9results about How to "Choose science" patented technology

The invention discloses an intelligent occupational ability assessment method and device, equipment and a storage medium, and belongs to the technical field of artificial intelligence. The method comprises the steps of obtaining user basic information of a to-be-evaluated user, and generating a user basic information tag based on the user basic information; based on a pre-trained occupational interest evaluation model and a workplace character evaluation model, obtaining an occupational adaptation type label, a workplace character type label and a psychological state type label; importing the user basic information tag, the occupational adaptation type tag, the workplace character type tag and the psychological state type tag into an occupational adaptation degree model to obtain an occupational ability adaptation degree tag and a psychological state adaptation degree tag; and importing the vocational ability adaptation degree tag and the psychological state adaptation degree tag into a vocational recommendation degree model to obtain a vocational recommendation result of the to-be-evaluated user. The invention further relates to the technical field of block chains, and the user information is stored on a block chain network. According to the method and the device, personalized evaluation labels and recommendation results can be dynamically generated.

The invention provides a power line carrier and wireless communication combined power data transmission method and system, and the method comprises the steps: collecting the operation data of terminal power equipment in real time through terminal collection equipment in a power distribution area, and adding a timestamp for the data; and the hybrid communication sub-equipment transmits the operation data with the timestamp to the hybrid communication main equipment of the substation by using the power line carrier. And after receiving the data, the main device calculates the communication distance between the power distribution area and the transformer substation according to the timestamp information, and selects a proper communication mode. And the master device continues to monitor and calculate the bit error rate, obtains parameters such as the signal-to-noise ratio, the attenuation value and the interference intensity of the communication channel, and inputs the parameters into the pre-trained support vector machine to predict the current bit error rate. And based on a prediction result, a communication distance, a load and other factors, a pre-trained reinforcement learning model is adopted to adaptively select an optimal communication mode, and the communication mode is dynamically adjusted to optimize a data transmission effect.

The invention provides a replacement cable selection method, and relates to the technical field of cable replacement, and the method comprises the steps: calculating the conductor shielding field intensity of a to-be-replaced cable and the insulation shielding field intensity of the to-be-replaced cable; performing preliminary screening from existing selectable cables to obtain a sample cable set; obtaining all types of performance evaluation values of each sample cable in each monitoring period; constructing a performance comprehensive evaluation matrix corresponding to each monitoring period of each sample cable; a comprehensive performance evaluation value of each sample cable is calculated, and a replacement cable is selected based on the comprehensive performance evaluation value of each sample cable. The replacement cable is selected through systematic steps, the scientificity of the selection process of the replacement cable is ensured, the electrical performance parameters of the to-be-replaced cable are fully considered, the influence of the actual parameters and limiting conditions of the construction environment on the replacement cable is emphasized, the possibility of cable failure is reduced, and the construction efficiency is improved. And the total cost of laying and later maintenance is fully considered in the cable selection process, so that the operation cost is reduced.

The present application relates to the technical field of hydrogen fuel cell vehicles, and discloses a method, system, device and medium for coordinated control of multiple power sources of hydrogen fuel cell vehicles, including: obtaining the working condition data of the hydrogen fuel cell vehicle, and determining the typical working condition mode corresponding to the working condition data; determining the initial power allocation value corresponding to each power source according to the typical working condition mode; generating the optimal first power allocation scheme corresponding to the hydrogen fuel cell vehicle in the future; generating the optimal second power allocation scheme corresponding to the hydrogen fuel cell vehicle in the future; selecting the optimal power target allocation scheme under the typical working condition mode according to the optimal first power allocation scheme and the optimal second power allocation scheme, and sending the optimal power target allocation scheme to the vehicle control system to realize coordinated control of multiple power sources. Its beneficial effect is to make rapid and accurate decisions under rapidly changing working conditions.

