In certain embodiments, a selection of a first point and a second point within an infrastructure may be obtained via a user interface. A plurality of pathways, including a plurality of cable trays, between the first point and the second point may be determined. A first set of cable trays, having weights that do not exceed weight thresholds, may be identified. Images of the first set of cable trays may be obtained from a plurality of image sensors within the infrastructure. Fullness levels of the first set of cable trays may be determined based on the images. A second set of cable trays, having fullness levels that do not exceed fullness thresholds, may be identified from the first set of cable trays. One or more recommended pathways between the first point and the second point may be determined based on the identified second set of cable trays.

In certain embodiments, a selection of a first point and a second point within an infrastructure may be obtained via a user interface. A plurality of pathways, including a plurality of cable trays, between the first point and the second point may be determined. A first set of cable trays, having weights that do not exceed weight thresholds, may be identified. Images of the first set of cable trays may be obtained from a plurality of image sensors within the infrastructure. Fullness levels of the first set of cable trays may be determined based on the images. A second set of cable trays, having fullness levels that do not exceed fullness thresholds, may be identified from the first set of cable trays. One or more recommended pathways between the first point and the second point may be determined based on the identified second set of cable trays.

A water and wastewater treatment process optimization and automatic design system and a design method using the same of the present invention can optimize water and wastewater treatment processes for design of a water and wastewater treatment device that includes a plurality of treatment processes and can automatically generate design deliverables such as drawings, bills of quantities, etc., for design of an optimal process configuration.

A water and wastewater treatment process optimization and automatic design system and a design method using the same of the present invention can optimize water and wastewater treatment processes for design of a water and wastewater treatment device that includes a plurality of treatment processes and can automatically generate design deliverables such as drawings, bills of quantities, etc., for design of an optimal process configuration.

In one embodiment, a method includes: accepting input data for a design including arrangement of spaces of a structure, operating parameters of a ventilation system, and locations and relative positions of an uninfected individual and one or more infected individuals in the structure with respect to air flowing in the structure and influenced by the ventilation system; calculating an inverse protection factor for the structure using a lumped element model, the inverse protection factor being an inverse of a protection factor which is a ratio of contaminant which the one or more infected individuals exhale in the structure and contaminant which the uninfected individual inhales in the structure; comparing the calculated inverse protection factor to a preset criterion; and if the calculated inverse protection factor fails to meet the preset criterion, changing the design, and repeating the calculating, comparing, and changing until the calculated inverse protection factor meets the preset criterion.

This application discloses a pooling processing method, applied to a pooling processing system of a convolutional neural network. The pooling processing system includes a first storage device, a data region, a pooling computation kernel, and a pooling controller. The method includes: reading, by the pooling controller, k pieces of feature data from the first storage device in each reading cycle, the k pieces of feature data being components in a feature map generated by a convolution operation of the convolutional neural network, and k being an integer greater than 1; writing, by the pooling controller, the k pieces of feature data read from the first storage device into the data region, wherein the k pieces of feature data form one group among n groups of k pieces of data with each group arranged in a first dimension and the n groups arranged in a second dimension, wherein the n groups of k pieces of data are written into the data region in an updating cycle, wherein a duration of the updating cycle is n times a duration of the reading cycle, and wherein n cis an integer greater than 1; and transmitting, after the updating cycle is ended, data in the data region to the pooling computation kernel to perform a pooling operation, wherein the data in the data region comprises the n groups of k pieces of data and last m groups of data from a previous updating cycle with each group along the second dimension, wherein the last m groups of data are temporarily stored in the data region for use in pooling calculation by the pooling computation kernel in a next updating cycle. The technical solution in this application reduces the number of storage, numbers of reading and writing due to data reuses, and improves the efficiency of pooling processing.

This application discloses a pooling processing method, applied to a pooling processing system of a convolutional neural network. The pooling processing system includes a first storage device, a data region, a pooling computation kernel, and a pooling controller. The method includes: reading, by the pooling controller, k pieces of feature data from the first storage device in each reading cycle, the k pieces of feature data being components in a feature map generated by a convolution operation of the convolutional neural network, and k being an integer greater than 1; writing, by the pooling controller, the k pieces of feature data read from the first storage device into the data region, wherein the k pieces of feature data form one group among n groups of k pieces of data with each group arranged in a first dimension and the n groups arranged in a second dimension, wherein the n groups of k pieces of data are written into the data region in an updating cycle, wherein a duration of the updating cycle is n times a duration of the reading cycle, and wherein n cis an integer greater than 1; and transmitting, after the updating cycle is ended, data in the data region to the pooling computation kernel to perform a pooling operation, wherein the data in the data region comprises the n groups of k pieces of data and last m groups of data from a previous updating cycle with each group along the second dimension, wherein the last m groups of data are temporarily stored in the data region for use in pooling calculation by the pooling computation kernel in a next updating cycle. The technical solution in this application reduces the number of storage, numbers of reading and writing due to data reuses, and improves the efficiency of pooling processing.

A heat supply network hydraulic circuit modeling method for a comprehensive energy system scheduling is provided. The hydraulic analysis model is unified with the power network model, and the connection between the hydraulic dynamic state and the hydraulic steady state is established. Based on the characteristic equations of thermal pipelines, flow control valves and compressors, this method abstracts hydraulic circuit element models such as hydraulic resistance, hydraulic inductance, and hydraulic pressure source, establishes hydraulic branch characteristics of the heat supply network based on the above hydraulic circuit elements, establishes the hydraulic topology constraints of the heat supply network based on Kirchhoff-like voltage and current laws, and establishes the steady hydraulic network equation by combining the above hydraulic branch characteristics and hydraulic topology constraints.

A method for modeling a network topology of a subarea of a low-voltage network, wherein the network topology of the subarea of the low-voltage network is dynamically changeable by switching on, over and/or off components and/or by adding or removing components, where the network topology is modeled as a graph with nodes and edges, states valid for all edges of the graph at an initialization time are determined and assigned to the edges as the respective first state instance, with each subsequent change to the network topology, the respective current states valid for the respective edge from a time of the change to the network topology are determined for the edges of the graph, and each edge of the graph is assigned the respective state determined and currently valid from the time of the respective change to the network topology as a respective further state instance together with a timestamp.

A method for modeling a network topology of a subarea of a low-voltage network, wherein the network topology of the subarea of the low-voltage network is dynamically changeable by switching on, over and/or off components and/or by adding or removing components, where the network topology is modeled as a graph with nodes and edges, states valid for all edges of the graph at an initialization time are determined and assigned to the edges as the respective first state instance, with each subsequent change to the network topology, the respective current states valid for the respective edge from a time of the change to the network topology are determined for the edges of the graph, and each edge of the graph is assigned the respective state determined and currently valid from the time of the respective change to the network topology as a respective further state instance together with a timestamp.