CN115689210A - Water and electricity adjusting method and device based on private data of water and electricity consumption and electronic equipment - Google Patents
Water and electricity adjusting method and device based on private data of water and electricity consumption and electronic equipment Download PDFInfo
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Abstract
The embodiment of the disclosure discloses a hydropower adjustment method, a hydropower adjustment device and electronic equipment based on private data of water consumption and electricity utilization. One embodiment of the method comprises: acquiring an electricity utilization sample and a water utilization sample corresponding to each power node in a target area to obtain an electricity utilization sample set and a water utilization sample set; training an initial power node user number recognition model based on the power consumption sample set and the water consumption sample set to obtain the trained initial power node user number recognition model serving as a power node user number recognition model; collecting power utilization information and water utilization information of a target power node in a preset time period; inputting the electricity utilization information and the water utilization information into the power node user number identification model to obtain the power node user identification number; and adjusting the water supply amount and the power supply load of the target power node according to the power node user identification number. The embodiment improves the timeliness of the detection and shortens the detection time.
Description
Technical Field
The embodiment of the disclosure relates to the technical field of computers, in particular to a water and electricity adjustment method and device based on water and electricity utilization private data and electronic equipment.
Background
In order to judge whether a unit area (cell/floor/house) has newly added personnel, the inspection and monitoring of the newly added personnel is delayed, the newly added personnel are easy to miss and the epidemic prevention effect is influenced only by the modes of self-reporting and the home-going investigation of epidemic prevention personnel. At present, whether a unit area has a newly added person is judged, and a commonly adopted mode is as follows: and checking through the check of epidemic prevention personnel.
However, the following technical problems generally exist in the above manner:
firstly, epidemic prevention personnel check at home, so that timeliness is low and check time is long;
secondly, the actual water consumption and the electricity consumption of the unit area are not judged, so that the accuracy of the detected number of the personnel in the unit area is low, and when the detected number of the personnel is larger than the actual number of the personnel, more epidemic prevention materials are easily provided, so that the waste of the epidemic prevention materials is caused;
thirdly, the relationship between the actual water consumption and the electricity consumption of the unit area is not comprehensively considered, so that the accuracy of the detected number of the personnel in the unit area is low, and when the detected number of the personnel is smaller than the actual number of the personnel, the shortage of the water supply amount and the power supply load is easily caused.
The above information disclosed in this background section is only for enhancement of understanding of the background of the inventive concept and, therefore, it may contain information that does not form the prior art that is already known to a person of ordinary skill in the art in this country.
Disclosure of Invention
This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the detailed description. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter.
Some embodiments of the present disclosure propose hydropower adjustment methods, apparatuses, electronic devices, and computer-readable media based on water-use electricity utilization privacy data to solve one or more of the technical problems mentioned in the background section above.
In a first aspect, some embodiments of the present disclosure provide a method of regulating water and electricity based on private data of water usage and electricity usage, the method comprising: acquiring an electricity utilization sample and a water utilization sample corresponding to each power node in a target area to obtain an electricity utilization sample set and a water utilization sample set; training an initial power node user number recognition model based on the power utilization sample set and the water utilization sample set to obtain the trained initial power node user number recognition model as a power node user number recognition model; acquiring power utilization information and water utilization information of a target power node in a preset time period; inputting the electricity utilization information and the water utilization information into the power node user number identification model to obtain the power node user identification number; and adjusting the water supply amount and the power supply load of the target power node according to the power node user identification number.
In a second aspect, some embodiments of the present disclosure provide a hydroelectric power adjustment apparatus based on private data of electricity usage with water, the apparatus comprising: the acquisition unit is configured to acquire an electricity utilization sample and a water utilization sample corresponding to each power node in a target area to obtain an electricity utilization sample set and a water utilization sample set; the training unit is configured to train an initial power node user number recognition model based on the power consumption sample set and the water consumption sample set, and the trained initial power node user number recognition model is obtained and serves as a power node user number recognition model; the acquisition unit is configured to acquire power utilization information and water utilization information of the target power node within a preset time period; an input unit configured to input the electricity consumption information and the water consumption information into the power node user number identification model to obtain a power node user identification number; and an adjusting unit configured to adjust the water supply amount and the power supply load of the target power node according to the power node user identification number.
