68 results about "Evaluation treatment" patented technology

The invention relates to the field of geotechnical engineering, in particular to an evaluation processing method for entrainment superimposed settlement of pile groups. According to the method, by utilizing a solid deep foundation simplified calculation model, a calculation formula for stress fields of surrounding soil bodies of pile foundations is deduced, and from the analysis of the calculation of the settlement of the pile foundations to the calculation of the stress fields and displacement fields of the surrounding soil bodies of the pile foundations, the evaluation processing method for the entrainment settlement of the pile groups is formed, and meanwhile, the entrainment settlement calculation of a single pile group foundation can be expanded to the entrainment settlement calculation of multiple pile group foundations by using the method. The evaluation processing method for the entrainment superimposed settlement of the pile groups provided by the invention has the advantages that the stress fields of the surrounding soil bodies of equivalent pier foundations are completely deduced; a method of classical soil mechanics is introduced into the evaluation method for the entrainment settlement of the pile groups, and therefore, not only can the settlement of pile tips be evaluated, but also the entrainment superimposed influences of the pile group foundations on the surrounding soil bodies can be evaluated. The evaluation processing method for the entrainment superimposed settlement of the pile groups is clear in concept, simple in method and reliable in evaluation accuracy, and convenient for engineering application.

The invention relates to the field of financial science and technology, and discloses a federation learning development method, device and equipment and a storage medium, and the method comprises thesteps: determining a plurality of participants in an industrial development demand if the industrial development demand is detected, and determining a first evaluation model and a preset evaluation condition according to the industrial development demand, wherein different industrial development requirements correspond to different first evaluation models and different preset evaluation conditions; generating a random number of each participant according to the plurality of participants, and performing fusion evaluation processing on the first evaluation model based on the local data of each participant and the random number to obtain a fusion evaluation value; and according to the preset evaluation condition and the fusion evaluation value, performing federated learning training on the first evaluation model to obtain a second evaluation model. According to the method, the development process of the transverse federated learning algorithm is simplified, the algorithm development workload is reduced, and the algorithm development efficiency is improved.

The embodiment of the invention provides a selecting method of a participle lexicon and relates to the technical field of information. The method comprises the following steps: setting an evaluation processing device; leading a plurality of participle lexicons into the evaluation processing device and generating a plurality of evaluation values corresponding to the plurality of participle lexicons; and selecting the maximum evaluation value from the plurality of evaluation values, and taking the participle lexicon corresponding to the maximum evaluation value as a participle lexicon to be selected. The embodiment of the invention further provides a selecting system of the participle lexicon. The problem in the prior art that the participle lexicons cannot be directly and accurately selected is solved; compared with the prior art, the selecting method and system are relatively accurate and convenient and more time is saved; and long-time counting of user behavior characteristics is not needed and a verifiable method is provided for a pertinent search group.

A motion state evaluation system is provided with a motion analyzer obtains a value representing a motion state of the subject based on a ratio, to a reference length, of a distance between predetermined joints estimated on an image; a reference storage stores a height of a subject as the reference length; a motion analyzer obtains, as a value for use in evaluation of motion of the subject, the value representing the motion state of the subject from a feature point distance on the image of a plurality of anatomical feature points based on a ratio, to the height, of a distance on the image that is determined from the plurality of anatomical feature points and corresponds to the height of the subject; and an evaluation processor evaluates the motion of the subject based on the value representing the motion state.

The invention provides a user posture evaluation method and device, and processing equipment. The method and the device are used for remarkably reducing the application cost on the premise of ensuring a high-precision user posture evaluation effect, so that popularization and application are facilitated. The user posture evaluation method provided by the invention comprises the steps that a processing device acquires a target image of a to-be-evaluated user posture, the target image is obtained from a shooting target user, and the target image is a depth image shot by a depth camera; the processing device inputs the target image into an evaluation model, user posture evaluation processing is carried out, and the evaluation model is obtained by training the initial neural network model through different depth image training marked with corresponding user posture evaluation results; and the processing device extracts a user posture evaluation result output by the evaluation model.

