CN116895338B - Method and system for improving dendrimer research model - Google Patents
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Abstract
The invention provides an improved method and system of a dendrimer research model, wherein the method comprises the following steps: step 1: acquiring a research record of a dendrimer research model; step 2: according to the research records, carrying out improvement judgment on the dendrimer research model, and obtaining a judgment result of the improvement judgment; step 3: if the judgment result is that improvement is needed, the corresponding dendrimer research model is taken as a model to be improved; step 4: acquiring a first target improvement parameter of a model to be improved; step 5: and correspondingly improving the model to be improved according to the first target improvement parameter. According to the method and the system for improving the dendrimer research model, the dendrimer research model is improved and judged according to the research record of the obtained dendrimer research model, when the dendrimer research model is judged to be improved, the first target improvement parameter of the model to be improved is obtained for improvement, the simulation result of the dendrimer research model is more accurate, and the rationality of a conclusion taking the simulation result as a deduction basis is improved.
Description
Technical Field
The invention relates to the technical field of electric digital data processing, in particular to an improved method and system of a dendrimer research model.
Background
The dendrimer research model is a model used to study molecular structure and properties. In this model, a molecule is considered a tree of atoms and chemical bonds, an atom being a node of the tree and a chemical bond being an edge of the tree. The nature of the molecule can be understood by analyzing the tree structure.
One of the advantages of the dendrimer model is that it can be used to describe complex molecular structures, such as: macromolecules and biomolecules. This is because the tree structure can be broken down layer by layer so that researchers can better understand the components of the molecules and the interactions between them. In another aspect, the dendrimer model may be used to develop molecular modeling algorithms, such as: molecular dynamics simulation and monte carlo simulation. These algorithms can be used to predict the nature of a molecule, for example: stability, reactivity and optical properties, as well as dynamic behavior of molecules, such as: molecular motion and chemical reactions. Dendrimer models can also be used to design new molecular structures, such as: in pharmaceutical design and materials science. By understanding the tree structure and interactions of molecules, researchers can design more efficient drugs and materials.
The application number is: the invention patent of CN202110401549.1 discloses a gas property verification method based on a virtual experiment, wherein the method comprises the following steps: acquiring first information, wherein the first information is used for expressing gesture actions acquired by an operation end; operating the gas model on the virtual experiment platform according to the first information to generate an operation flow; sending the operation flow to a server; and obtaining improvement opinion from the server, and improving the operation flow according to the improvement opinion. The invention can save the experimental cost, can intuitively display the internal molecular structure through a three-dimensional gas molecular model, ensures students to have deeper knowledge on the molecular structure, and improves the enthusiasm of learning; meanwhile, the gas property is verified through the virtual experiment, the harm to the body of students caused by some harmful gases can be effectively avoided, the method has very good popularization and use values, and the chemical classroom can be more vivid and interesting.
However, after the three-dimensional gas molecular model is built, the accuracy of the three-dimensional gas molecules simulated by the three-dimensional gas molecular model is not verified in the prior art, when the three-dimensional gas molecular model is unreliable, the simulation accuracy is low, and further, the internal structure of the molecules presented to students later is unreasonable.
In view of the foregoing, there is a need for an improved method and system for tree-shaped molecular research models that address at least the above-mentioned shortcomings.
Disclosure of Invention
According to the method, a dendrimer research model is improved, a judgment result is obtained by judging the dendrimer research model according to the research record of the obtained dendrimer research model, and when the judgment result is that improvement is needed, a first target improvement parameter of the model to be improved is obtained for corresponding improvement, so that the accuracy of the simulation result of the dendrimer research model is improved, and the rationality of a conclusion taking the simulation result as a deduction basis is further improved.
The method for improving the dendrimer research model provided by the embodiment of the invention comprises the following steps:
step 1: acquiring a research record of a dendrimer research model;
step 2: according to the research records, carrying out improvement judgment on the dendrimer research model, and obtaining a judgment result of the improvement judgment;
step 3: if the judgment result is that improvement is needed, the corresponding dendrimer research model is taken as a model to be improved;
step 4: acquiring a first target improvement parameter of a model to be improved;
step 5: and correspondingly improving the model to be improved according to the first target improvement parameter.
Preferably, step 1: obtaining a study record of a dendrimer study model, comprising:
acquiring the current moment and simultaneously acquiring the target moment of a historical output record of the dendrimer research model;
acquiring time screening requirements;
and determining research records in the historical output records according to the time screening requirement, the current time and the target time.