In a third aspect, some embodiments of the present disclosure provide an electronic device, comprising: one or more processors; a storage device having one or more programs stored thereon, which when executed by one or more processors, cause the one or more processors to implement the method described in any of the implementations of the first aspect.
In a fourth aspect, some embodiments of the disclosure provide a computer-readable medium on which a computer program is stored, wherein the computer program, when executed by a processor, implements the method described in any implementation manner of the first aspect.
The above embodiments of the present disclosure have the following advantages: through the water and electricity adjusting method based on the water and electricity private data of some embodiments of the disclosure, the timeliness of the inspection is improved, and the checking time is shortened. Specifically, the reason why the check time is long is that: the timeliness is lower through the checking of epidemic prevention personnel. Based on this, according to the hydropower adjustment method based on private data of power consumption by water, firstly, a power consumption sample and a water consumption sample corresponding to each power node in a target area are obtained, and a power consumption sample set and a water consumption sample set are obtained. Therefore, data support is provided for training the power node user number identification model. Secondly, training an initial power node user number recognition model based on the power consumption sample set and the water consumption sample set, and obtaining the trained initial power node user number recognition model as a power node user number recognition model. Therefore, a model for identifying the number of people in a unit area (power node) can be trained according to the power utilization samples and the water utilization samples corresponding to the power node. Therefore, the number of persons in a unit area can be checked from the electricity consumption information and the water consumption information of the unit area (power node). And then, collecting the electricity utilization information and the water utilization information of the target power node in a preset time period. And then, inputting the electricity utilization information and the water utilization information into the power node user number identification model to obtain the power node user identification number. Thus, the number of persons in the unit area (power node) can be identified from the electricity consumption information and the water consumption information of the single power node (target power node). And finally, adjusting the water supply amount and the power supply load of the target power node according to the power node user identification number. Thus, the number of persons in a unit area (power node) can be directly detected from the amount of electricity and water used. The detection timeliness is improved, and the checking time is shortened.
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The above and other features, advantages and aspects of various embodiments of the present disclosure will become more apparent by referring to the following detailed description when taken in conjunction with the accompanying drawings. Throughout the drawings, the same or similar reference numbers refer to the same or similar elements. It should be understood that the drawings are schematic and that elements and components are not necessarily drawn to scale.
FIG. 1 is a flow diagram of some embodiments of a water and electricity regulation method based on water usage electricity usage privacy data according to the present disclosure;
FIG. 2 is a schematic block diagram of some embodiments of a water and electricity regulation device based on water usage electricity usage privacy data according to the present disclosure;
FIG. 3 is a schematic block diagram of an electronic device suitable for use in implementing some embodiments of the present disclosure.
Detailed Description
Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the disclosure are shown in the drawings, it is to be understood that the disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the disclosure are for illustration purposes only and are not intended to limit the scope of the disclosure.
It should be noted that, for convenience of description, only the portions related to the present invention are shown in the drawings. The embodiments and features of the embodiments in the present disclosure may be combined with each other without conflict.
It should be noted that the terms "first", "second", and the like in the present disclosure are only used for distinguishing different devices, modules or units, and are not used for limiting the order or interdependence of the functions performed by the devices, modules or units.
It is noted that references to "a" or "an" in this disclosure are intended to be illustrative rather than limiting, and that those skilled in the art will appreciate that references to "one or more" are intended to be exemplary and not limiting unless the context clearly indicates otherwise.
The names of messages or information exchanged between devices in the embodiments of the present disclosure are for illustrative purposes only, and are not intended to limit the scope of the messages or information.
The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
Fig. 1 is a flow diagram of some embodiments of a water and electricity regulation method based on water usage electricity usage privacy data according to the present disclosure. A flow 100 of some embodiments of a hydroelectric regulation method based on water usage electricity privacy data in accordance with the present disclosure is shown. The hydropower adjustment method based on the private data of water consumption and electricity consumption comprises the following steps:
In some embodiments, an executing subject (e.g., a server) of the hydropower adjustment method based on the private data of water consumption and electricity consumption can obtain the electricity consumption sample and the water consumption sample corresponding to each power node in the target area from the terminal device through a wired connection or a wireless connection, so as to obtain the electricity consumption sample set and the water consumption sample set. Here, the target area may be a previously divided area. For example, the target area may be a city, district, county, etc. A power node may refer to a power node of a certain unit area. For example, a power node may characterize an electricity meter node for a unit area (cell).
