170results about "Genetic models" patented technology

The present disclosure is related to framework for automatically and efficiently finding machine learning (ML) architectures that are optimized to one or more specified performance metrics and / or hardware platforms. This framework provides ML architectures that are applicable to specified ML domains and are optimized for specified hardware platforms in significantly less time than could be done manually and in less time than existing ML model searching techniques. Furthermore, a user interface is provided that allows a user to search for different ML architectures based on modified search parameters, such as different hardware platform aspects and / or performance metrics. Other embodiments may be described and / or claimed.

The invention belongs to the technical field of aero-engine performance testing, particularly relates to a physical constraint-based aero-engine state prediction model construction method and system, and aims to solve the problems of high calculation complexity and poor data quality of an existing physical information model. The method comprises the following steps: acquiring historical operation data of the aero-engine and a physical constraint rule set of engineering simplification; predicting performance parameters by adopting a deep learning model; constructing a total loss function formed by weighting a data loss item and a physical loss item to train the model; wherein the physical loss item is generated based on the deviation degree of the predicted performance parameter and the engineering simplified physical constraint rule set, and is used for replacing the complex partial differential equation constraint. According to the method, the engineering simplified physical rule is introduced, so that the calculation overhead of model training is remarkably reduced, the model is effectively guided to learn the characteristics conforming to the physical rule, and the accuracy and generalization ability of the prediction model are remarkably improved under the condition of limited data.

The invention discloses an integrated circuit fault supervision method and system for dynamic time slot allocation, and the method comprises the steps: collecting and preprocessing multi-source time slot data, and generating a standardized data set; based on the standardized data set, genetic programming is used for generating a mathematical formula for describing the relation between time slot allocation and fault detection; clustering the standardized data set by using fuzzy C-means clustering, and identifying a data state category; dynamically adjusting a time slot allocation strategy in combination with a mathematical formula and a clustering result, and generating a repair result; if abnormity is detected, an adjustment formula is quickly generated based on a mathematical formula and a clustering category, and repair is executed; and feeding back the distribution and repair result, and adaptively updating the mathematical formula and the clustering result. According to the invention, efficient adaptive optimization of dynamic time slot allocation and intelligent fault supervision in an integrated circuit system is realized.

One embodiment of the invention discloses a method and device for optimizing network anti-virus indexes. The method comprises following steps: obtaining anti-virus indexes of terminals in a network, wherein the anti-virus index of each terminal in the network comprises at least one kind of information as follows: virus infection and anti-virus capability information; optimizing the anti-virus indexes of terminals in a network by means of the genetic algorithm to obtain the optimized anti-virus indexes of terminals in the network; obtaining the optimized network anti-virus indexes based on the optimized anti-virus indexes of terminals in the network. One embodiment of the invention also discloses a device for optimizing network anti-virus indexes.

The invention relates to the technical field of education science and technology, and discloses a self-adaptive early education training system based on cloud computing, which comprises a data acquisition module, a cloud platform data processing module, a self-adaptive analysis module, a training execution module, a feedback evaluation module and a cross-platform data synchronization interface. The multi-dimensional behavior data and the physiological indexes are fused through a transfer learning algorithm, a dynamically updated individual ability portrait is constructed, the limitation of traditional age grouping is broken through, the matching precision of a teaching scheme and the actual development stage of children is improved, and through a curriculum matching engine based on a reinforcement learning framework, the learning efficiency is improved. Teaching strategies can be dynamically adjusted according to real-time feedback, accurate adaptation of teaching content and learning progress is achieved, and the occurrence probability of advanced learning and lagged learning is reduced.

We provide the system. [Solution] A means for storing and performing initial processing on communication information obtained from a data acquisition device, A detection means for analyzing the communication information and detecting anomalies, A means for generating and presenting a warning based on the detected anomaly, A self-learning method that improves the accuracy of analysis and detection using machine learning models, A means for visualizing the aforementioned communication information and warnings and for creating a report, A means of notifying mobile terminals when an anomaly is detected in the communication network, A system that includes this.

The system according to this embodiment aims to force users to perform muscle training by controlling the operation of home appliances. [Solution] The system according to the embodiment comprises a generating AI agent, a sensor, and a control unit. The generating AI agent is incorporated into home appliances and electrical products. The sensor counts the number of muscle training repetitions. The control unit controls the operation of the home appliance based on the number of muscle training repetitions counted by the sensor.

