CN112784394A - Ecological breeding simulation system based on artificial intelligence - Google Patents
Ecological breeding simulation system based on artificial intelligence Download PDFInfo
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Abstract
The invention discloses an artificial intelligence-based ecological breeding simulation system, and particularly relates to the field of ecological systems, wherein the system comprises a core system, a visual simulator interface, a data center and a learning module; the core system comprises a biological digital basic database, a three-dimensional environment model and ecological rules; the visual simulator interface is an operation interface used by a user side of the system and comprises external information input, calculation result output and a visual interface. The invention can more accurately and comprehensively simulate and calculate the running state of the artificial ecosystem of the farm by taking digital biology as a basis, utilizing the biological science technology and calculating the ecological rule, and simultaneously carry out more scientific catastrophic prediction, thereby adding 'professional brain' to the artificial ecosystem, reducing the operation risk and simultaneously enabling the system to be more intelligent and automatic.
Description
Technical Field
The invention relates to the technical field of ecological systems, in particular to an artificial intelligence-based ecological breeding simulation system.
Background
The ecosystem is a dynamic ecosystem which is composed of a biological community and living environment thereof, wherein the biological community is composed of certain types of animals, plants and microorganisms which exist in a certain range or area of the nature and depend on each other, and the living environment contains various non-biological substances and energy. The ecological system in nature is complex and various and has different sizes, which is as large as the whole ecological circle of the earth and as small as a water vat. The ecosystem can be divided into a natural ecosystem, a semi-artificial ecosystem and an artificial ecosystem, wherein the semi-artificial ecosystem and the artificial ecosystem enable the ecosystem to be produced according to a target designed artificially by means of human intervention, for example, various farmlands, orchards, breeding bases, aquaculture, household aquarium fish and the like widely exist at present.
In the field of research and application of natural ecology, the technology directions of intelligent solutions based on agriculture, forestry and fishery production, specific ecological environment simulation devices or systems based on natural ecological research, systems based on computational chemistry and other simulation substance biochemical processes and the like are developed in succession by combining the computer technology, the internet of things technology and the like which are developed at a high speed at present. However, the intelligent solution of the prior art in agriculture, forestry and fishery production generally adopts a strong manual intervention mode, the core is a monitoring and early warning function, and the system mainly enables the whole system to operate according to an inherent mode through artificially constructing the growth environment of a specified organism and then through a sensor monitoring tool and an automation tool so as to achieve the production purpose; the inherent model is used for guiding production, but due to the specialty and complexity of an ecosystem, particularly when a certain number of different types of biological communities are formed, the system cannot analyze and accurately reflect the stability of the whole ecology, and even cannot perform professional prediction; the scheme adopts a strong manual intervention mode, cannot fully utilize self-regulation and balance of natural ecological knowledge to guide production, wastes resources and influences the quality of cultured organisms.
Disclosure of Invention
In order to overcome the above defects in the prior art, the embodiment of the invention provides an artificial intelligence-based ecological breeding simulation system, and the technical problems to be solved by the invention are as follows: the intelligent level of automatic management of the farm is improved through the simulator, and the quality of the cultured organisms is guaranteed.
In order to achieve the purpose, the invention provides the following technical scheme: an artificial intelligence-based ecological breeding simulation system comprises a core system, a visual simulator interface, a data center and a learning module;
the core system comprises a biological digital basic database, a three-dimensional environment model and ecological rules;
the biological digital basic database is the attribute parameters of survival and growth of various organisms;
the three-dimensional environment model is a natural environment attribute parameter of the position of the ecological environment;
the ecological rule is an operation center for calculating various rules;
the visual simulator interface is an operation interface used by a user side of the system and comprises external information input, calculation result output and a visual interface;
the external information input comprises biological composition information input and basic environment information input;
the calculation result outputs a system analysis result in the reference ecological rule, wherein the system analysis result comprises an environment construction model suggestion, a biological composition and quantity configuration suggestion and an equipment configuration suggestion, and an optimal equipment operation model and an optimal manual intervention behavior suggestion are given according to an actual environment model and an equipment configuration condition;
the visual interface carries out simulation display on biological information, spatial information, environmental information, equipment operation information and monitoring information, and can comprehensively display the ecological operation condition;
the data center is responsible for acquiring operation data of various ecological systems;
the learning module corrects initial parameters in a core system and optimizes an algorithm through big data analysis and calculation.