In practice, the executing body may obtain the electricity and water usage samples corresponding to each power node in the target area by:
the first step is to obtain the user number sequence, the total number of users and the power node identification corresponding to the power node. The user number may refer to a house number of a unit area corresponding to the power node. The power node identification may characterize the meter identification of the unit area.
And secondly, acquiring the power consumption sequence of the user number sequence in a first historical time period. And the user number in the user number sequence corresponds to the electricity consumption in the electricity consumption sequence. Here, the duration of the first history period may be one month. The power usage may represent a total power usage of one month by a user number.
And thirdly, generating a power consumption sample according to the user number sequence, the total number of the users, the power node identification and the power consumption sequence.
In practice, the above-mentioned third step may comprise the following sub-steps:
and a first substep of determining a total amount of electricity to be used as a sum of the individual amounts of electricity included in the above-described electricity usage series.
And a second substep, determining the ratio of the total power consumption to the total number of the users as the average human power consumption.
And a third substep, acquiring a historical electricity consumption sequence of the user number sequence in a second historical time period. And the user numbers in the user number sequence correspond to the historical electricity consumption in the historical electricity consumption sequence. Here, the duration of the second history period may be one week. The historical power usage may represent a total power usage for a week numbered by a user.
And a fourth substep of determining the ratio of the sum of the historical electricity consumptions included in the historical electricity consumption sequence to the target duration as historical average electricity consumption. And the target time length is the time length of the second historical time period.
And a fifth substep of determining a ratio of the current daily power consumption corresponding to the power node to the historical average power consumption as an average daily power consumption ratio.
And a sixth substep of determining a difference between the current daily electricity consumption and a historical daily electricity consumption corresponding to the current daily electricity consumption as a daily electricity consumption difference. Here, the history daily electricity amount corresponding to the current daily electricity amount may refer to a daily electricity amount of a day before the week before the current date.
And a seventh substep of determining the ratio of the difference value of the daily electricity consumption to the historical daily electricity consumption as the same-ratio difference rate of the daily electricity consumption.
And an eighth substep of determining a difference between the current daily electricity consumption and a previous daily electricity consumption of the current daily electricity consumption as a ring-to-day electricity consumption difference.
A ninth substep of determining the ratio of the difference between the ring ratio daily power consumption and the previous day power consumption as the ring ratio difference rate of daily power consumption.
And a tenth sub-step of determining the total number of the users as the power consumption sample labels.
An eleventh substep of combining the user number sequence, the power node identifier, the date type, the per-person power consumption, the average daily power consumption rate, the daily power consumption geometric rate difference, and the power consumption sample label into a power consumption sample corresponding to the power node. Here, combining may refer to merging.
And fourthly, acquiring a user number sequence, a user total number and a hydraulic node identifier corresponding to the electric power node. The hydraulic node identification can represent the water meter identification of a unit area.
And fifthly, acquiring the water consumption sequence of the user number sequence in the first historical time period. And the user number in the user number sequence corresponds to the water consumption in the water consumption sequence. The water usage may represent the total water usage for a month at a customer number.
And sixthly, generating a water consumption sample according to the user number sequence, the total number of the users, the hydraulic node identification and the water consumption sequence.
In practice, the above sixth step may comprise the following sub-steps:
the first sub-step, the sum of the water consumption sequence is determined as the total water consumption.
And the second substep, determining the ratio of the total water consumption to the total user amount as the average human water consumption.
And a third substep, acquiring a historical water consumption sequence of the user number sequence in a second historical time period. And the user number in the user number sequence corresponds to the historical water consumption in the historical water consumption sequence. Here, the duration of the second history period may be one week. The historical water usage may represent a user's total water usage for a week.
And a fourth substep of determining the ratio of the sum of the historical water consumption included in the historical water consumption sequence to the target duration as the historical average water consumption. Wherein the target duration is a duration of the second historical time period.
And a fifth substep of determining the ratio of the current daily water consumption corresponding to the power node to the historical average water consumption as an average daily water consumption ratio.
And a sixth substep of determining the difference between the current daily water usage and the historical daily water usage corresponding to the current daily water usage as the daily water usage difference. Here, the historical daily water amount corresponding to the current daily water amount may be a daily water amount of a day before the current day.