We provide the system. [Solution] Means for collecting and analyzing multilingual information, A means of designing a new standard representation using a generative algorithm, means for converting the multilingual information into the standardized expression and compressing it, A means for optimizing the predictive model using the transformed information, A means of performing bidirectional communication with the user using a predicted model, A means of presenting information translated in real time, A system that includes this.

The system according to this embodiment aims to automatically generate and provide optimal training programs tailored to the skill levels and goals of employees. [Solution] The system according to the embodiment comprises an analysis unit, a generation unit, and a monitoring unit. The analysis unit analyzes employees' historical data, current skill levels, and individual goals. The generation unit automatically generates and provides an optimal training program based on the analysis results obtained by the analysis unit. The monitoring unit monitors training progress in real time based on the training program generated by the generation unit and provides feedback and support.

Provided is a technique relating to codon optimization. A method for optimizing a nucleic acid sequence for expression of a protein in a host comprises: obtaining a protein subsequence-nucleic acid subsequence pair according to collected highly expressed protein sequences and encoding nucleic acid sequences thereof, so as to form a training set; using the training set to train a neural machine translation model, wherein the neural machine translation model is used to realize translation from an amino acid sequence to a codon sequence; cleaving the protein sequence requiring codon optimization into protein subsequences; using the trained neural machine translation model to translate the protein subsequences from amino acid sequences to codon sequences; and overlapping the translated subsequences, so as to combine same into a full-length codon sequence, wherein during overlapping to synthesize the codon sequence, the synonymous codon with the highest occurrence frequency or number is selected as the optimal codon for the position according to the frequency or the number of the synonymous codon corresponding to each amino acid position of the protein sequence.

The application discloses a layout planning method based on reinforcement learning and a genetic algorithm, and comprises the following steps: 1, generating an original population of the genetic algorithm through perturbation B*‑tree; 2, calculating the fitness of all individuals, and selecting an individual with the highest fitness value as the optimal individual in the population; 3, according to the probability, selecting whether to use a crossover operator in an iteration, if the crossover operator is selected, selecting two parent individuals from the population, and generating offspring individuals through the crossover; 4, according to the probability, selecting whether to use a mutation operator in the iteration, if the mutation operator is selected, selecting a parent individual from the population, and generating an offspring individual through the mutation; 5, optimizing the offspring individual by using a reinforcement learning intelligent agent, and then determining whether to replace the parent individual according to the fitness of the offspring individual; and 6, the iteration is ended, and the optimal individual is obtained. The application efficiently reduces the area and line length of layout planning.

The present invention relates to a distribution network multidimensional measurement configuration method and system for improving risk perception capabilities, which includes: analyzing data requirements for the types of disasters faced by the distribution network in the region; selecting distribution network multidimensional measurement equipment based on the analysis results of the data requirements and taking into account the micro-meteorological factors in the region; considering the real-time data transmitted by the multidimensional measurement equipment configured in the distribution network, comparing the line failure probability results obtained based on the distribution network disaster mechanism model with the actual line failure probability, and adopting a distribution network risk perception accuracy improvement method; improving the distribution network risk perception capability, ensuring that the measurement equipment configuration has good economic efficiency as the goal, and taking into account the observability of important load nodes, using a genetic algorithm to solve the number and location of the multidimensional measurement configuration in the distribution network. The present invention achieves the improvement of the distribution network disaster loss identification capability in the event of failure of the electrical measurement device, and can be widely used in the field of electrical automation.

The invention discloses an electric power emergency communication network resource allocation method and system based on a genetic algorithm. The method comprises the following steps: acquiring a plurality of users and a plurality of subcarriers currently coexisting in an electric power emergency communication network; according to the plurality of users and the plurality of subcarriers, combining a preset resource allocation model, solving the resource allocation model by using a genetic algorithm, and determining a resource allocation scheme of the power emergency communication network; wherein the resource allocation model is provided with a dual-objective function and a constraint condition set of resource allocation; the dual-objective function is a resource allocation optimization function established by taking power emergency communication network capacity maximization and energy efficiency maximization as optimization objectives; the constraint condition set comprises a service quality constraint condition and a network resource limit constraint condition; and carrying out resource allocation on the power emergency communication network according to the resource allocation scheme. According to the invention, reasonable scheduling and dynamic allocation of resources in the power emergency communication network can be realized.