In a preferred embodiment, the data center is responsible for collecting various data of the ecological operation, including but not limited to sensor monitoring data, human observation data, human intervention behavior data, and operation logs of the equipment.
In a preferred embodiment, the data center is further provided with an early warning rule and an automatic processing scheme for ensuring the normal operation of the monitored abnormal data.
In a preferred embodiment, the biological digital basic database comprises four parts of information of biological living environment parameters, biological growth cycle parameters, biological interspecies relations and biochemical units.
In a preferred embodiment, the stereoscopic environment model is set as natural environment parameter information where the artificial ecosystem is located, including spatial information and environmental information.
In a preferred embodiment, the ecological rule is used for performing rationality analysis of an artificial ecosystem by using a biological data base database and a three-dimensional environment model, and comprises living environment analysis and ecological stability analysis.
In a preferred embodiment, the biochemical unit is configured to biochemically consume each organism in vivo, including decomposition, absorption, and metabolism of various nutrients.
In a preferred embodiment, the control device and the monitoring device for external information input both access the hardware monitoring and control system by means of external access, so as to guide the setting operation of the device.
The invention has the technical effects and advantages that:
1. the method is based on digital biology, utilizes the biological science technology, can more accurately and comprehensively simulate and calculate the running state of the artificial ecosystem of the farm through the calculation of ecological rules, simultaneously carries out more scientific catastrophic prediction, adds a professional brain to the artificial ecosystem, reduces the operation risk, and simultaneously enables the system to be more intelligent and automatic;
2. according to the invention, ecological knowledge is utilized to carry out cultivation, certain self-supply is realized through the supply relationship and predation relationship inside the ecology, manual strong intervention is reduced, and the quality of the product is improved;
3. the system has low use threshold, and users only need to input basic biological information and environmental information, so that the system can automatically carry out scientific calculation and judgment, thereby reducing the guidance of agricultural experts or professionals and saving the operation cost;
4. the invention guides the construction of the artificial ecosystem by matching the natural environment model of the artificial ecosystem with the biological living environment of the ecosystem, can provide an optimal environment construction scheme and an equipment configuration model, reduces the investment cost, is not limited by the environment and the equipment configuration, can provide an optimal operation scheme under the existing environment and the matched equipment, and provides rationality suggestions aiming at biological composition and quantity configuration;
5. the invention is different from the current simulation system based on various specific natural environments, the system is not limited by any conditions in use, can be applied to various small artificial ecosystems, can be directly used in various artificial ecosystems such as various land and water breeding plants, greenhouses, household fish tanks, aquariums and the like, is not limited by any equipment, and can also provide production guidance based on biological science technology in a pure on-line mode.
Drawings
Fig. 1 is a main schematic diagram of the overall system structure of the present invention.
FIG. 2 is a diagram of a basic computational model of the core system of the present invention.
FIG. 3 is a diagram of the basic database composition model of the present invention.
FIG. 4 is a model diagram of the living environment parameters of the living creature of the present invention.
FIG. 5 is a diagram showing the analysis of the interspecies relationship in the present invention.
FIG. 6 is a schematic diagram of a biochemical unit according to the present invention.
FIG. 7 is a diagram illustrating the calculation process and rules of the present invention.
FIG. 8 is a diagram of a model of rules for common living environment of living organisms according to the present invention.