And a seventh substep of determining the ratio of the difference between the daily water consumption and the historical daily water consumption as the same ratio difference of the daily water consumption.
And an eighth substep of determining the difference between the current daily water consumption and the daily water consumption before the current daily water consumption as the difference between the ring-to-ring daily water consumption.
And a ninth substep of determining the ratio of the difference between the daily water consumption of the ring ratio and the daily water consumption of the previous day as the ring ratio difference rate of the daily water consumption.
And a tenth sub-step of determining the total number of the users as a water sample label.
And an eleventh substep of combining the user number sequence, the date type, the average water consumption, the average daily water consumption ratio, the same-ratio difference rate of the daily water consumption, the ring-ratio difference rate of the daily water consumption, and the water sample label into a water sample corresponding to the power node. Combining may refer to merging.
The related content in the above step 101 is taken as an invention point of the present disclosure, thereby solving the technical problem two mentioned in the background art that the epidemic prevention material is wasted. ". The factors causing the waste of epidemic prevention materials are as follows: the actual water consumption and the electricity consumption of the unit area are not judged, so that the accuracy of the number of detected personnel in the unit area is low, and when the number of the detected personnel is larger than the actual number of the personnel, more epidemic prevention materials are easily provided. If the factors are solved, the effect of reducing the waste of epidemic prevention materials can be achieved. To achieve this effect, first, the user number sequence, the total number of users, and the power node identifier corresponding to the power node are obtained. And secondly, acquiring the electricity consumption sequence of the user number sequence in the first historical time period. Thus, the number of persons in the unit area can be detected based on the actual amount of electricity used in the unit area. And then generating an electricity consumption sample according to the user number sequence, the total number of the users, the power node identification and the electricity consumption sequence. Therefore, data support is provided for training the initial power node user number identification model. Thus, the trained model is enabled to identify the number of people in the unit area based on the electricity usage. And then, acquiring a user number sequence, a user total number and a hydraulic node identification corresponding to the electric power node. And then, acquiring the water consumption sequence of the user number sequence in the first historical time period. Therefore, the number of people in the unit area can be detected according to the actual water consumption of the unit area. And finally, generating a water consumption sample according to the user number sequence, the total number of the users, the hydraulic node identification and the water consumption sequence. Therefore, data support is provided for training an initial power node user number identification model. Thus, the trained model can identify the number of people in a unit area according to the water consumption. From this, can make the personnel quantity that detects out laminate in actual personnel quantity to, make the epidemic prevention goods and materials that provide laminate in actual demand, reduced the waste of epidemic prevention goods and materials.
And 102, training an initial power node user number recognition model based on the power consumption sample set and the water consumption sample set, and taking the trained initial power node user number recognition model as a power node user number recognition model.
In some embodiments, the executing entity may train an initial power node user number recognition model based on the power consumption sample set and the water consumption sample set, and obtain the trained initial power node user number recognition model as the power node user number recognition model. The initial power node user number identification model includes: the initial power consumer quantity identification model and the initial hydraulic consumer quantity identification model. Here, the initial power consumer number recognition model may refer to an untrained convolutional neural network model. The initial hydraulic user number recognition model may refer to an untrained convolutional neural network model.
In practice, based on the electricity consumption sample set and the water consumption sample set, the executing body may train an initial power node user number identification model through the following steps, and obtain the trained initial power node user number identification model as a power node user number identification model:
in the first step, a power consumption sample is selected from the power consumption sample set. Here, one electricity usage sample may be randomly selected from the above electricity usage sample set.
And secondly, selecting a water sample from the water sample set. Here, one water sample may be randomly selected from the water sample set.
And thirdly, inputting the power utilization samples into the initial power node user number identification model to obtain a power node user number identification result. Here, the power node user number identification result may represent the number of identified users corresponding to the power consumption sample.
And fourthly, inputting the water sample into the initial hydraulic user number identification model to obtain a hydraulic user number identification result. Here, the water user number recognition result may represent the number of recognized users corresponding to the water use sample.
And fifthly, determining a power consumption loss value between the power node user number identification result and a power consumption sample label included in the power consumption sample based on a first preset loss function. The first loss function may include, but is not limited to: mean square error loss function (MSE), hinge loss function (SVM), cross entropy loss function (cross entropy), and the like.
