2 results about "Interaction strength" patented technology

The invention provides a method for predicting sorting of fermented sponge spicules through machine learning, which comprises the following steps of: analyzing the interaction strength of spicule structures and hypha attachment according to a deformation aggravation degree to obtain a potential rising level of a sorting misjudgment rate; if the potential rising level of the sorting misjudgment rate exceeds a preset rising level standard, the airflow intensity and the screen mesh aperture are obtained from historical data, the airflow intensity and the screen mesh aperture are adjusted according to the adhesion stacking risk, and a dynamic adjustment instruction set is obtained; the airflow intensity and the screen mesh aperture of the sorting equipment are adjusted by executing the adjusting instruction set, the state of the single-layer distribution bone needles adjusted by the sorting equipment is obtained, and the single-layer distribution uniformity of the bone needles is recognized; the final sorting parameters are applied to a sponge spicule sorting system to sort sponge spicules, single-layer distributed sponge spicules are obtained, and the stability of the sponge spicule sorting process is evaluated by analyzing the uniformity and the sorting misjudgment rate of the single-layer distributed spicules.

This invention relates to the field of groundwater environmental assessment, specifically to an intelligent assessment method and system for groundwater environmental effects based on multi-field coupling. The method takes any spatial unit of the area to be assessed and its corresponding time period as the target spatiotemporal unit, and forms target field pairs from any two fields. Correlation analysis is performed on key indicator data of the target spatiotemporal unit with respect to the target field pairs to obtain the interaction strength coefficient of the target spatiotemporal unit with respect to the target field pairs. The spatial distribution and temporal variation trend of the interaction strength coefficient are analyzed to obtain the spatiotemporal coupling factor of the target field pairs. Combined with key indicator data of the spatiotemporal unit with respect to different fields, a visual assessment of the groundwater environmental effects in the area to be assessed is performed. This invention quantifies and integrates the complex nonlinear and spatiotemporally variable interactions between seepage fields, chemical fields, and temperature fields in the groundwater system, improving the assessment effect of groundwater environmental effects.