In the ever-evolving landscape of agriculture, the need for precision and efficiency has never been more critical. This paper introduces a cutting-edge irrigation management system that leverages the power of the Inte...
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In response to the problems of insufficient prediction accuracy and slow response speed in traditional commodity sales trend prediction methods, this article explored market demand prediction based on long short-term ...
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ISBN:
(纸本)9798400718144
In response to the problems of insufficient prediction accuracy and slow response speed in traditional commodity sales trend prediction methods, this article explored market demand prediction based on long short-term memory networks. Firstly, the historical data of product sales was preprocessed, including filling in missing values, removing outliers, and standardizing the data. Then, feature selection and dimensionality reduction were performed by calculating Pearson correlation coefficients and principal component analysis. Next, the LSTM (Long Short-Term Memory) model was constructed and the network architecture was designed. Hyperparameters and activation functions were selected, and time step information was added to the input sequence to enhance the model's ability to capture temporal dependencies. In addition, real-time data integration was carried out to improve the timeliness and accuracy of model predictions. In the test set experiment, the accuracy of the LSTM model used in this article increased to 93.1%, with an precision of 93%, a recall rate of 91.2%, and an F1 value of 0.92, demonstrating good performance;in the sales forecast test, the highest prediction accuracy reached 99.3%;in terms of response time, our model was faster than other models;in the questionnaire survey, the satisfaction rate of prediction accuracy was as high as 95%. The experimental results showed the practical application value and potential of the LSTM model in the field of market demand prediction.
The objective of this study was to develop a model application to systematize nutritional grouping (NG) management in commercial dairy farms. The model has 4 sub-sections: (1) real-timedata stream integration, (2) ca...
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The objective of this study was to develop a model application to systematize nutritional grouping (NG) management in commercial dairy farms. The model has 4 sub-sections: (1) real-timedata stream integration, (2) calculation of nutritional parameters, (3) grouping algorithm, and (4) output reports. A simulation study on a commercial Wisconsin dairy farm was used to evaluate our NG model. On this dairy farm, lactating cows (n = 2,374 +/- 185) are regrouped weekly in 14 pens according to their parity and lactation stage, for which 9 diets are provided. Diets are seldom reformulated and nutritional requirements are not factored to allocate cows to pens. The same 14 pens were used to simulate the implementation of NG using our model, closely following the current farm criteria but also including predicted nutritional requirements (net energy for lactation and metabolizable protein;NEL and MP) and milk yield in an attempt to generate more homogeneous groups of cows for improved diet accuracy. The goal of the simulation study was to implement a continuous weekly system for cows' pen allocation and diet formulation. The predicted MP and NEL requirements from the NG were used to formulate the diets using commercial diet formulation software and the same feed ingredients, feed prices, and other criteria as the current farm diets. Diet MP and NEL densities were adjusted to the nutritional group requirements. Results from the simulation study indicated that the NG model facilitates the implementation of an NG strategy and improves diet accuracy. The theoretical diet cost and predicted nitrogen supply with NG decreased for lownutritional-requirement groups and increased for highnutritional-requirement groups compared with current farm groups. The overall average N supply in diets for NG management was 15.14 g/cow per day less than the current farm grouping management. The average diet cost was $3,250/cow per year for current farm management and $3,219/cow per year for NG, whi
The presentation would identify the business drivers on UK manufacturing and identify the priorities for realtimedataintegration. Demanding customers are requiring time compression of all aspects of the supply chai...
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ISBN:
(纸本)0863417256;9780863417252
The presentation would identify the business drivers on UK manufacturing and identify the priorities for realtimedataintegration. Demanding customers are requiring time compression of all aspects of the supply chain. Responsive operations are essential and a necessary but not sufficient condition for excellent realtime supply chains. While manufacturing leaders rarely have an interface issue many #m's are wasted installing complex enterprise management processes around poor operations
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