And sixthly, determining a water consumption loss value between the water power user number identification result and a water consumption sample label included in the water consumption sample based on a second preset loss function. The second loss function may include, but is not limited to: mean square error loss function (MSE), hinge loss function (SVM), cross entropy loss function (cross entropy), and the like.
And seventhly, in response to the fact that the power consumption loss value is larger than or equal to a preset power consumption loss value, reversely deriving the network parameters of the initial power node user number identification model according to the power consumption loss value to obtain a power gradient value. Here, the power gradient value may refer to gradient data of an initial power node user number identification model.
And eighthly, in response to the fact that the water loss value is larger than or equal to a preset water loss value, reversely deriving the network parameters of the initial hydraulic user number identification model according to the water loss value to obtain a hydraulic gradient value. Here, the hydraulic gradient value may refer to gradient data of an initial hydraulic user number recognition model.
And ninthly, adjusting network parameters of the initial power node user number identification model according to the hydraulic gradient value. For example, a power consumption error value between the power consumption loss value and a preset power consumption loss value may be determined. On the basis, according to the hydraulic gradient value, the electricity utilization error value is transmitted from the last layer of the model to the front by using methods such as back propagation, random gradient descent and the like so as to adjust the parameters of each layer. Of course, according to the requirement, a network freezing (dropout) method may also be adopted, and the network parameters of some layers are kept unchanged and are not adjusted, which is not limited in any way.
And step ten, adjusting the network parameters of the initial hydraulic power user number identification model according to the electric power gradient value. For example, a water use error value between the water use loss value and a preset water use loss value may be determined. On the basis, according to the power gradient value, the water use error value is transmitted from the last layer of the model to the front by methods such as back propagation, random gradient descent and the like so as to adjust the parameter of each layer. Of course, according to the requirement, a network freezing (dropout) method may also be adopted, and network parameters of some layers are kept unchanged and are not adjusted, which is not limited in any way.
When exchanging the hydraulic gradient value and the electric gradient value, the hydraulic gradient value and the electric gradient value are encrypted respectively to improve the safety of the hydraulic gradient value and the electric gradient value.
The related content in the step 102 is taken as an inventive point of the present disclosure, thereby solving the technical problems mentioned in the background art, i.e., the third technical problem is that the water supply amount and the power supply load are insufficient. ". Indeed, the factors that tend to cause insufficient water supply and power supply load are often as follows: the relation between the actual water consumption and the electricity consumption of the unit area is not comprehensively considered, so that the accuracy of the detected number of the personnel in the unit area is low, and when the detected number of the personnel is smaller than the actual number of the personnel. If the above factors are solved, the effects of reducing the water supply amount and the insufficient power supply load can be achieved. To achieve this effect, first, a power consumption sample is selected from the power consumption sample set; selecting water samples from the water sample set. Therefore, data support is provided for training an initial power node user number identification model. And secondly, inputting the power consumption sample into the initial power node user number identification model to obtain a power node user number identification result. Therefore, the initial power node user number recognition model can be trained to include. And secondly, inputting the water sample into the initial hydraulic user number identification model to obtain a hydraulic user number identification result. Thus, an initial hydraulic power number of users recognition model included in the training initial power node number of users recognition model may be trained. And then, determining a power consumption loss value between the power node user number identification result and a power consumption sample label included in the power consumption sample based on a first preset loss function. Then, based on a second preset loss function, a water use loss value between the water use number identification result and a water use sample label included in the water use sample is determined. And then, in response to the fact that the power consumption loss value is larger than or equal to a preset power consumption loss value, reversely deriving the network parameters of the initial power node user number identification model according to the power consumption loss value to obtain a power gradient value. And in response to the fact that the water loss value is larger than or equal to a preset water loss value, reversely performing derivation on the network parameters of the initial hydraulic power user number identification model according to the water loss value to obtain a hydraulic gradient value. Therefore, the initial power consumer quantity identification model and the initial hydraulic consumer quantity identification model are convenient to adjust. And then, adjusting the network parameters of the initial power node user number identification model according to the hydraulic gradient value. Therefore, the network parameters of the initial power node user number identification model can be adjusted according to gradient data generated by the initial hydraulic power user number identification model in the training process. And finally, adjusting the network parameters of the initial hydraulic power user number identification model according to the electric power gradient value. Therefore, the network parameters of the initial hydraulic power user number identification model can be adjusted according to gradient data generated by the initial power node user number identification model in the training process. Therefore, the network parameters of the initial power node user number identification model and the initial hydraulic power user number identification model can be adjusted by comprehensively considering the gradient data of the water consumption and the power consumption in the training process. Furthermore, the accuracy of the trained power node user number identification model for identifying the number of people in the unit area is improved. Therefore, the water supply amount and the power supply load which are adapted to the predicted number of the users can be provided for the users, so that the problem that the water supply amount and the power supply load of part of the users are insufficient is solved.