Preferably, step 2: according to the research record, carrying out improvement judgment on the dendrimer research model to obtain a judgment result of the improvement judgment, wherein the method comprises the following steps:
acquiring improved judgment standard parameters;
obtaining the construction basis of a dendrimer research model;
determining model parameters according to the construction basis;
obtaining a comparison type of model parameters corresponding to improved decision criterion parameters, the comparison type comprising: direct and indirect controls;
when the comparison type is direct comparison, the corresponding model parameter is used as a first target parameter, improvement judgment is carried out according to the first target parameter and the improvement judgment standard parameter, and a first judgment sub-result is obtained;
when the comparison type is indirect comparison, the corresponding model parameter is used as a second target parameter;
determining a comparison parameter according to the second target parameter;
performing improvement judgment according to the comparison parameter and the improvement judgment standard parameter to obtain a second judgment sub-result;
the first judging sub-result and the second judging sub-result are used as judging results together;
wherein obtaining the improved decision criterion parameter comprises:
acquiring historical experimental data;
training a theoretical data prediction model according to historical experimental data;
obtaining a simulation demand;
inputting the simulation demand into a theoretical parameter prediction model, obtaining predicted theoretical parameters, and taking the theoretical parameters as improved judgment standard parameters.
Preferably, determining the control parameter based on the second target parameter comprises:
acquiring a plurality of conversion channels;
acquiring a first parameter type of a second target parameter;
inputting a second target parameter into a channel interface corresponding to the conversion channel according to the first parameter type;
and obtaining an output result correspondingly output by the conversion channel after the second target parameter is input into the channel interface, and taking the output result as a comparison parameter.
Preferably, step 4: obtaining a first target improvement parameter of a model to be improved, comprising:
if the judgment result is that improvement is needed, analyzing the corresponding judgment result, and acquiring the improvement direction of the model to be improved;
acquiring a target improvement record according to the improvement direction;
acquiring an improvement strategy parameterization record corresponding to the target improvement record;
determining an adaptive parameterized template corresponding to the improvement direction according to the target improvement strategy parameterized record;
the target improvement record is input into an adaptive parameterization template to obtain a first target improvement parameter.
Preferably, step 5: according to the first target improvement parameter, correspondingly improving the model to be improved, including:
determining a first parameter distance value according to the first target improvement parameter and the current parameter acquired in real time;
determining a second parameter distance value of a target parameter distance preset by the first parameter distance value;
determining a fluctuation improvement parameter range according to the second parameter distance value;
according to the fluctuation improvement parameter range, simulating to improve the model to be improved, and obtaining a simulation improvement result;
determining a second target improvement parameter of the target simulation improvement result according to the simulation improvement result; when a second target improvement parameter of the target simulation improvement result is determined according to the simulation improvement result, determining a difference between the simulation improvement result and a predicted result of a research requirement corresponding to the simulation improvement result, taking the simulation improvement result with the smallest difference as the target simulation improvement result, and taking a first target improvement parameter corresponding to the target simulation improvement result as the second target improvement parameter;
and correspondingly improving the model to be improved according to the second target improvement parameter.
Preferably, according to the second target improvement parameter, the model to be improved is correspondingly improved, including:
acquiring a second parameter type of a second target improvement parameter;
constructing an empty parameter adjustment array according to the second parameter type and a preset parameter type-array element position library;
writing a second target improvement parameter of a second parameter type into the position of an array element of the null parameter adjustment array corresponding to the second parameter type to obtain a parameter adjustment array;
and according to the parameter adjustment array, performing parameter adjustment of the model to be improved.
The method for improving the dendrimer research model provided by the embodiment of the invention further comprises the following steps:
step 6: acquiring a first research conclusion of a research record and a second research conclusion of an improved model to be improved, judging repeated simulation requirements according to the first research conclusion and the second research conclusion, and if the judgment result of the repeated simulation requirements is that repeated simulation is required, performing corresponding repeated simulation;
and performing repeated simulation demand judgment according to the first research conclusion and the second research conclusion, wherein the repeated simulation demand judgment comprises the following steps:
acquiring a first study item of a first study conclusion;
acquiring a second study item of a second study conclusion;
determining a degree of project similarity of the first study and the second study;
if the item similarity is greater than or equal to a preset item similarity threshold, taking the corresponding first research item as a third research item, and taking a first research conclusion corresponding to the third research item as a third research conclusion;
determining conclusion deviations based on semantic analysis techniques from the second and third study conclusions;
if the conclusion deviation is greater than or equal to a preset conclusion deviation threshold, repeated simulation is needed, otherwise, the repeated simulation is not needed.
Preferably, if the determination result of the repeated simulation demand determination is that repeated simulation is required, performing corresponding repeated simulation includes:
if the judgment result of the repeated simulation demand judgment is that repeated simulation is needed, the corresponding third research project is used as a fourth research project;
acquiring a historical application node of a fourth research project, and simultaneously acquiring an allocable contact resource;
judging whether the allocable contact resources can support and notify the historical application node according to the historical application node and the allocable contact resources, if so, carrying out concurrent notification;
if the allocable contact resources cannot support and inform the historical application node, determining the receiving time of the historical application node for receiving a fourth research conclusion of the fourth research project;
and according to the order of the receiving time from the early to the late, the allocable contact resources are sequentially scheduled for notification.