FIG. 9 is a schematic view of an ecological internal and external material circulation model according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention provides an artificial intelligence-based ecological breeding simulation system, which comprises a core system, a visual simulator interface, a data center and a learning module (refer to fig. 1);
the core system comprises a biological digital basic database, a three-dimensional environment model and ecological rules (the system model refers to fig. 2);
the system regards the artificial ecosystem of the whole farm as a relatively closed whole, all substances input into the ecosystem are taken as total input, all outputs in the running process of the ecosystem are taken as total output, the space, the temperature and the illumination parameters of the ecosystem form an environment digital model, a complex relation network exists in the ecosystem, and the biological interspecies relation exists between each organism and other organisms;
the biological digital basic database is the attribute parameters of the survival and growth of various organisms, including four parts of information of the living environment parameters, the growth cycle parameters of the organisms, the inter-organism relationship and the biochemical units (the components of the biological digital basic database refer to FIG. 3);
in a natural ecological system, organisms are generally divided into producers, consumers and decomposers, the three are various in number, a very complex natural ecological environment is formed, and a certain dynamic balance is kept through the cooperation of the three, in an artificial ecological system, the environment is relatively closed due to the aim of production, the types and the number of the organisms are relatively small, the ecological structure is relatively simple, and manual intervention is strong, so that the system simply summarizes various common green plants into the producers, various common aquatic and terrestrial animals as the consumers and various saprophagic organisms as the decomposers, and a biological digital basic database needs to collect the main common survival and growth data parameters of various organisms and is used as the calculation basis of a core system;
1) biological living environment parameters (parameter composition refers to FIG. 4)
A1. The environment type: according to the living environment requirements of organisms, the system is defined into six categories of seawater, fresh water, brackish water, seawater land and water, fresh water land and water and land;
B1. the illumination parameters are as follows: the illumination duration, illumination intensity, light quality and photosynthetic effective value of organisms;
C1. temperature parameters: living temperature and suitable temperature requirement of the living beings;
D1. water quality parameters: dissolved oxygen and CO in biological water2The content, the pH value of the water body, the specific gravity of the seawater, the salinity of the seawater, the hardness GH of the water body, KH of the water body and the content of main inorganic salts in the water body are required;
E1. soil parameters: the organism has requirements on soil type, soil thickness, soil volume weight, soil humidity, soil PH, PH tolerance value, salinity, soil main inorganic salt content, soil organic matter content, soil EC (threshold value for limiting activity of plants and microorganisms), and soil CES (fertility preserving capability value);
F1. air parameters: air CO2 content, air oxygen content, air humidity, air pressure;
the biological living environment parameters relate to a large amount of biological research in a long period and biological parameter information collection work, so the system divides the parameters into necessary parameters and non-necessary parameters, the integrity and the accuracy of the parameters are favorable for the accuracy of the calculation result of the system, and the biological parameters which are mainly cultured and cultivated by human are preferentially collected.
2) Biological growth cycle parameters
The system collects the growth cycle parameters of organisms, mainly comprising three types of animals, plants and microorganisms, wherein the growth and development model of the animals is subjected to simulation calculation by referring to a von Berta-Lanffy equation:
A2. animals: the method comprises five time periods of animal reproduction, young growth, maturity and life, and parameter information of body type, weight and living environment in each period;
B2. plant: comprises five time periods of plant propagation, growth, maturity, flowering and fruiting; and the height of the plant, the type of the root system and the parameter information of the living environment in each period;
C2. microorganisms: the method comprises three types of information of microbial reproduction cycle, quantity and life;
3) relationships between biological species (see FIG. 5)
Various complex relationship nets exist among organisms, neutral effects (no direct effects), positive interactions (including partial interest symbiosis, original collaboration and mutual interest symbiosis) and negative interactions (competition, predation, parasitism and partial damage) are summarized in natural science, and because the biological composition of an artificial ecosystem is relatively simple, the interspecific relationships of the organisms are summarized into four types of most common relationships of competition, supply, predation and neutral in the system according to the most common interaction types;
in the artificial ecosystem, the definition and relationship of a producer, a consumer and a decomposer are not different from those of a natural ecosystem, and organisms of the artificial ecosystem are classified according to the types of the producer, a phytophagous animal, a omnivorous animal, a primary carnivorous animal, a secondary carnivorous animal and a saprophagous organism:
A3. the producer: mainly comprises various green plants, algae or plankton with photosynthesis;