Optionally, in response to determining that the power consumption loss value is smaller than the preset power consumption loss value and the water consumption loss value is smaller than the preset water consumption loss value, determining the initial power node user number identification model as the power node user number identification model.
In some embodiments, the execution subject may determine the initial power node consumer number identification model as the power node consumer number identification model in response to determining that the power consumption loss value is less than the preset power consumption loss value and the water consumption loss value is less than the preset water consumption loss value.
And 103, collecting the electricity utilization information and the water utilization information of the target power node in a preset time period.
In some embodiments, the execution main body may collect the electricity utilization information and the water utilization information of the target power node within a preset time period from the terminal device through a wired connection or a wireless connection. Here, the target power node may refer to a power node of a unit area to which the number of persons to be detected is. Here, the power consumption information may refer to power consumption information of each user corresponding to the target power node within a preset time period, and may include, but is not limited to: a target power usage sequence. The target electricity consumption amount may refer to an electricity consumption amount of a single user number within a preset time period. The water usage information may refer to water usage information of each user corresponding to the target power node within a preset time period, and may include, but is not limited to: target water usage sequence. The target water usage may refer to the water usage of a single user number within a preset time period.
And 104, inputting the electricity utilization information and the water utilization information into the power node user number identification model to obtain the power node user identification number.
In some embodiments, the execution body may input the electricity information and the water use information into the power node user number identification model to obtain the power node user identification number.
And 105, adjusting the water supply amount and the power supply load of the target power node according to the power node user identification number.
In some embodiments, the execution body may adjust the water supply amount and the power supply load of the target power node according to the power node user identification number. In practice, in response to determining that the above-described power node user identification number is greater than the historical user number, the water supply amount and the power supply load corresponding to the target power node are increased. Here, the specific values of the increased water supply amount and the power supply load may be adjusted according to the amount of change in the actual power node user identification number. For another example, in response to determining that the above-described power node user identification number is smaller than the historical user number, the water supply amount and the power supply load corresponding to the target power node are reduced. Here, the historical number of users may refer to the number of users of the target power node collected last time.
Optionally, in response to determining that the power node user identification number is greater than the historical user number, controlling the associated transportation vehicle to transport the epidemic prevention material to the target power node.
In some embodiments, the execution subject may control the associated transportation vehicle to transport the epidemic prevention material to the target power node in response to determining that the power node user identification number is greater than the historical number of users. Here, the associated transport vehicle may refer to a vehicle for transporting the epidemic prevention materials, which performs the communication connection with the main body as described above. Here, the epidemic prevention materials may include, but are not limited to: medical mask and disinfectant.
The above embodiments of the present disclosure have the following advantages: through the hydropower adjustment method based on the water and electricity utilization private data of some embodiments of the disclosure, the timeliness of the inspection is improved, and the checking time is shortened. Specifically, the reason why the check time is long is that: through the check of epidemic prevention personnel, the timeliness is lower. Based on this, according to the hydropower adjustment method based on private data of power consumption by water, firstly, a power consumption sample and a water consumption sample corresponding to each power node in a target area are obtained, and a power consumption sample set and a water consumption sample set are obtained. Therefore, data support is provided for training the power node user number identification model. Secondly, training an initial power node user number recognition model based on the power consumption sample set and the water consumption sample set, and obtaining the trained initial power node user number recognition model as a power node user number recognition model. Therefore, a model for identifying the number of people in a unit area (power node) can be trained according to the power utilization samples and the water utilization samples corresponding to the power node. Therefore, the number of persons in the unit area can be checked from the electricity information and water information of the unit area (power node). And then, collecting the electricity utilization information and the water utilization information of the target power node in a preset time period. And then, inputting the electricity utilization information and the water utilization information into the power node user number identification model to obtain the power node user identification number. Thus, the number of persons in the unit area (power node) can be identified from the electricity consumption information and the water consumption information of the single power node (target power node). And finally, adjusting the water supply amount and the power supply load of the target power node according to the power node user identification number. Thus, the number of persons in a unit area (power node) can be directly detected from the amount of electricity and water used. The detection timeliness is improved, and the checking time is shortened.