The improved system of the dendrimer research model provided by the embodiment of the invention comprises:
the research record acquisition subsystem is used for acquiring research records of the dendrimer research model;
the judgment result acquisition subsystem is used for carrying out improvement judgment on the dendrimer research model according to the research record to acquire a judgment result of improvement judgment;
the model to be improved determines a subsystem, and is used for taking a corresponding dendrimer research model as a model to be improved if the judgment result is that improvement is needed;
the improved parameter acquisition subsystem is used for acquiring a first target improved parameter of the model to be improved;
and the improvement subsystem is used for correspondingly improving the model to be improved according to the first target improvement parameter.
The beneficial effects of the invention are as follows:
according to the invention, the dendrimer research model is improved, the judgment result is obtained by judging the dendrimer research model according to the research record of the obtained dendrimer research model, and when the judgment result is that the modification is needed, the first target modification parameter of the model to be modified is obtained for corresponding modification, so that the accuracy of the simulation result of the dendrimer research model is improved, and the rationality of the conclusion taking the simulation result as the deducing basis is further improved.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims thereof as well as the appended drawings.
The technical scheme of the invention is further described in detail through the drawings and the embodiments.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 is a schematic diagram of an improved method of a dendrimer study model in an embodiment of the present invention;
FIG. 2 is a schematic diagram of an improved system of dendrimer research models in an embodiment of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described below with reference to the accompanying drawings, it being understood that the preferred embodiments described herein are for illustration and explanation of the present invention only, and are not intended to limit the present invention.
The embodiment of the invention provides an improved method of a dendrimer research model, as shown in figure 1, comprising the following steps:
step 1: acquiring a research record of a dendrimer research model; wherein, the dendrimer research model is: the dendrimer model is a model used for researching the structure and properties of the dendrimer; the study record is: comparing and recording the simulation result and the theoretical result output by the dendrimer research model;
step 2: according to the research records, carrying out improvement judgment on the dendrimer research model, and obtaining a judgment result of the improvement judgment; wherein the improvement is determined as: judging whether a dendrimer research model needs to be improved; the judgment result is as follows: improvements are needed or are not needed;
step 3: if the judgment result is that improvement is needed, the corresponding dendrimer research model is taken as a model to be improved; the model to be improved is as follows: a dendrimer study model for which improvement determination is determined to be necessary;
step 4: acquiring a first target improvement parameter of a model to be improved; wherein the first target improvement parameter is: the model to be improved needs to be improved in optimal parameter setting of model parameters, and the model parameters are as follows: the optimal parameters are set as follows, such as the type of atoms, the type and length of chemical bonds, the charge distribution, the initial velocity and position in molecular force field and molecular dynamics simulation, etc: setting model parameters and what parameters take values;
step 5: and correspondingly improving the model to be improved according to the first target improvement parameter. When the model to be improved is correspondingly improved according to the first target improvement parameter, the model parameter of the model to be improved is adjusted to the first target improvement parameter.
The working principle and the beneficial effects of the technical scheme are as follows:
according to the method, the device and the system, the dendrimer research model is improved, the judgment result is obtained by judging the dendrimer research model according to the research record of the obtained dendrimer research model, when the judgment result is that improvement is needed, the first target improvement parameter of the model to be improved is obtained, corresponding improvement is carried out, the accuracy of the simulation result of the dendrimer research model is improved, and the rationality of a conclusion taking the simulation result as a deduction basis is further improved.
When the method is applied specifically, research records of a dendrimer research model are obtained in real time, improvement judgment is carried out, and when improvement is judged to be needed, a first target improvement parameter for improvement is determined to carry out improvement.
In one embodiment, step 1: obtaining a study record of a dendrimer study model, comprising:
acquiring the current moment and simultaneously acquiring the target moment of a historical output record of the dendrimer research model; wherein, the current moment is: local time recorded by the system; the history output record is: historical research records corresponding to the dendrimer research model; the target time is: the output time of the historical output record recorded by the system;
acquiring time screening requirements; wherein, the time screening demand is: historical study records of which time period need to be screened;
and determining research records in the historical output records according to the time screening requirement, the current time and the target time. When determining the research record in the historical output record according to the time screening requirement, the current time and the target time, determining the screening time in the target time according to the time screening requirement and the current time, and taking the historical output record corresponding to the screening time as the research record.
The working principle and the beneficial effects of the technical scheme are as follows:
according to the method and the device, the time screening requirement is introduced, and the research record in the history output record is determined according to the time screening requirement, the current time and the target time, so that the acquisition suitability of the research record is improved.
