6results about How to "Reduce evaluation error" patented technology

The invention discloses a mountain photovoltaic power station equipment self-organizing group irradiance assessment method and a related device, and belongs to the technical field of photovoltaic power station operation and maintenance. The method comprises the steps of obtaining related data of an area where a target mountain photovoltaic power station is located, and generating a power station three-dimensional digital body containing terrain and equipment information; based on the three-dimensional digital body of the power station, dynamically clustering photovoltaic equipment with adjacent spatial positions and similar irradiation environment characteristics, and dividing the photovoltaic equipment into a plurality of self-organizing groups; dividing a continuous terrain area covered by each self-organizing group into a plurality of evaluation grids according to preset grid precision; based on the evaluation grids, calculating to obtain a theoretical irradiance value of each evaluation grid in a specified time period by using an irradiation transmission model; and aggregating the theoretical irradiance values of all the evaluation grids in the same self-organizing group, and generating a comprehensive irradiance evaluation value representing the overall irradiation level of the self-organizing group.

This invention relates to the field of image processing technology, and more particularly to a method and system for assessing the quality of prefabricated construction based on image processing. The method includes the following steps: after removing the EVA transport protective padding that came with the prefabricated construction components, a panoramic image of the component splicing surface is captured using an industrial camera to obtain an original image containing the natural adhesion marks of the padding; multi-scale edge enhancement processing is performed on the original image to extract the contour data of the adhesion marks, and the global flatness of the component splicing surface is calculated based on the deformation features of the contour data; an industrial camera is used in a ring array to capture images of the pre-reserved grouting holes in the components, and the grouting hole boundaries are extracted after contour sharpening processing of the images; the three-dimensional axis of the grouting holes is constructed by combining the reflective features of the inner sidewalls of the holes. This invention achieves accurate detection and standardized assessment of the quality of prefabricated components through multi-polarized light sources and ring camera imaging technology, ultimately improving the accuracy of construction quality assessment.

The invention relates to the technical field of reservoir structure safety control in water conservancy projects, in particular to an anti-sliding stability control method under the working condition of two-way sudden water level drop of a plain reservoir partition dam, which comprises the following steps: S1, working condition initialization and boundary condition definition; s2, carrying out seepage-stress coupling analysis; s3, solving an anti-sliding stability coefficient; s4, performing multi-objective optimization on the structural parameters; s5, verifying the efficiency of the waterproof and drainage system; s6, construction parameter simulation: fitting a soil material dry density-water content relationship through compaction test data, and determining an optimal construction water content and compaction degree parameter; and S7, performing dynamic early warning in an operation period. The anti-slip stability coefficient is accurately solved by constructing the seepage-stress bidirectional coupling analysis model and combining the strip division method, the internal mechanical response and potential slip crack surface characteristics of the dam body under the working condition of bidirectional sudden water level drop can be accurately captured, the anti-slip stability evaluation error is reduced, and a reliable quantitative basis is provided for safety management and control of the partition dam.

According to the sampling test evaluation method for the tailings, the electronic equipment and the storage medium, classified sampling is carried out on different tailings discharge types, and it is ensured that the taken sample tailings have high representativeness in time and space. Evaluation errors caused by sampling deviation are fundamentally reduced, and the accuracy of evaluation results is improved. The phase factor influence coefficient based on phase analysis can quantify the proportion of recyclable elements, and is used for evaluating the recoverability. The dissociation degree factor influence coefficient based on dissociation degree analysis can quantify the restriction of the mineral intergrowth state on target element recovery, and is used for evaluating the selectability. The particle size factor influence coefficient based on particle size analysis can quantitatively evaluate the influence of the particle size on the beneficiation efficiency, and is used for evaluating the recoverability. The concentrate recovery rate is determined according to the constraint relation of the three dimensions, the tailing evaluation result is determined according to the concentrate recovery rate and the tailing comprehensive grade, and a direct basis is provided for making a targeted technical scheme for tailing recovery.

The invention relates to an electric power system benefit evaluation method and system considering the implementation influence of a technical standard system, and the method comprises the following steps: collecting the business data of an electric power system in real time, the business data of the electric power system comprising power grid planning data, scheduling operation data and operation and maintenance data; based on the collected power system business data, a multi-level evaluation index system considering implementation benefits of the technical standard system is constructed, and the multi-level evaluation index system comprises a first-level index, a second-level index and a bottom-level index; based on the multi-level evaluation index system, determining each index weight by adopting an analytic hierarchy process and a DELPHI expert method; calculating implementation benefits through a full-chain value decomposition method based on the multi-level evaluation index system and the determined weight of each index; and generating an evaluation report based on the calculated implementation benefit, and feeding back the evaluation report to optimize a data acquisition strategy.

The invention discloses a learning rejection behavior evaluation method and device, electronic equipment and a readable storage medium. The method comprises the steps of obtaining at least two course videos corresponding to a to-be-evaluated object in a preset evaluation interval, and inputting the at least two course videos into a target evaluation model; for any course video in the at least two course videos, acquiring a multi-modal feature sequence corresponding to the to-be-evaluated object; performing state analysis on the multi-modal feature codes corresponding to the multi-modal feature sequence through expert networks of at least two dimensions in the target evaluation model to obtain learning state features of at least two dimensions; and based on the learning state features corresponding to the at least two dimensions corresponding to the at least two course videos, obtaining a learning state score corresponding to the to-be-evaluated object output by the target evaluation model. Therefore, the learning state score is obtained based on the multi-course video and the multi-dimensional learning state features, so that the evaluation result is more practical, and the evaluation accuracy and interpretability are improved.