The embodiment of the invention relates to an enterprise evaluation data processing method and device, and the method comprises the steps: obtaining enterprise economic data which comprises credit rating data, profit table data, asset and debt table data, credit extension service table data and guarantee service table data; according to the credit rating data, inquiring a first corresponding relation table reflecting the corresponding relation between the credit rating and the conversion coefficient, and generating a first coefficient; according to the first coefficient, the profit sheet data and the asset balance sheet data, performing enterprise operation evaluation processing to generate first evaluation data; performing enterprise risk assessment processing according to the credit service table data and the guarantee service table data to generate second assessment data; and according to the first evaluation data and the second evaluation data, performing enterprise overall evaluation processing to generate enterprise evaluation data. The method and the device provided by the invention can assist an enterprise in carrying out operation data analysis and self-evaluation, can help to improve the enterprise value and reduce the enterprise risk.

The invention is suitable for the technical field of artificial intelligence and data analysis, and provides an industrial development level evaluation method and device, electronic equipment and a storage medium, and the method comprises the steps of collecting the industrial data of a to-be-evaluated industry according to a preset evaluation index system; performing mutual relation scoring processing on the evaluation indexes configured in the evaluation index system to obtain relation scoring data among the evaluation indexes in the to-be-evaluated industry; performing weighting processing on each evaluation index according to the relation score data to obtain a weight value corresponding to each evaluation index; and performing industrial development level evaluation processing on the industrial data according to the weight value to obtain an evaluation score, and comparing the evaluation score with a preset reference score to generate an industrial development level evaluation result corresponding to the to-be-evaluated industry. According to the method, the one-sidedness caused by analyzing industrial development only through financial data is avoided, the randomness of subjective and perceptual evaluation is reduced, and the objectivity and fairness of evaluation are improved.

An assessment method which is capable of appropriately assessing review ability of a reviewer and a reward setting method which is capable of appropriately setting a reward to be paid to the reviewer are realized. A computer includes a memory and a controller, and the controller executes efficiency evaluation processing of evaluating review efficiency of a reviewer to be assessed in accordance with a predicted review period of each piece of electronic data and an actual review period, accuracy evaluation processing of evaluating review accuracy of the reviewer to be assessed by examining a review result by the reviewer to be assessed, and assessment processing of assessing review ability of the reviewer to be assessed in accordance with the review efficiency evaluated in the efficiency evaluation processing and the review accuracy evaluated in the accuracy evaluation processing.

The invention relates to an information evaluation processing method. The information evaluation method comprises the steps of obtaining evaluation reference rule information; acquiring user attributeinformation according to preset first system setting time by a server, and determining a user ID of the first type of users according to the user attribute information; obtaining user basic information according to the user ID, and determining evaluation reference parameters of each user according to the user basic information; inquiring evaluation performance parameters of each user in a presettime period before the first system setting time according to the user ID; performing weighted quantization processing according to the evaluation reference parameters and the evaluation performance parameters to generate evaluation data of the user; sorting the evaluation data of all the first type of users to obtain evaluation ranking information; determining a second user according to the firstpreset proportionality coefficient or the first preset quantity and the evaluation ranking information; and adding user basic information items to the second user, and adding evaluation item information corresponding to the evaluation item ID to the user basic information.

The invention provides a multi-terminal asynchronous remote visual training method and system. The method comprises the steps that: a training plan making end makes a visual training plan according to user information and optimizes the visual training plan according to training feedback data and supervision feedback data; a VR training end executes the visual training plan and continuously collects training data of a user to form training feedback data; and the training process of the visual training plan is displayed on a supervision end, and the supervision end performs evaluation processing on the training process to form supervision feedback data. With the multi-terminal asynchronous remote vision training method and system of the invention adopted, remote visual training can be carried out, a multi-terminal asynchronous mechanism is formed, the training plan making end can optimize the visual training plan at any time according to data fed back by the VR training end and the supervision end. The multi-terminal asynchronous remote vision training method and system aim to reduce the risk of bad training results and improve the visual training efficiency of the user.

