12 results about "Problem solver" patented technology

The invention belongs to an intelligent highway pavement structure based on a self-sensing asphalt material and a monitoring system of the intelligent highway pavement structure, and discloses the intelligent highway pavement structure based on the self-sensing asphalt material and the monitoring system of the intelligent highway pavement structure. A pavement structural surface layer is made of a self-sensing asphalt mixture containing an amorphous silicon-based composite functional phase, the functional phase is prepared through a specific process, a nano bowl-shaped array is arranged on the surface of the functional phase, tungsten carbide nano crystal nucleuses are coated on the surface of the functional phase, and the functional phase and asphaltene form a non-equilibrium electron cloud overlapping system. The monitoring system is based on a non-contact microwave resonant cavity coupling principle, analyzes reflected signals, extracts characteristic vectors, and inverts real-time stress, strain, damage factors and temperature state parameters in combination with an inverse problem solver. A traditional sensor pre-embedding mode is abandoned, the pavement body and the sensing function are fused, the problems of implantation damage, life mismatching, low spatial resolution and the like are solved, and a new normal form is provided for intelligent road safety early warning and full-life management.

A spiking neural network (SNN) system is disclosed having spiking neurons associated with clause values associated with a satisfiability (SAT) problem. Each spiking neuron generates a voltage spike when on input voltage applied to each spiking neuron is increased above a spiking voltage threshold. The input voltage that is increased above the spiking voltage threshold is indicative that the corresponding clause value is satisfied. A controller applies the clause grid that includes clause values to a literal grid that includes literal values. The controller generates the input voltage that is applied to each spiking neuron based on each corresponding clause value associated with each spiking neuron that is applied to the literal values. The controller determines that each clause value is satisfied when the corresponding spiking neuron generates the voltage spike and that each clause value is unsatisfied when the corresponding spiking neuron fails to generate the voltage spike.

The invention provides a test method and system for a mathematical character question solver, and the system comprises a data preprocessing module which is used for integrating a multi-source mathematical character question data set, carrying out the standardized processing and marking of questions in the mathematical character question data set, and outputting a data instance with a unified data structure; the solver module is used for decomposing a solving algorithm into different basic function components as algorithm components, calling related algorithm components to form a corresponding solver according to a logic sequence of a to-be-tested solving algorithm, and solving a mathematical problem by using the solver based on an input data instance to generate a solving answer; and the perspective confusion comparison module is used for receiving the solving answer and comprehensively evaluating a solver corresponding to the algorithm to be measured through three dimensions of question type classification, key question solving steps and an algorithm component. According to the invention, multi-source data sets can be integrated, automatic and reproducible test workflows are provided, and fine-grained and multi-dimensional performance tests are supported.

The invention discloses a privacy protection elastic distributed solver design method and system for resisting mixed attacks in resource allocation and a storage medium, and the method comprises the steps: designing a solver in combination with steganography based on a classical distributed optimization framework for a mixed attack scene in which Byzantine attacks and eavesdropping attacks exist at the same time, and designing a privacy protection elastic distributed solver in combination with steganography; the privacy protection effect can be achieved while the Byzantine attack is resisted. Compared with a traditional resource allocation problem solver, the method has the capacity of processing hybrid attacks, and convergence errors of the algorithm are reduced. According to the method, two types of attacks can be confronted at the same time, malicious node interference is effectively inhibited through robust screening and an elastic updating mechanism, so that the system still keeps stable convergence with relatively low error in a mixed attack environment, privacy embedding with low calculation overhead is realized by introducing steganography and Hadamard transformation, and the method does not depend on heavy encryption or an MPC protocol, so that the method is simple and convenient to operate. And the real-time requirement of an intelligent power grid is met.

A method of resource management for transferring resources from providers to consumers is described. The method comprises the following steps. Supply parameters for the providers and demand parameters for the consumers are established, and constraints on the allocation of the resources are also established, as is an optimisation function for determining matches between providers and consumers. The optimisation function is solved for the established constraints using a constraint-based problem solver to determine matches between providers and consumers. Resources are then transferred from providers to consumers according to the determined matches. A computing system adapted to perform this method is also described, along with a power distribution system including such a computing system.