In one embodiment, step 2: according to the research record, carrying out improvement judgment on the dendrimer research model to obtain a judgment result of the improvement judgment, wherein the method comprises the following steps:
acquiring improved judgment standard parameters; wherein, the improved judgment standard parameters are as follows: model parameters meeting the research requirements of a dendrimer research model;
obtaining the construction basis of a dendrimer research model; wherein, the construction basis is: constructing requirements;
determining model parameters according to the construction basis; wherein, the model parameters are: real-time parameters of the dendrimer study model;
obtaining a comparison type of model parameters corresponding to improved decision criterion parameters, the comparison type comprising: direct and indirect controls; wherein, the direct contrast is: directly comparing the model parameters with corresponding improved judging standard parameters; the indirect controls were: the model parameters indirectly influence the improved judgment standard, and the model parameters are converted to obtain a conversion result which directly influences the judgment standard for comparison;
when the comparison type is direct comparison, the corresponding model parameter is used as a first target parameter, improvement judgment is carried out according to the first target parameter and the improvement judgment standard parameter, and a first judgment sub-result is obtained; when the improvement judgment is carried out according to the first target parameter and the improvement judgment standard parameter, judging whether the first target parameter is in a range specified by the improvement judgment standard parameter, if so, judging that the first judgment result is that improvement is not needed, otherwise, judging that the first judgment result is needed;
when the comparison type is indirect comparison, the corresponding model parameter is used as a second target parameter;
determining a comparison parameter according to the second target parameter; wherein, the control parameters are: the second target parameter can be directly compared with the improved judgment standard parameter after being converted;
performing improvement judgment according to the comparison parameter and the improvement judgment standard parameter to obtain a second judgment sub-result; wherein, the improvement judgment is carried out according to the control parameter and the improvement judgment standard parameter: judging whether the comparison parameter is in the range specified by the improved judgment standard parameter, if so, judging that the second judgment result is that improvement is not needed, otherwise, judging that the second judgment result is that improvement is needed;
the first judging sub-result and the second judging sub-result are used as judging results together;
wherein obtaining the improved decision criterion parameter comprises:
acquiring historical experimental data; wherein, historical experimental data is: experimental data of dendrimer studies were historically performed;
training a theoretical data prediction model according to historical experimental data; the theoretical data prediction model is as follows: an artificial intelligence model for replacing model parameter prediction of manually performing theory according to simulation requirements;
obtaining a simulation demand; wherein, the simulation demand is: the modeling of what dendrimers are needed;
inputting the simulation demand into a theoretical parameter prediction model, obtaining predicted theoretical parameters, and taking the theoretical parameters as improved judgment standard parameters.
The working principle and the beneficial effects of the technical scheme are as follows:
according to the method, the improved judgment standard parameters are introduced, meanwhile, model parameters of the dendrimer research model are obtained, the comparison type is introduced, when the comparison type is direct comparison, the first target parameters and the improved judgment standard parameters are directly compared for improved judgment, when the comparison type is indirect comparison, the second target parameters are converted into the comparison parameters for improved judgment, and then the improved judgment is carried out, so that the judgment efficiency of the improved judgment is improved.
In one embodiment, determining the control parameter based on the second target parameter comprises:
acquiring a plurality of conversion channels; wherein, the conversion channel is: converting the second target parameter into a conversion formula model of the comparison parameter;
acquiring a first parameter type of a second target parameter; the first parameter type is as follows: the type of parameters;
inputting a second target parameter into a channel interface corresponding to the conversion channel according to the first parameter type; wherein, the channel interface is: converting an input end corresponding to a parameter of a first parameter type in the formula model;
and obtaining an output result correspondingly output by the conversion channel after the second target parameter is input into the channel interface, and taking the output result as a comparison parameter.
The working principle and the beneficial effects of the technical scheme are as follows:
according to the method and the device, the conversion channel is obtained, meanwhile, the first parameter type of the second target parameter is introduced, the second target parameter is input into the channel interface corresponding to the conversion channel according to the first parameter type, the second target parameter is input into the channel interface corresponding to the conversion channel, the output result of the conversion channel is obtained, and the normalization of the comparison parameter obtaining is improved.
In one embodiment, step 4: obtaining a first target improvement parameter of a model to be improved, comprising:
if the judgment result is that improvement is needed, analyzing the corresponding judgment result, and acquiring the improvement direction of the model to be improved; wherein, the improvement direction is: the type of parameters to be improved of the model to be improved;
acquiring a target improvement record according to the improvement direction; wherein, the target improvement record is: a history parameter adjustment record corresponding to the direction of improvement;
acquiring an improvement strategy parameterization record corresponding to the target improvement record; wherein, the improvement policy parameterization record is: acquiring a process record of the parameterized improvement strategy according to the target improvement record;
determining an adaptive parameterized template corresponding to the improvement direction according to the target improvement strategy parameterized record; wherein, the adaptive parameterized template is: the constraint only carries out the adaptability parameterization of the improvement strategy in the improvement direction, and the adaptability parameterization is as follows: adaptively generating an improvement strategy parameter suitable for a model to be improved;
the target improvement record is input into an adaptive parameterization template to obtain a first target improvement parameter.
The working principle and the beneficial effects of the technical scheme are as follows:
according to the method and the device, the improvement direction of the model to be improved is obtained, the target improvement record corresponding to the improvement direction is determined, meanwhile, the improvement strategy parameterization record corresponding to the target improvement record is introduced, the adaptive parameterization template corresponding to the improvement direction is formulated according to the target improvement strategy parameterization record, the first target improvement parameter is determined according to the adaptive parameterization template, the parameterization process of the improvement strategy is more suitable, and the improvement is more accurate.