B3. feeding to a plant animal: mainly feeding vegetarian animals, and selecting specific producer species in an artificial ecosystem by a human intervention mode so as to accurately establish a food chain;
C3. omnivorous animals: in the predation relationship, the predation property is mainly used, so that the food chain relationship can be judged by combining animal sexual conditions, the mild type is generalized in the predation property food chain, and the aggressive type is generalized in the carnivorous property food chain;
D3. first-order carnivorous animals: the first-class carnivorous animals generally mainly comprise vegetarian animals, and generally have strong aggressive property and sharp teeth;
E3. secondary carnivorous animals: secondary carnivores are generally large, violent carnivores, have very strong aggressiveness and feed on various animals;
F3. saprophage organisms: various non-living complex organic matters such as animal carcasses, animal wastes and dead branches of plants are taken as food, various bacteria (saprophytic bacteria) and fungi are taken as main materials, and a small amount of saprophytic animals are also contained;
from the above biotype definitions, a simple interspecific relationship is formed:
A4. neutral relationship: the two have no direct correlation, and the carnivorous animal and the producer are not related;
B4. competition relationship: the robbing and competition of living space and living resources are involved, and producers, herbivores, omnivores and carnivores are involved;
C4. supply relationship: directly forming a food chain relation, but not forming destructive predation, and only eating plant parts between the vegetarian animals and the producers;
D4. the predation relationship is as follows: directly forming a food chain relation, and performing destructive predation between carnivorous animals and herbivorous animals, between carnivorous animals and omnivorous animals, between secondary carnivorous animals and primary carnivorous animals, and between secondary carnivorous animals and secondary carnivorous animals (the predatory relation also needs to be calculated by combining size and body shape parameters and caliber parameters of the animals);
4) biochemical unit (refer to FIG. 6)
Each organism has extremely complex biochemical consumption process in vivo, which relates to the decomposition, absorption and metabolism process of various nutrient substances, each organism is taken as an independent biochemical unit which is sealed in one by one in the system, and the calculation is carried out only by considering the input and the output of the unit;
A5. inputting: various organic nutrients and inorganic salts which enter the body of the organism in a direct absorption and feeding way are taken as input;
B5. and (3) outputting: the organism produces substances as output through various excretions, secretions, respiration or photosynthesis metabolism;
spatial information: the method comprises the following steps of (1) converting parameters of water volume and space model, land surface area, effective cultivation soil thickness and area, air volume and circulation, and converting biological survival basic environment elements of the space model;
and (3) environment information: according to the average temperature, illumination, oxygen content and humidity information of the latitude and longitude of the position under different seasons, in addition, the standard variable reference values of the altitude, the temperature and the oxygen content are also included; the depth of the water body and standard variable reference values of temperature, illumination and oxygen content are used for judging the matching degree of the environmental parameters and the ecological system;
the three-dimensional environment model is natural environment attribute parameters of the position of the ecological environment, and the natural environment parameter information of the artificial ecological system comprises space information and environment information;
the ecological rules are operation centers for calculating various rules, and the ecological rules are used for performing rationality analysis of an artificial ecosystem by utilizing a biological data basic database and a three-dimensional environment model, including living environment analysis and ecological stability analysis (refer to fig. 7);
selecting an ecological model: in the ecological balance system of the nature, the relationship among producers, consumers and decomposers is in a relatively stable state; the input and output of energy and material in the system are nearly equal, namely the production process and the consumption and decomposition process in the system are in a balanced state; according to the use of the ecological model, the artificial ecological system is divided into a primary biological ecological model and a secondary biological ecological model and a simple balanced ecological model;
a1, primary and secondary biotype ecotypes: an ecological model for ensuring the growth or the growth of the main organisms is artificially set, and secondary organisms in an ecological system often serve for the growth of the main organisms;
b 1: simple and easy balanced type ecological model: the stable coexistence of various organisms is realized by a manual intervention mode, the manual intervention amount depends on the reasonability of the biological ecosystem, the model is a simple model of the natural ecological balance relationship, the food network relationship among producers, consumers and decomposers is weakened, and the aim of stable coexistence is taken as the main aim;