The invention relates to an artificial intelligence teaching system for guided learning and an application thereof, the artificial intelligence teaching system can provide an integrated intelligent collaborative learning platform taking cases as a center, and the system can create a complete clinical situation for learners, so that the learners can learn more clearly. A direct relation between morphological characteristics and disease diagnosis is helped to be established, so that the clinical comprehensive thinking ability is cultivated; and meanwhile, the learner is changed from a passive observer to an active and cooperative problem solver. Moreover, in order to solve the problem of lack of real-time professional guidance in collaborative learning, the system innovatively introduces an AI intelligent guidance module, so that interactive behaviors of learning groups are analyzed in real time, prompts, problems and feedbacks highly related to situations are provided, students are actively guided to focus on key features, potential error cognition is corrected, and learning efficiency is improved. And an immersive and efficient school effect of simulating expert guidance aside is achieved.

A computer-implemented method of interpreting a solution 12 of declarative problem codes 10, 11 is presented. The solution 12 and the natural language problem 20 with respect to the latter are provided to a machine learning system 2 that determines an auxiliary constraint 21 opposite to the premise of the problem 20. A declarative problem solver 1 identifies conflicts between these auxiliary constraints 21 and constraints of declarative problem codes 10, 11. The machine learning system 2 then determines an interpretation 31 based on conflict constraints of the declarative problem codes 10, 11.

A spiking neural network (SNN) system is disclosed having spiking neurons associated with clause values associated with a satisfiability (SAT) problem. Each spiking neuron generates a voltage spike when on input voltage applied to each spiking neuron is increased above a spiking voltage threshold. The input voltage that is increased above the spiking voltage threshold is indicative that the corresponding clause value is satisfied. A controller applies the clause grid that includes clause values to a literal grid that includes literal values. The controller generates the input voltage that is applied to each spiking neuron based on each corresponding clause value associated with each spiking neuron that is applied to the literal values. The controller determines that each clause value is satisfied when the corresponding spiking neuron generates the voltage spike and that each clause value is unsatisfied when the corresponding spiking neuron fails to generate the voltage spike.

A computer-implemented procedure for explaining a solution 12 to a declarative problem coding 10, 11 is presented. The solution 12 and a natural language question 20 related to it are provided to a machine learning system 2, which determines additional constraints 21 that contradict the premise of the question 20. The declarative problem solver 1 identifies conflicts between these auxiliary constraints 21 and the constraints of the declarative problem coding 10, 11. The machine learning system 2 then determines an explanation 31 based on the conflicting constraints of the declarative problem coding 10, 11.

This application provides a test question generation method, apparatus, electronic device, and storage medium. The method includes: parsing test question data to generate a conditional reasoning dependency graph representing the problem-solving logic chain, and extracting topological semantic fingerprints to construct a fingerprint database; generating a test question blueprint that meets the discrimination conditions through adversarial game between the generator and a discriminator simulating the cognitive state of the problem solver; calculating the cognitive entropy of the test question blueprint, and generating the target test question after completing threshold verification. This application can improve the quality of generated test questions.

A computer-implemented method of explaining a solution of a declarative problem encoding. The solution and a natural language question about the latter are provided to a machine learning system, which determines auxiliary constraints 21 opposing the questions premise. The declarative problem solver identifies conflicts between these auxiliary constraints and the constraints of the declarative problem encoding. The machine learning system then determines an explanation based on the conflicting constraints of the declarative problem encoding.

The present application relates to the technical field of chip, especially relates to a random constraint problem solver core determination method, electronic equipment and medium, through constructing a solver core determination model with input of network attribute vector, node attribute vector and adjacent network matrix and output of each solver core weight, inputting the input data in the form of network attribute vector, node attribute vector and adjacent network matrix corresponding to the to-be-solved random constraint problem into the solver core determination model, the solver core corresponding to the to-be-solved random constraint problem can be determined, so that all inputted random constraint problems can be matched to the optimal solver core. The present application improves the solving efficiency and accuracy of random constraint problems.