We provide the system. [Solution] A means of receiving tasks entered by users, A means for analyzing the aforementioned problem and extracting requirements, A means for selecting the optimal combination from multiple artificial intelligence systems based on the aforementioned requirements, A means of integrating selected artificial intelligence systems to present solutions to users, A means of providing the aforementioned solution as information related to urban planning, A system that includes this.

We provide the system. [Solution] A means for receiving and integrating learner evaluation data, aptitude data, and survey data, A means of analyzing integrated data to identify learner characteristics, A means of suggesting career path options based on the characteristics of learners, A means of generating a study plan tailored to the desired career path, A method for automatically generating interview materials and question lists for educators, Means of notifying parents of career guidance, A system that includes this.

The invention relates to the technical field of black cattle breeding, and discloses a snowflake black cattle intelligent breeding method and system based on an animal model, and the method comprises the steps: collecting pedigree structure data and standardized phenotype data; calculating an additive genetic relationship matrix among snowflake black cattle individuals; establishing a quantitative genetics animal model, and outputting an individual additive genetic effect estimated value and calculating a predicted breeding value through the quantitative genetics animal model under the constraint of the additive genetic relationship matrix; extracting actual phenotype performance data in a subsequent time period; respectively carrying out individual descending sorting and sorting quantile division on the predicted breeding value and the actual phenotype performance data, and extracting a stability index of a target breeding quantile interval; and updating a fixed effect design matrix and variance component parameters of the quantitative genetics animal model, and re-outputting a predicted breeding value and a corresponding snowflake black cattle breeding decision. The stability and reliability of snowflake black cattle breeding are improved.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a neural network system to perform multiple machine learning tasks.

A supportive software-based “toolbox” for optimizing finite state machine (FSM)-modeled systems. The optimization may include defining a plurality of alternative models for the FSM-modeled system and iterating one or more of the domain alternative into iterated alternatives. The optimization may include generating a plurality of stateflow representations for the FSM-modeled system according to the iterated alternatives, and based thereon, generating a model score for each of the stateflow representations predictively ranking the stateflow representations based at least in part on one or more of user experience, usability, correctness, transformability, effectiveness, and readiness.

Disclosed herein are system, apparatus, article of manufacture, method and / or computer program product aspects, and / or combinations and sub-combinations thereof, for generating a workflow plan for completing a process. An example embodiment operates by receiving a user request from a user device in which the user request includes a natural language description of the workflow plan. The embodiment then retrieves, from a knowledge database, workflow information associated with a step of the workflow plan. The embodiment then generates a plurality of steps associated with the workflow plan. The embodiment then retrieves plan information from a storage database in which the plan information includes a sample workflow plan generated from a sample user request and the workflow information in which the workflow information is further associated with a step of the sample workflow plan. The embodiment then generates the workflow plan using a large language model (LLM) and a prompt.

Provided is a determination method that includes obtaining measurement data, selecting one or more second wavelengths from a plurality of first wavelengths including at least one of a plurality of measurement wavelengths to generate a plurality of individuals, by using a genetic algorithm, inputting, to a first model learned to reproduce a correct answer label of a target object, the measurement data of the target object belonging to a remaining group and a second spectroscopic spectrum determined by the second wavelength to discriminate a label of the target object belonging to the remaining group, for each of the plurality of individuals, and determining whether or not to use the second wavelength as the wavelength of the spectroscopic spectrum for discrimination based on a rate at which the label is correctly discriminated.

The system according to this embodiment aims to understand the user's emotions and personalize the conversation based on those emotions. [Solution] The system according to this embodiment comprises an emotion recognition unit, a dialogue management unit, and a personalization unit. The emotion recognition unit understands the user's emotions. The dialogue management unit performs advanced dialogue management based on the emotions understood by the emotion recognition unit. The personalization unit personalizes the interaction with the user based on the dialogue conducted by the dialogue management unit.

We provide the system. [Solution] A user input / output means that receives user input and initiates dialogue, A dialogue control means that analyzes the user's input and identifies related knowledge based on the generated information, A knowledge-providing means that provides the user with the identified knowledge and supports their understanding of the generated AI, A learning support means that improves the performance of a machine learning model using information collected through the aforementioned interaction with the user, Information processing means that personalize information based on the user's history and interests, A system that includes this.