In one embodiment, step 5: according to the first target improvement parameter, correspondingly improving the model to be improved, including:
determining a first parameter distance value according to the first target improvement parameter and the current parameter acquired in real time; wherein, the current parameters are: model parameters of the model to be improved in real time; the first parameter distance value is: a parameter range between the first target improvement parameter and the current parameter;
determining a second parameter distance value of a target parameter distance preset by the first parameter distance value; wherein the preset target parameter distance is preset manually; the second parameter distance value is: the parameter values of the target parameter distances around the first target improvement parameter;
determining a fluctuation improvement parameter range according to the second parameter distance value; wherein, the fluctuation improvement parameter range is: possible drop points for optimal improvement parameters;
according to the fluctuation improvement parameter range, simulating to improve the model to be improved, and obtaining a simulation improvement result; when the model to be improved is simulated according to the fluctuation improvement parameter range, a simulation improvement model is constructed, and improvement parameters of all fluctuation improvement parameter ranges are simulated; the simulation improvement results are: after simulating the improved parameters of the fluctuation improved parameter range, outputting results of the simulated dendrimer research model on the research requirements;
determining a second target improvement parameter of the target simulation improvement result according to the simulation improvement result; when a second target improvement parameter of the target simulation improvement result is determined according to the simulation improvement result, determining a difference between the simulation improvement result and a predicted result of a research requirement corresponding to the simulation improvement result, taking the simulation improvement result with the smallest difference as the target simulation improvement result, and taking a first target improvement parameter corresponding to the target simulation improvement result as the second target improvement parameter;
and correspondingly improving the model to be improved according to the second target improvement parameter.
The working principle and the beneficial effects of the technical scheme are as follows:
the improved parameters of the determined model are determined manually or through historical experience, in general, the directly predicted model improved parameters are not necessarily accurate, but the detection efficiency of each adjustable value of the improved parameters is lower, meanwhile, the optimal improved parameters are generally near the predicted model improved parameters, so that the fluctuation improved parameter range is determined according to the first target improved parameters, the current parameters and the target parameter distance, the model to be improved is simulated according to the fluctuation improved parameter range, the model to be improved is improved according to the simulated improved effect, the second target improved parameters for determining the target simulated improved effect are improved according to the simulated improved effect, the accuracy of determining the second target improved parameters is further improved, and the determination efficiency is higher.
In one embodiment, according to the second target improvement parameter, the model to be improved is improved correspondingly, including:
acquiring a second parameter type of a second target improvement parameter; wherein the second parameter type is: a parameter class of the second target improvement parameter;
constructing an empty parameter adjustment array according to the second parameter type and a preset parameter type-array element position library; the preset parameter type-array element position library is a database, and comprises a plurality of third parameter types and array element positions which are in one-to-one correspondence; the null parameter adjustment array is: marking a blank array where parameters of a parameter type need to be written at the array element position;
writing a second target improvement parameter of a second parameter type into the position of an array element of the null parameter adjustment array corresponding to the second parameter type to obtain a parameter adjustment array; wherein, the parameter adjustment array is: parameter adjustment vectors;
and according to the parameter adjustment array, performing parameter adjustment of the model to be improved.
The working principle and the beneficial effects of the technical scheme are as follows:
according to the method, the second parameter type and the parameter type-array element position library of the second target improvement parameter are introduced to construct the null parameter adjustment array, the second target improvement parameter of the second parameter type is written into the null parameter adjustment array at the position of the array element corresponding to the second parameter type to obtain the parameter adjustment array, the construction of the parameter adjustment array is more accurate, and further, parameter adjustment is more suitable according to the parameter adjustment array.
The embodiment of the invention provides an improved method of a dendrimer research model, which further comprises the following steps:
step 6: acquiring a first research conclusion of a research record and a second research conclusion of an improved model to be improved, judging repeated simulation requirements according to the first research conclusion and the second research conclusion, and if the judgment result of the repeated simulation requirements is that repeated simulation is required, performing corresponding repeated simulation; wherein, the first study conclusion is: conclusions in the study record corresponding to the study requirements; the second study was concluded as: the second modified study conclusion corresponds to the conclusion of the study requirement;
and performing repeated simulation demand judgment according to the first research conclusion and the second research conclusion, wherein the repeated simulation demand judgment comprises the following steps:
acquiring a first study item of a first study conclusion; wherein, the first study item is: first study conclusion corresponds to study requirements such as: the diffusion rule of the dendrimers in the particle swarm;
acquiring a second study item of a second study conclusion; wherein the second study is: the second study conclusion corresponds to the study requirement;
determining a degree of project similarity of the first study and the second study; the item similarity degree is, for example: 0.9;
if the item similarity is greater than or equal to a preset item similarity threshold, taking the corresponding first research item as a third research item, and taking a first research conclusion corresponding to the third research item as a third research conclusion; the preset project similarity threshold is preset manually;
determining conclusion deviations based on semantic analysis techniques from the second and third study conclusions; wherein conclusion bias refers to the degree of semantic difference between the second and third study conclusions;
if the conclusion deviation is greater than or equal to a preset conclusion deviation threshold, repeated simulation is needed, otherwise, the repeated simulation is not needed. The preset conclusion deviation threshold is preset manually.
