processing module is used to process the real-time data of temperature, humidity and light to obtain greenhouse environmental parameters; the greenhouse environmental parameters are input into a greenhouse environmental control model for processing to obtain greenhouse control parameters; the greenhouse environmental control model processes the input vector through a control function to obtain an intermediate result, and linearly weights the intermediate result to obtain greenhouse control parameters; the greenhouse control parameters are used to control the operating state of the greenhouse environmental control equipment.

9. A computing device, characterized in that include: A processor and a memory storing a computer program, wherein when the computer program is executed by the processor, the method according to any one of claims 1 to 7 is performed.

10. A computer-readable storage medium, characterized in that The device stores instructions, which, when executed on a computer, enable the computer to execute the method according to any one of claims 1 to 7.

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