determining basic environment parameters: inputting the parameter information of the three-dimensional environment model where the artificial ecosystem is located, wherein the parameter information comprises longitude and latitude, altitude and water depth information of the three-dimensional environment model; the terrestrial environment comprises space parameters, illumination parameters, temperature parameters, soil parameters and air parameters; the aquatic environment comprises space parameters, illumination parameters, temperature parameters and water quality parameters, and the information of the parameters can be manually input or calculated by the system according to the standard variable parameters of longitude and latitude, altitude and water depth under different seasons and climates;
determining the biological composition: inputting biological composition information defined in an artificial ecosystem according to the purpose and purpose of the artificial ecological model, and determining whether main organisms exist;
specification of ecological rules:
rule 1: rules of commonality of living environment (refer to FIG. 8)
Firstly, taking intersection set from living environment parameters of all organisms of an artificial ecosystem, if the intersection set does not exist, the organism composition is unreasonable, the organisms can not be cultivated at the same time, and the organism composition needs to be modified; if the intersection exists, the parameters obtained by calculating the intersection are used as an environmental parameter model required by the ecosystem; secondly, matching the output basic environment parameters with an environment parameter model required by calculation survival, if the output basic environment parameters meet the requirements, passing the results, and if the output basic environment parameters do not meet the requirements, calculating a correction suggestion;
rule 2: rule of spatial density biological saturation
The biological saturation of space density is usually related to the factors of nutrient substances or food density, oxygen and activity space in a living space, the living state of the organism is more in enough space due to self-regulation of the organism, but no absolute requirement is required for the space, particularly in an artificial ecosystem, nutrient substances and food are artificially added, and the requirement definition of the space is fuzzy, so that the system does not define the density of terrestrial organisms for the moment, only proposes the density of aquatic animals, and the density system of the aquatic animals converts the saturation according to parameters of body type length, water body volume and water area;
rule 3: food chain supply rules
When the selected model is a primary and secondary biological type ecological model, the system recommends to build a biological model according to the supply relationship and the predation relationship, and certain self-supply is realized so as to improve the natural living quality of the primary organism;
rule 4: rules for determining biological coexistence
When the selected model is a simple balanced ecological model, the system rules can avoid the existence of predation relations in organisms, the preferred neutral relation and the preferred supply relation among the organisms are good, and the preferred competition relation is secondary; maintaining a certain balance between the number of supply relations and the number of competition relations;
rule 5: food chain balance rule
In the food supply model, if the supply relation and the predation relation are completely self-balanced, a certain quantity proportion needs to be kept at least; the system adopts a mode of 'initial value + correction value' to dynamically adjust the balance;
the energy transfer of an initial value producer and a phytophagous animal is 13.5 percent, the energy transfer of the phytophagous animal to a carnivorous animal is 20 percent, and the system converts the initial value of the mass ratio of the food chain into the number-to-weight ratio relation of the food chain according to the conditions that the producer, the phytophagous animal and the carnivorous animal are =100:13.5:2.7 ", and the content density of the biomonomic organic matter is combined;
the corrected value is analyzed according to the ecological running condition in a time period, the initial value is gradually corrected by combining the monitored actual food chain quality ratio (obtained by quantity ratio conversion) relationship, so that a balance relationship is gradually formed, and the corrected value is used as a dynamic adjusting parameter in each actual ecological system;
rule 6: rule of material balance (refer to FIG. 9)
In a natural ecosystem, a producer, a consumer and a decomposer form a matter dynamic balance relationship, and the main route is as follows: the output of the producer can be used as the input of the consumer, the output of the consumer is also used as the input of the decomposer, the output of the decomposer is used as the input of the producer, and the three keep a balance relation in a stable ecological environment; the manual intervention mode is a manual addition and manual removal mode to balance the material circulation in the ecology;
the system summarizes and researches the common input and output substances of producers, consumers and decomposers in the artificial ecosystem except for the absorption of organisms, and comprises the following table:
calculating all input and output material compositions by judging specific biological compositions in each artificial ecosystem, judging the rationality of the ecological compositions according to the consistency of total input and total output materials in the ecosystem, intelligently and dynamically judging the quantity balance relationship in the ecology according to the monitoring of key parameter values, and outputting accurate and simple artificial intervention behavior suggestions according to the quantity balance relationship;
rule 7: ecological stability detoxification rules
