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Method and system for establishing cultivation environment parameter-fish growth prediction model

A technology for forecasting models and environmental parameters, applied in forecasting, data processing applications, character and pattern recognition, etc., can solve problems such as low forecasting accuracy, inability to predict fish growth, and limited forecasting ability, and achieve the effect of improving economic benefits.

Active Publication Date: 2021-10-22
HUAZHONG AGRI UNIV
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Problems solved by technology

Among them, the regression analysis method focuses on the exploration of correlation. It can rely on the existing data to establish a regression model to perform correlation analysis, such as analyzing the correlation between fish growth efficiency and different water environment factors, but its predictive ability There are great limitations, and the prediction accuracy is low
Although the data fitting method has a strong predictive ability, the special Von Bertalanffy growth equation, the general Von Bertalanffy growth equation, the Logistic growth equation, the Gompertz growth equation, the Brody growth equation, and the exponential growth equation are commonly used in the data fitting method. Six animal growth models It is not suitable for research on the relationship between fish growth benefits and aquaculture environment parameters, and cannot predict fish growth through changes in aquaculture environment parameters

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  • Method and system for establishing cultivation environment parameter-fish growth prediction model
  • Method and system for establishing cultivation environment parameter-fish growth prediction model
  • Method and system for establishing cultivation environment parameter-fish growth prediction model

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Embodiment 1

[0056] Such as figure 1 As shown, this embodiment shows a method for establishing a breeding environment parameter-fish growth prediction model, which specifically includes the following steps:

[0057] Step S1, collecting fish breeding data; the fish breeding data includes breeding environment parameter data and fish growth index data; the breeding environment parameter data includes hydration factor index data and biological factor index data, specifically including:

[0058] Collect the culture environment parameter data and the fish growth index data, and establish a database; when establishing the database, use various methods that can collect fish growth and corresponding culture environment parameter data to supplement and enrich the database. Sources include but are not limited to existing literature, field investigations and scientific experiments.

[0059] The hydration factor index data includes but not limited to culture temperature, ammonia nitrogen and nitrite n...

Embodiment 2

[0115] Such as Figure 6 As shown, the present embodiment provides a system for establishing a breeding environment parameter-fish growth prediction model, which specifically includes:

[0116] The fish farming data collection module M1 is used to collect fish farming data; the fish farming data includes farming environment parameter data and fish growth index data;

[0117] A fish farming data classification module M2, configured to classify the fish farming data;

[0118] The functional relationship acquisition module M3 is used to perform correlation analysis on the classified fish breeding data to obtain the functional relationship between the fish growth index and each breeding environment parameter;

[0119] A parameter prediction model building module M4, configured to establish a parameter prediction model according to the functional relationship;

[0120] The parameter prediction model solving module M5 is used to solve the parameters of the parameter prediction mod...

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Abstract

The invention relates to a method and system for establishing a cultivation environment parameter-fish growth prediction model, and belongs to the technical field of factory aquaculture. The method comprises steps: firstly, acquiring fish culture data; classifying the fish culture data; performing correlation analysis on the classified fish culture data to obtain a function relation between the fish growth index and each culture environment parameter; establishing a parameter prediction model according to the function relation; performing parameter solving on the parameter prediction model to obtain a coefficient of determination; correcting the parameter prediction model according to the coefficient of determination to obtain an optimized parameter prediction model; and verifying the optimized parameter prediction model, inputting the culture environment parameter data into the optimized parameter prediction model, and outputting fish growth benefit index data, so that the fish growth can be accurately predicted, a fish culture enterprise can seek the optimal production load and culture scale, and the economic benefit of the culture enterprise is improved.

Description

technical field [0001] The invention relates to the technical field of industrialized aquaculture, in particular to a method and system for establishing a fish growth prediction model based on data analysis for aquaculture environment parameters. Background technique [0002] In recent years, fish farming in industrial circulating water is a modern industrial production method, which mainly relies on mechanical equipment to regulate the water body. Its core components are high-efficiency biological filtration devices and automatic monitoring systems for aquaculture water, which can achieve a highly controllable aquaculture environment. At present, the main indicators of biological filters such as ammonia nitrogen loading rate are usually set at unreasonably high levels, which greatly increases energy consumption, and energy consumption is one of the main reasons restricting the profitability of industrial recirculating aquaculture. One of the development trends of industrial...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q10/06G06Q50/02G06K9/62G06F30/27
CPCG06Q10/04G06Q10/06393G06Q50/02G06F30/27G06F18/241Y02A40/81
Inventor 李莉张策李大鹏
Owner HUAZHONG AGRI UNIV