The invention discloses a processor performance evaluation method, which is suitable for generating an evaluation component for evaluating the performance of a processor, and the evaluation component comprises at least one adjustable parameter. The method comprises the following steps: obtaining an execution result sequence of a calibration program executed by the processor, the execution result sequence comprising a plurality of instructions arranged according to an execution sequence; calculating a performance index value of the processor by using the current evaluation component according to the execution result sequence; acquiring accumulative operation information of the processor during the period of executing the calibration program, and determining an actual performance index value of the processor according to the accumulative operation information; and adjusting parameters of the evaluation component by comparing the performance index value calculated by the evaluation component with the performance index value so as to reduce an error between the performance index value calculated by the evaluation component and an actual performance index value. The invention also discloses a processor performance evaluation method for evaluating the performance of the processor by adopting the generated evaluation component and a corresponding device.

The invention discloses a satellite health assessment method based on a Gaussian mixture model, and the method comprises the steps: respectively carrying out the preprocessing feature extraction of obtained normal operation multi-dimensional remote parameter data and current operation multi-dimensional remote parameter data, and obtaining a normal high-dimensional feature vector and a current high-dimensional feature vector; performing training processing on an initial Gaussian mixture model by using the normal high-dimensional feature vector to obtain a trained normal Gaussian mixture model,and performing training processing on the trained normal Gaussian mixture model by using the current high-dimensional feature vector to obtain a trained current Gaussian mixture model; calculating theoverlapping degree of the trained normal Gaussian mixture model and the trained current Gaussian mixture model, and performing normalization processing on the overlapping degree to obtain a current health degree index value; and performing evaluation processing on the satellite health state by using the plurality of current health degree index values.

The invention relates to the field of data analysis, and discloses a sewage treatment quality evaluation method based on an AHP-entropy weight method, which comprises the following steps: calculating an analytic hierarchy weight of a sewage treatment detection index by using a paired comparison matrix of the sewage treatment detection index, and carrying out weighting to obtain a target treatment evaluation hierarchical structure model; calculating information entropy according to category index evaluation values of the sewage treatment detection indexes according to sewage treatment rating categories, calculating entropy weights of the sewage treatment detection indexes according to an entropy weight calculation formula, correcting the hierarchical analysis weights by using the entropy weights, obtaining a target evaluation hierarchical entropy weight structure model, obtaining index detection values, and obtaining a target evaluation hierarchical entropy weight structure model; and rating the to-be-evaluated treated sewage by using the target evaluation hierarchical entropy weight structure model. The invention further provides a sewage treatment quality evaluation device based on the AHP-entropy weight method, electronic equipment and a computer readable storage medium. The method can solve the problem that the judgment of the sewage treatment quality lacks standardization and pertinence.

The invention relates to a delirium risk assessment device based on a hospital information system, in particular to a delirium risk assessment device for a to-be-assessed object such as an ICU patient, and at least one of the language expression ability, the physical activity ability and the facial expression ability of the to-be-assessed object is limited. The evaluation device at least comprises: an evaluation processing module configured to combine the plurality of evaluation values about the at least one delirium feature and determine whether the combination satisfies a predetermined evaluation condition; when a combination of a plurality of evaluation values about at least one delirium feature obtained by performing delirium consciousness fuzzy rapid evaluation on the to-be-evaluatedobject does not meet a predetermined evaluation condition, historical information related to the to-be-evaluated object in a hospital information system is called, secondary evaluation in combinationwith medical information and/or evaluation information in the historical information is performed, and a delirium potential risk level of the to-be-evaluated object is determined based on a dynamic delirium risk evaluation strategy.

The invention provides an anesthesia visit evaluation method, electronic equipment and a computer storage medium. The method comprises the following steps: analyzing preoperative data information, and determining first visit problem information matched with the preoperative data information from multiple pieces of visit problem information stored in a server; sending the first visit problem information to the patient end, so that the patient end receives the first visit problem information, and feeds back the first visit problem information to the patient, so that the patient replies the first visit problem information; first visit reply information corresponding to the first visit question is received, the preoperative data information and the first visit reply information are input into a deep neural network model for evaluation processing, and a preliminary anesthesia diagnosis result is obtained; and sending the preliminary anesthesia diagnosis result to a doctor terminal, and enabling the doctor terminal to display the preliminary anesthesia diagnosis result, so that a doctor determines a target anesthesia diagnosis result based on the preliminary anesthesia diagnosis result. According to the anesthesia visit evaluation method, the accuracy of anesthesia visit evaluation is improved.