With further reference to fig. 2, as an implementation of the methods illustrated in the above figures, the present disclosure provides some embodiments of a hydropower adjustment device based on water and electricity utilization privacy data, which correspond to those of the method embodiments illustrated in fig. 1, and which may be applied in various electronic devices in particular.
As shown in fig. 2, the hydropower adjustment device 200 based on the private data of the water consumption electricity of some embodiments includes: an acquisition unit 201, a training unit 202, an acquisition unit 203, an input unit 204 and an adjustment unit 205. The acquiring unit 201 is configured to acquire an electricity consumption sample and a water consumption sample corresponding to each power node in a target area, so as to obtain an electricity consumption sample set and a water consumption sample set; a training unit 202, configured to train an initial power node user number identification model based on the power consumption sample set and the water consumption sample set, to obtain a trained initial power node user number identification model as a power node user number identification model; the acquisition unit 203 is configured to acquire power utilization information and water utilization information of the target power node within a preset time period; an input unit 204 configured to input the electricity information and the water use information into the power node user number identification model to obtain a power node user identification number; an adjusting unit 205 configured to adjust the water supply amount and the power supply load of the target power node according to the power node user identification number.
It is to be understood that the units recited in the hydropower adjustment device 200 based on the water usage electricity utilization privacy data correspond to the respective steps in the method described with reference to fig. 1. Thus, the operations, features and resulting benefits described above for the method are equally applicable to the hydropower adjustment device 200 and the units contained therein based on the water and electricity utilization privacy data, and will not be described in detail herein.
Referring now to FIG. 3, a block diagram of an electronic device (e.g., server) 300 suitable for use in implementing some embodiments of the present disclosure is shown. The electronic device in some embodiments of the present disclosure may include, but is not limited to, mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and the like, and fixed terminals such as digital TVs, desktop computers, and the like. The electronic device shown in fig. 3 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present disclosure.
As shown in fig. 3, electronic device 300 may include a processing device (e.g., central processing unit, graphics processor, etc.) 301 that may perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM) 302 or a program loaded from a storage device 308 into a Random Access Memory (RAM) 303. In the RAM303, various programs and data necessary for the operation of the electronic apparatus 300 are also stored. The processing device 301, the ROM302, and the RAM303 are connected to each other via a bus 304. An input/output (I/O) interface 305 is also connected to bus 304.
Generally, the following devices may be connected to the I/O interface 305: input devices 306 including, for example, a touch screen, touch pad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, or the like; an output device 307 including, for example, a Liquid Crystal Display (LCD), a speaker, a vibrator, and the like; storage devices 308 including, for example, magnetic tape, hard disk, etc.; and a communication device 309. The communication means 309 may allow the electronic device 300 to communicate wirelessly or by wire with other devices to exchange data. While fig. 3 illustrates an electronic device 300 having various means, it is to be understood that not all illustrated means are required to be implemented or provided. More or fewer devices may alternatively be implemented or provided. Each block shown in fig. 3 may represent one device or may represent multiple devices, as desired.
In particular, according to some embodiments of the present disclosure, the processes described above with reference to the flow diagrams may be implemented as computer software programs. For example, some embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In some such embodiments, the computer program may be downloaded and installed from a network through the communication device 309, or installed from the storage device 308, or installed from the ROM 302. The computer program, when executed by the processing apparatus 301, performs the above-described functions defined in the methods of some embodiments of the present disclosure.
It should be noted that the computer readable medium described in some embodiments of the present disclosure may be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In some embodiments of the disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In some embodiments of the present disclosure, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.
In some embodiments, the clients, servers may communicate using any currently known or future developed network Protocol, such as HTTP (Hyper Text Transfer Protocol), and may interconnect with any form or medium of digital data communication (e.g., a communications network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the Internet (e.g., the Internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed network.