The invention relates to the technical field of nuclear power cables, solves the technical problems that the prior art is easy to fall into local optimum, lacks a variation mechanism and is difficult to jump out of local optimum, and particularly relates to a nuclear power cable and a multi-mode real-time detection method for surface defects of the nuclear power cable. The method comprises the following steps: S1, acquiring multi-modal data of the surface of a cable through a multi-modal sensor, and performing joint filtering on the multi-modal data to obtain an anisotropic joint filtering value; according to the method, an independent SNR estimation module can be carried out by fusing the weight value and the weighted feature aggregation value to improve the weight reasonability, an experiment shows that the suppression effect on the low-illumination infrared noise is greatly improved, the complexity of each sub-step is not high, and the method can be applied to the field of low-illumination infrared noise suppression. And when the resolution of the image is 4K, the delay of the whole assembly line is extremely short, and the real-time requirement is met.

Disclosed herein are system, apparatus, article of manufacture, method and / or computer program product aspects, and / or combinations and sub-combinations thereof, for multi-agent network and security operations. An example embodiment operates by determining a complexity level of the task is high based on identifying a requirement of a collaboration between a plurality of decentralized agents when executing the task. The embodiment then determines a distributable level of the task is low based on identifying a requirement of a central agent for task allocation when executing the task. The embodiment then, in response to determining the complexity level of the task being high and the distributable level of the task being low, selects a hybrid architecture as the optimal architecture associated with the task. The embodiment then assigns the task to an agent associated with the hybrid architecture. The embodiment then executes the task using the hybrid architecture.

Provide a system. 【Solution means】 Means for collecting past maintenance data, Means for analyzing the collected data and generating a training scenario, Visual technology means for visualizing the generated training scenario, Means for providing the visualized training to the user, Means for recording and analyzing the user's training activities, Means for providing guidance information to the user based on the analysis results, Means for providing the user with the procedures for robot maintenance and troubleshooting through visual technology, A system including the above.

The application provides a kind of methane emission source intensity estimation method and system, device, storage medium under the support of multi-source data, belong to the technical field of environmental monitoring, including based on unmanned vehicle observation obtains target evaluation methane emission point source background meteorological data;Based on differential absorption laser radar obtains target evaluation methane emission point source methane concentration data;According to the background meteorological data and the methane concentration data of the target evaluation methane emission point source obtained, a methane Gauss diffusion model is constructed;According to the methane Gauss diffusion model constructed, the methane emission source intensity estimation result is obtained by solving.The application cooperates the monitoring result of unmanned vehicle measurement and differential absorption laser radar measurement to model the methane emission source of target area based on the modeling result and solve, so as to more accurately estimate the methane emission source intensity, high accuracy, long-term sustainability monitoring.

The system according to this embodiment aims to enable senior citizens to effectively utilize digital devices and reduce the workload of local governments. [Solution] The system according to the embodiment comprises a learning support unit, a family collaboration unit, a gamification unit, and a data analysis unit. The learning support unit provides customized guides and tutorials based on the user's learning pace and level of understanding. The family collaboration unit allows family members to check and support the user's learning progress. The gamification unit provides gamification to make learning fun and sustainable. The data analysis unit analyzes the user's learning data and provides an individually optimized learning plan.

The system according to this embodiment aims to learn operation data and identify and optimize efficient workflows. [Solution] The system according to the embodiment comprises a collection unit, a learning unit, a reinforcement learning unit, and a provision unit. The collection unit collects operation data. The learning unit learns the operation data collected by the collection unit and identifies an efficient flow. The reinforcement learning unit performs reinforcement learning based on the efficient flow identified by the learning unit and finds the optimal flow. The provision unit provides the flow optimized by the reinforcement learning unit.

Methods, systems, and apparatuses, including computer programs, for performing incremental secondary analysis of nucleic acid sequence reads. The method can include (i) obtaining first data describing a plurality of first reads generated by a nucleic acid sequencing device during a first read interval, (ii) obtaining second data describing a plurality of second reads generated by the nucleic acid sequencing device during a second read interval that is performed after the first read interval, wherein while the second data is being obtained: (a) providing, by the nucleic acid sequencing device, the first data as an input to a mapping and alignment unit, (b) receiving, from the mapping and alignment unit, alignment results, and (c) storing the received alignment results, and, thereafter (iii) instructing the mapping and alignment unit to begin alignment of the second data representing the second plurality of reads to the reference sequence.