The working principle and the beneficial effects of the technical scheme are as follows:
in general, tree analysis research models are improved, and some research conclusions with deviation often appear, but the influence degree of model deviation on the final conclusions is different, such as: the conclusion of the modified tree analysis research model has little difference from the original conclusion, and the method is as follows: the conclusion of the modified tree analysis research model is quite opposite to the original conclusion, therefore, according to the obtained first research conclusion and the second research conclusion of the model to be improved, according to the item similarity degree of the first research item and the second research item of the first research conclusion, a third research item with the item similarity degree greater than or equal to the item similarity degree threshold value and a third research conclusion corresponding to the third research item are determined, according to the semantic analysis technology, conclusion deviation of the second research conclusion and the third research conclusion is determined, when the conclusion deviation is greater than or equal to the conclusion deviation threshold value, repeated simulation is carried out, and triggering conditions of repeated simulation are more suitable.
In one embodiment, if the determination result of the repeated simulation requirement determination is that repeated simulation is required, performing corresponding repeated simulation includes:
if the judgment result of the repeated simulation demand judgment is that repeated simulation is needed, the corresponding third research project is used as a fourth research project;
acquiring a historical application node of a fourth research project, and simultaneously acquiring an allocable contact resource; wherein, history application node is: a communication node of a conclusion application party (such as a laboratory) of a fourth study conclusion corresponding to the fourth study item; the allocable contact resources are: communication resources that can be allocated;
judging whether the allocable contact resources can support and notify the historical application node according to the historical application node and the allocable contact resources, if so, carrying out concurrent notification; when judging whether the allocable contact resources can support and notify the historical application node, acquiring the required contact resources for supporting the concurrent notification historical application node, and if the required contact resources are smaller than or equal to the allocable contact resources, carrying out concurrent notification;
if the allocable contact resources cannot support and inform the historical application node, determining the receiving time of the historical application node for receiving a fourth research conclusion of the fourth research project; if the required contact resources are larger than the allocable contact resources, the allocable contact resources cannot support and notify the historical application node, receiving time is obtained, wherein the receiving time is the time of the historical application node to receive a fourth research conclusion of a fourth research project, and the longer the time distance between the receiving time and the current time is, the larger the influence possibly generated by the corresponding fourth research conclusion is, and when the allocable contact resources are insufficient, the contact should be preferentially carried out;
and according to the order of the receiving time from the early to the late, the allocable contact resources are sequentially scheduled for notification.
The working principle and the beneficial effects of the technical scheme are as follows:
according to the method, the historical application node of the fourth research project is introduced, meanwhile, the allocable contact resources are obtained, whether the allocable contact resources can be allocated or not is judged according to the historical application node and the allocable contact resources, concurrent notification is carried out when concurrent notification can be supported, and the historical application node is notified, otherwise, the historical application node is introduced to receive the receiving time of the fourth research conclusion of the fourth research project, and the allocable contact resources are sequentially scheduled to be notified according to the sequence from the early to the late of the receiving time, so that the rationality and timeliness of notification are improved.
The embodiment of the invention provides an improved system of a dendrimer research model, as shown in fig. 2, comprising:
the research record acquisition subsystem 1 is used for acquiring research records of a dendrimer research model;
the judging result acquisition subsystem 2 is used for carrying out improvement judgment on the dendrimer research model according to the research record to acquire the judging result of the improvement judgment;
the model to be improved determining subsystem 3 is used for taking the corresponding dendrimer research model as the model to be improved if the judging result is that improvement is needed;
an improvement parameter acquisition subsystem 4 for acquiring a first target improvement parameter of the model to be improved;
and the improvement subsystem 5 is used for correspondingly improving the model to be improved according to the first target improvement parameter.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (8)
1. An improved method of a dendrimer research model, comprising:
step 1: acquiring a research record of a dendrimer research model;
step 2: according to the research records, carrying out improvement judgment on the dendrimer research model, and obtaining a judgment result of the improvement judgment;
step 3: if the judgment result is that improvement is needed, the corresponding dendrimer research model is taken as a model to be improved;
step 4: acquiring a first target improvement parameter of a model to be improved;
step 5: according to the first target improvement parameter, correspondingly improving the model to be improved;
wherein, step 2: according to the research record, carrying out improvement judgment on the dendrimer research model to obtain a judgment result of the improvement judgment, wherein the method comprises the following steps:
acquiring improved judgment standard parameters;
obtaining the construction basis of a dendrimer research model;
determining model parameters according to the construction basis;
obtaining a comparison type of model parameters corresponding to improved decision criterion parameters, the comparison type comprising: direct and indirect controls;