The computer readable medium may be embodied in the electronic device; or may be separate and not incorporated into the electronic device. The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to: acquiring an electricity utilization sample and a water utilization sample corresponding to each power node in a target area to obtain an electricity utilization sample set and a water utilization sample set; training an initial power node user number recognition model based on the power utilization sample set and the water utilization sample set to obtain the trained initial power node user number recognition model as a power node user number recognition model; collecting power utilization information and water utilization information of a target power node in a preset time period; inputting the electricity utilization information and the water utilization information into the power node user number identification model to obtain the power node user identification number; and adjusting the water supply amount and the power supply load of the target power node according to the power node user identification number.
Computer program code for carrying out operations for embodiments of the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, smalltalk, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units described in some embodiments of the present disclosure may be implemented by software, and may also be implemented by hardware. The described units may also be provided in a processor, and may be described as: a processor includes an acquisition unit, a training unit, a collection unit, an input unit, and an adjustment unit. Here, the names of these units do not constitute a limitation to the unit itself in some cases, for example, the acquiring unit may also be described as "a unit that acquires an electricity consumption sample and a water consumption sample corresponding to each power node in a target area, and obtains an electricity consumption sample set and a water consumption sample set".
The functions described herein above may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems on a chip (SOCs), complex Programmable Logic Devices (CPLDs), and the like.
The foregoing description is only exemplary of the preferred embodiments of the disclosure and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the invention in the embodiments of the present disclosure is not limited to the specific combinations of the above-mentioned features, and other embodiments in which the above-mentioned features or their equivalents are combined arbitrarily without departing from the spirit of the invention are also encompassed. For example, the above features and (but not limited to) technical features with similar functions disclosed in the embodiments of the present disclosure are mutually replaced to form the technical solution.
Claims (6)
1. A hydropower adjustment method based on private data of water and electricity utilization comprises the following steps:
acquiring a power utilization sample and a water utilization sample corresponding to each power node in a target area to obtain a power utilization sample set and a water utilization sample set;
training an initial power node user number recognition model based on the power consumption sample set and the water consumption sample set to obtain the trained initial power node user number recognition model as a power node user number recognition model;
collecting power utilization information and water utilization information of a target power node in a preset time period;
inputting the electricity utilization information and the water utilization information into the power node user number identification model to obtain the power node user identification number;
and adjusting the water supply amount and the power supply load of the target power node according to the power node user identification number.
2. The method of claim 1, wherein the obtaining of the power and water usage samples corresponding to each power node within the target area comprises:
acquiring a user number sequence, a user total number and a power node identification corresponding to the power node;
acquiring a power consumption sequence of the user number sequence in a first historical time period, wherein the user number in the user number sequence corresponds to the power consumption in the power consumption sequence;
and generating a power consumption sample according to the user number sequence, the total number of the users, the power node identification and the power consumption sequence.
3. The method of claim 1, wherein the obtaining of the electricity and water usage samples corresponding to each power node in the target area comprises:
acquiring a user number sequence, a user total number and a hydraulic node identification corresponding to the electric power node;
acquiring a water consumption sequence of the user number sequence in a first historical time period, wherein the user number in the user number sequence corresponds to the water consumption in the water consumption sequence;
and generating a water consumption sample according to the user number sequence, the total number of the users, the hydraulic node identification and the water consumption sequence.
4. A water and electricity adjusting device based on private data of water and electricity utilization comprises:
the acquisition unit is configured to acquire an electricity utilization sample and a water utilization sample corresponding to each power node in a target area to obtain an electricity utilization sample set and a water utilization sample set;
the training unit is configured to train an initial power node user number recognition model based on the power utilization sample set and the water utilization sample set, and the trained initial power node user number recognition model is obtained and serves as a power node user number recognition model;
the acquisition unit is configured to acquire power utilization information and water utilization information of the target power node within a preset time period;
an input unit configured to input the electricity utilization information and the water utilization information into the power node user number identification model, resulting in a power node user identification number;
an adjusting unit configured to adjust a water supply amount and a power supply load of the target power node according to the power node user identification number.
5. An electronic device, comprising:
one or more processors;
a storage device having one or more programs stored thereon;
when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-3.
6. A computer-readable medium, on which a computer program is stored, wherein the computer program, when being executed by a processor, carries out the method according to any one of claims 1-3.
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