3 results about "Mean square difference" patented technology

This disclosure relates to the field of bridge engineering, specifically to a design method, system, and medium for HPC-RC combined eccentrically compressed columns. The method includes: defining a design space; selecting optimal design data combinations based on engineering specification constraints, bearing capacity constraints, and cost-effectiveness values ​​to construct a design data sample set; constructing a two-branch heterogeneous neural network model, the model including an input layer, a shared feature extraction layer, a diameter prediction classification branch, and a reinforcement area prediction regression branch; constructing a loss function composed of focal loss and mean square error loss; training the two-branch heterogeneous neural network model using the design data sample set; and using the trained two-branch heterogeneous neural network model to predict the diameter and total reinforcement area of ​​the eccentrically compressed column. This disclosure improves the stability and accuracy of the design, reduces the computational burden, increases computational speed, and reduces computational complexity.

The present disclosure relates to the field of bridge engineering, and particularly relates to a design method, system and medium for HPC-RC combined eccentric compression column. The method comprises the following steps: defining a design space; screening out an optimal design data combination according to engineering specification constraints, bearing capacity constraints and performance-price ratio value, and constructing a design data sample set; constructing a double-branch heterogeneous neural network model, wherein the model comprises an input layer, a shared feature extraction layer, a diameter prediction classification branch and a reinforcement area prediction regression branch; constructing a loss function composed of focal loss and mean square error loss, and training the double-branch heterogeneous neural network model by using the design data sample set; and predicting the diameter of the eccentric compression column and the total reinforcement area of the eccentric compression column by using the trained double-branch heterogeneous neural network model. The present disclosure improves the stability and accuracy of the design, has a small calculation burden, improves the calculation speed and reduces the calculation amount.

The application discloses a kind of centroid extraction method and extraction system of autocollimator image, wherein based on the Gaussian filter of mean square deviation σ is filtered to image;According to the edge of the image refined by multistage calculation, the edge detection of image is completed, and edge pixel point is determined;Ellipse centroid is fitted to edge pixel point;Based on each ellipse centroid is normalized, and the centroid of image is calculated, at this time, the edge of the image refined by filtering processing under multistage calculation, and corresponding edge pixel point is determined, ellipse centroid is fitted to edge pixel point, and based on each ellipse centroid is normalized, by this method, the influence of unstable gray on centroid extraction can be overcome, and the centroid extraction precision of autocollimator image is improved.