when the comparison type is direct comparison, the corresponding model parameter is used as a first target parameter, improvement judgment is carried out according to the first target parameter and the improvement judgment standard parameter, and a first judgment sub-result is obtained; when the improvement judgment is carried out according to the first target parameter and the improvement judgment standard parameter, judging whether the first target parameter is in a range specified by the improvement judgment standard parameter, if so, judging that the first judgment result is that improvement is not needed, otherwise, judging that the first judgment result is needed;
when the comparison type is indirect comparison, the corresponding model parameter is used as a second target parameter;
determining a comparison parameter according to the second target parameter;
performing improvement judgment according to the comparison parameter and the improvement judgment standard parameter to obtain a second judgment sub-result; wherein, the improvement judgment is carried out according to the control parameter and the improvement judgment standard parameter: judging whether the comparison parameter is in the range specified by the improved judgment standard parameter, if so, judging that the second judgment result is that improvement is not needed, otherwise, judging that the second judgment result is that improvement is needed;
the first judging sub-result and the second judging sub-result are used as judging results together;
wherein obtaining the improved decision criterion parameter comprises:
acquiring historical experimental data;
training a theoretical data prediction model according to historical experimental data;
obtaining a simulation demand;
inputting the simulation demand into a theoretical parameter prediction model, obtaining predicted theoretical parameters, and taking the theoretical parameters as improved judgment standard parameters;
wherein, step 4: obtaining a first target improvement parameter of a model to be improved, comprising:
if the judgment result is that improvement is needed, analyzing the corresponding judgment result, and acquiring the improvement direction of the model to be improved; wherein, the improvement direction is: the type of parameters to be improved of the model to be improved;
acquiring a target improvement record according to the improvement direction; wherein, the target improvement record is: historical parameter adjustment records of the improvement direction;
acquiring an improvement strategy parameterization record corresponding to the target improvement record; wherein, the improvement policy parameterization record is: acquiring a process record of the parameterized improvement strategy according to the target improvement record;
determining an adaptive parameterized template corresponding to the improvement direction according to the target improvement strategy parameterized record; the adaptive parameterization template constraint only carries out adaptive parameterization of an improvement strategy in an improvement direction, and the adaptive parameterization is as follows: adaptively generating an improvement strategy parameter of a model to be improved;
the target improvement record is input into an adaptive parameterization template to obtain a first target improvement parameter.
2. The method for improving a dendrimer research model according to claim 1, wherein step 1: obtaining a study record of a dendrimer study model, comprising:
acquiring the current moment and simultaneously acquiring the target moment of a historical output record of the dendrimer research model;
acquiring time screening requirements;
and determining research records in the historical output records according to the time screening requirement, the current time and the target time.
3. The method of modifying a dendrimer study model of claim 1, wherein determining the control parameter based on the second target parameter comprises:
acquiring a plurality of conversion channels;
acquiring a first parameter type of a second target parameter;
inputting a second target parameter into a channel interface corresponding to the conversion channel according to the first parameter type;
and obtaining an output result correspondingly output by the conversion channel after the second target parameter is input into the channel interface, and taking the output result as a comparison parameter.
4. The method for improving a dendrimer research model according to claim 1, wherein step 5: according to the first target improvement parameter, correspondingly improving the model to be improved, including:
determining a first parameter distance value according to the first target improvement parameter and the current parameter acquired in real time; wherein, the first parameter distance value is: a parameter range between the first target improvement parameter and the current parameter;
determining second parameter distance values of target parameter distances preset at left and right sides of the first parameter distance value;
determining a fluctuation improvement parameter range according to the second parameter distance value; wherein, the second parameter distance value is: the parameter values of the target parameter distances around the first target improvement parameter;
according to the fluctuation improvement parameter range, simulating to improve the model to be improved, and obtaining a simulation improvement result;
determining a second target improvement parameter of the target simulation improvement result according to the simulation improvement result; when a second target improvement parameter of the target simulation improvement result is determined according to the simulation improvement result, determining a difference between the simulation improvement result and a predicted result of a research requirement corresponding to the simulation improvement result, taking the simulation improvement result with the smallest difference as the target simulation improvement result, and taking a first target improvement parameter corresponding to the target simulation improvement result as the second target improvement parameter;
and correspondingly improving the model to be improved according to the second target improvement parameter.
5. The method for modifying a dendrimer study model according to claim 4, wherein the modifying the model according to the second target modification parameter comprises:
acquiring a second parameter type of a second target improvement parameter;
constructing an empty parameter adjustment array according to the second parameter type and a preset parameter type-array element position library;
writing a second target improvement parameter of a second parameter type into the position of an array element of the null parameter adjustment array corresponding to the second parameter type to obtain a parameter adjustment array;
and according to the parameter adjustment array, performing parameter adjustment of the model to be improved.