The toxicity analysis is carried out on the common biological output substances in the ecological system to ensure that the total output substances in the ecological system do not generate toxicity or negative effect influence on the organisms in the ecological system, and the common toxic substances comprise NH3、NO2-、H2S, in addition to CH4The system judges according to the negative effect that the microbial mass propagation germs affect the survival of the organisms and outputs accurate and simple artificial intervention behavior suggestions, such as increasing the number of plants, adding nitrobacteria/photosynthetic bacteria and artificially isolating excrement, and toxic substances are researched as follows:
rule 8: other rules
In a simple balanced ecological model, under the condition of weak manual intervention, the system judges the biomass by referring to a J-type growth model and an S-type growth model, wherein the S-type growth model is simulated by adopting a Logistic biomass growth curve and is calculated by combining a population competition model Ricker equation, the J-type growth refers to a biomass natural growth model under the condition that the biomass has no natural enemy and sufficient resources, and the S-type growth refers to a biomass growth model under the condition that the biomass has natural enemy and the resources are insufficient;
under the condition that the artificial ecosystem is relatively closed, the development condition of the whole ecosystem can be calculated through a circulation rule of mass and element conservation, and the biological composition and relative balance relation can be calculated through accurately controlling the total input of manual intervention;
in summary, the system analyzes the results:
and (3) analyzing the living environment: analyzing the space and environmental parameters of the ecosystem by combining the biological composition in the selected ecosystem according to the analysis results of the rule 1 and the rule 2, and giving a reasonable environmental construction model suggestion by the ecosystem for guiding the matching construction of the artificial ecosystem;
and (3) ecological stability analysis: according to the analysis results of the rules 3 to 8, combining the biological composition in the selected ecological system and ecological balance and stability requirements, the system gives a collocation model suggestion of the biological composition and the quantity in the ecological system;
and (3) manual intervention scheme suggestion: according to the analysis results of the rules 1 to 8 and in combination with the finally and actually determined biological composition, space and environment parameter models, the system provides a specific scheme needing manual intervention, including monitoring and early warning setting, equipment operation models and manual behavior intervention so as to ensure the balance and stability of the ecological system;
the biochemical unit is set to carry out biochemical consumption processes of each organism in vivo, including decomposition, absorption and metabolism processes of various nutrient substances;
the visual simulator interface is an operation interface used by a user side of the system and comprises external information input, calculation result output and a visual interface;
the external information input comprises biological composition information input and basic environment information input, and both a control device and a monitoring device for external information input are accessed into the hardware monitoring and control system in an external access mode to guide the setting and operation of the device;
the calculation result outputs a system analysis result in the reference ecological rule, wherein the system analysis result comprises an environment construction model suggestion, a biological composition and quantity configuration suggestion and an equipment configuration suggestion, and an optimal equipment operation model and an optimal manual intervention behavior suggestion are given according to an actual environment model and an equipment configuration condition;
the visual interface carries out simulation display on biological information, spatial information, environmental information, equipment operation information and monitoring information, and can comprehensively display the ecological operation condition;
the data center is responsible for acquiring operation data of various ecosystems, including but not limited to sensor monitoring data, human observation data, manual intervention behavior data and operation logs of the equipment, and meanwhile, for various monitored abnormal data, early warning rules and an automatic processing scheme are set to control the operation of the equipment;
the learning module corrects initial parameters in a core system and optimizes an algorithm through big data analysis and calculation;
the learning module analyzes the acquired monitoring data in the running process of the ecological system in combination with the biomass change, the substance input and output change, the environmental parameter change and the ecological abnormal condition in the running process of the ecological system, adjusts the initial parameters in the ecological rules in real time, and optimizes the algorithm so as to gradually approach to a simulation model of the most real ecological running, and can predict the possibility of catastrophic damage to the ecological stability in combination with a regular data model;
because the growth of organisms relates to a very complex internal and external relation, the organisms cannot be completely closed, and the organisms are easily interfered by various random factors, so that the construction and the operation of each ecosystem are unique, the system carries out respective operation on each ecosystem by adopting an initial value plus a correction value, the initial value is used as an original reference value, and the correction value is dynamically corrected by carrying out intelligent analysis on big data;
in addition, various initial parameters and algorithms related in the scheme of the system are dynamically adjusted after being intelligently analyzed according to data of all ecosystems, and the environmental requirements of the system are reversely matched through the digital ecology science of organisms, so that the production is guided.