This invention belongs to the field of cutting parameter optimization technology, specifically relating to a multi-objective cutting parameter optimization method, including: acquiring cutting parameters and machine tool spindle power signals, calculating cutting specific energy, and simultaneously acquiring surface roughness; constructing a BP neural network model, optimizing the connection weights and thresholds of the BP neural network model using the Harris Eagle optimization algorithm to minimize the fitness function, and establishing a cutting specific energy prediction model; constructing a surface roughness prediction model with the encoded variables of cutting parameters as input and surface roughness as output, and establishing a multi-objective cutting parameter optimization model; solving the multi-objective cutting parameter optimization model to obtain the Pareto non-dominated solution set, using the entropy weight method for comprehensive decision-making, and selecting the solution with the largest comprehensive evaluation value as the optimal cutting parameter combination. This invention, through methods such as the BP neural network improved by the Harris Eagle optimization algorithm, reduces machining energy consumption, improves surface roughness, and enhances overall machining performance.

The present application relates to the vulnerability evaluation method of immovable cultural relics, comprising the following steps: 1, determining the vulnerability evaluation index; 2, determining the evaluation index vulnerability value grading standard; 3, obtaining evaluation index data and vulnerability value assignment; 4, determining the vulnerability evaluation index weight; 5, constructing the vulnerability evaluation model; 6, dividing the vulnerability level; 7, calculating the vulnerability index; 8, determining the vulnerability level of immovable cultural relics. The method of the present application can well evaluate the vulnerability of immovable cultural relics under the influence of natural disasters such as flood, earthquake and other disasters at different scales, and has universal applicability.

The invention discloses a method for detecting the exterior wall of a building, and relates to the technical field of detecting the exterior wall of a building. A data detection module is used to respectively detect and experimentally obtain detection data of a pore volume KXZ, a pore surface area KXB, an average particle diameter KLZ, a particle density KM, a Darcy coefficient d, an external pressure difference WY, a material thickness CH and a weathering resistance coefficient KF. The maintenance cost WC, a maintenance cycle WZ and the detection data of historical data of the building exterior wall are combined, and a data evaluation processing module is used to evaluate the pore characteristics, permeability and durability. The detection and evaluation results of the pore characteristics, permeability and durability are comprehensively analyzed to evaluate the overall performance of the exterior wall, and corresponding repair, transformation and reinforcement suggestions are proposed according to the evaluation results. The invention realizes a comprehensive and accurate evaluation of the performance of the exterior wall material by constructing a comprehensive evaluation system, adopting a quantitative evaluation method, optimizing material selection and guiding construction and maintenance.

The invention provides a screening method and system for a blast furnace heat prediction model, and relates to the technical field of blast furnace smelting. The method comprises the following steps: training a plurality of candidate prediction models; calculating a combined evaluation index of each model for furnace heat abnormity early warning, wherein the indexes comprise three indexes for measuring prediction accuracy, abnormity capture capability and early warning advance; and determining an optimal prediction model according to an evaluation result of the combined evaluation indexes. According to the method, the combined evaluation indexes oriented to abnormal early warning are constructed, so that the model evaluation standard is aligned with the actual production demand, the screened optimal model has the capability of accurately early warning the key furnace heat abnormality in advance, precious reaction time can be won for field operators, and the method has relatively high practical value.

The present application belongs to the technical field of oil and gas development and exploitation engineering, and particularly relates to a method for selecting a sand control mode of an oil and gas well in a loose sandstone reservoir. The method is based on stablely obtainable geological and production parameters in an engineering field, and a parameter obtainability index PAI is introduced i The sand control evaluation indexes are screened, and based on historical operation data and the screened sand control indexes, main sand control indexes of different sand control modes are screened, and the main sand control indexes of the screened sand control modes are divided into positive indexes and negative indexes. On this basis, an applicability index (UI), a failure risk index (FRI) and a comprehensive adaptation index (CSI) are respectively calculated, so as to realize quantitative evaluation and optimization of the sand control mode, and overcome problems of the existing sand control mode selection method, such as small coverage of the selected sand control mode, single factor considered, strong subjectivity, large calculation amount, and difficult parameter acquisition.