6. The method of modifying a dendrimer study model of claim 1, further comprising:
step 6: acquiring a first research conclusion of a research record and a second research conclusion of an improved model to be improved, judging repeated simulation requirements according to the first research conclusion and the second research conclusion, and if the judgment result of the repeated simulation requirements is that repeated simulation is required, performing corresponding repeated simulation;
and performing repeated simulation demand judgment according to the first research conclusion and the second research conclusion, wherein the repeated simulation demand judgment comprises the following steps:
acquiring a first study item of a first study conclusion;
acquiring a second study item of a second study conclusion;
determining a degree of project similarity of the first study and the second study;
if the item similarity is greater than or equal to a preset item similarity threshold, taking the corresponding first research item as a third research item, and taking a first research conclusion corresponding to the third research item as a third research conclusion;
determining conclusion deviations based on semantic analysis techniques from the second and third study conclusions;
if the conclusion deviation is greater than or equal to a preset conclusion deviation threshold, repeated simulation is needed, otherwise, the repeated simulation is not needed.
7. The method for improving a dendrimer study model according to claim 6, wherein if the determination result of the repeated simulation demand determination is that repeated simulation is required, performing corresponding repeated simulation comprises:
if the judgment result of the repeated simulation demand judgment is that repeated simulation is needed, the corresponding third research project is used as a fourth research project;
acquiring a historical application node of a fourth research project, and simultaneously acquiring an allocable contact resource;
judging whether the allocable contact resources can support and notify the historical application node according to the historical application node and the allocable contact resources, if so, carrying out concurrent notification;
if the allocable contact resources cannot support and inform the historical application node, determining the receiving time of the historical application node for receiving a fourth research conclusion of the fourth research project;
and according to the order of the receiving time from the early to the late, the allocable contact resources are sequentially scheduled for notification.
8. An improved system for a dendrimer study model, comprising:
the research record acquisition subsystem is used for acquiring research records of the dendrimer research model;
the judgment result acquisition subsystem is used for carrying out improvement judgment on the dendrimer research model according to the research record to acquire a judgment result of improvement judgment;
the model to be improved determines a subsystem, and is used for taking a corresponding dendrimer research model as a model to be improved if the judgment result is that improvement is needed;
the improved parameter acquisition subsystem is used for acquiring a first target improved parameter of the model to be improved;
the improvement subsystem is used for correspondingly improving the model to be improved according to the first target improvement parameter;
wherein, the judging result acquisition subsystem executes the following operations:
acquiring improved judgment standard parameters;
obtaining the construction basis of a dendrimer research model;
determining model parameters according to the construction basis;
obtaining a comparison type of model parameters corresponding to improved decision criterion parameters, the comparison type comprising: direct and indirect controls;
when the comparison type is direct comparison, the corresponding model parameter is used as a first target parameter, improvement judgment is carried out according to the first target parameter and the improvement judgment standard parameter, and a first judgment sub-result is obtained; when the improvement judgment is carried out according to the first target parameter and the improvement judgment standard parameter, judging whether the first target parameter is in a range specified by the improvement judgment standard parameter, if so, judging that the first judgment result is that improvement is not needed, otherwise, judging that the first judgment result is needed;
when the comparison type is indirect comparison, the corresponding model parameter is used as a second target parameter;
determining a comparison parameter according to the second target parameter;
performing improvement judgment according to the comparison parameter and the improvement judgment standard parameter to obtain a second judgment sub-result; wherein, the improvement judgment is carried out according to the control parameter and the improvement judgment standard parameter: judging whether the comparison parameter is in the range specified by the improved judgment standard parameter, if so, judging that the second judgment result is that improvement is not needed, otherwise, judging that the second judgment result is that improvement is needed;
the first judging sub-result and the second judging sub-result are used as judging results together;
wherein obtaining the improved decision criterion parameter comprises:
acquiring historical experimental data;
training a theoretical data prediction model according to historical experimental data;
obtaining a simulation demand;
inputting the simulation demand into a theoretical parameter prediction model, obtaining predicted theoretical parameters, and taking the theoretical parameters as improved judgment standard parameters;
wherein the improved parameter acquisition subsystem performs the following operations:
if the judgment result is that improvement is needed, analyzing the corresponding judgment result, and acquiring the improvement direction of the model to be improved; wherein, the improvement direction is: the type of parameters to be improved of the model to be improved;
acquiring a target improvement record according to the improvement direction; wherein, the target improvement record is: historical parameter adjustment records of the improvement direction;
acquiring an improvement strategy parameterization record corresponding to the target improvement record; wherein, the improvement policy parameterization record is: acquiring a process record of the parameterized improvement strategy according to the target improvement record;
determining an adaptive parameterized template corresponding to the improvement direction according to the target improvement strategy parameterized record; the adaptive parameterization template constraint only carries out adaptive parameterization of an improvement strategy in an improvement direction, and the adaptive parameterization is as follows: adaptively generating an improvement strategy parameter of a model to be improved;
the target improvement record is input into an adaptive parameterization template to obtain a first target improvement parameter.
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