Finally, it should be noted that: the above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that are within the spirit and principle of the present invention are intended to be included in the scope of the present invention.
Claims (8)
1. The utility model provides an ecological breed analog system based on artificial intelligence which characterized in that: the system comprises a core system, a visual simulator interface, a data center and a learning module;
the core system comprises a biological digital basic database, a three-dimensional environment model and ecological rules;
the biological digital basic database is the attribute parameters of survival and growth of various organisms;
the three-dimensional environment model is a natural environment attribute parameter of the position of the ecological environment;
the ecological rule is an operation center for calculating various rules;
the visual simulator interface is an operation interface used by a user side of the system and comprises external information input, calculation result output and a visual interface;
the external information input comprises biological composition information input and basic environment information input;
the calculation result outputs a system analysis result in the reference ecological rule, wherein the system analysis result comprises an environment construction model suggestion, a biological composition and quantity configuration suggestion and an equipment configuration suggestion, and an optimal equipment operation model and an optimal manual intervention behavior suggestion are given according to an actual environment model and an equipment configuration condition;
the visual interface carries out simulation display on biological information, spatial information, environmental information, equipment operation information and monitoring information, and can comprehensively display the ecological operation condition;
the data center is responsible for acquiring operation data of various ecological systems;
the learning module corrects initial parameters in a core system and optimizes an algorithm through big data analysis and calculation.
2. The artificial intelligence based ecological breeding simulation system according to claim 1, characterized in that: the data center is responsible for collecting various data of ecological operation, including but not limited to sensor monitoring data, human observation data, human intervention behavior data and operation logs of equipment.
3. The artificial intelligence based ecological breeding simulation system according to claim 1, characterized in that: the data center is also provided with an early warning rule and an automatic processing scheme for ensuring the normal operation of the monitored abnormal data equipment.
4. The artificial intelligence based ecological breeding simulation system according to claim 1, characterized in that: the biological digital basic database comprises four parts of information of biological living environment parameters, biological growth cycle parameters, biological interspecific relations and biochemical units.
5. The artificial intelligence based ecological breeding simulation system according to claim 1, characterized in that: the three-dimensional environment model is set as the natural environment parameter information of the artificial ecosystem, including space information and environment information.
6. The artificial intelligence based ecological breeding simulation system according to claim 1, characterized in that: the ecological rules are used for carrying out rationality analysis of an artificial ecological system by utilizing a biological data basic database and a three-dimensional environment model, and comprise living environment analysis and ecological stability analysis.
7. The artificial intelligence based ecological breeding simulation system according to claim 4, characterized in that: the biochemical unit is set to carry out biochemical consumption processes of each organism in vivo, including decomposition, absorption and metabolism processes of various nutrient substances.
8. The artificial intelligence based ecological breeding simulation system according to claim 1, characterized in that: the control equipment and the monitoring equipment for inputting the external information are both accessed into the hardware monitoring and control system in an external access mode and are used for guiding the setting and operation of the equipment.
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| WO2023002658A1 (en) * | 2021-07-20 | 2023-01-26 | ソニーグループ株式会社 | Program, information processing device, and information processing method |
| CN115860284A (en) * | 2023-03-01 | 2023-03-28 | 山东省海洋资源与环境研究院(山东省海洋环境监测中心、山东省水产品质量检验中心) | Fishery resource density identification method and device, storage medium and electronic equipment |
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