45 results about "Combinatorial algorithms" patented technology

An apparatus for implementing a game having a deterministic component and a non-deterministic component wherein a player uses the game through at least one player interface unit. Each player interface unit generates a player record indicating player-initiated events. A random number generator provides a series of pseudo-random numbers and a rules library stores indexed rules for one or more games. An interface registry stores mapping records where the mapping records are used to associate the player-initiated events to pre-selected rules in the rules library. A control means is coupled to the player interface to receive the output of the player interface unit, coupled to the interface registry, the rules library, and the random number generator. The control means processes the player record and returns an output record to the player interface unit where the output record is determined by executing the game's rules with reference to the pseudo-random numbers and predefined combinatorial algorithms for selecting sets of the pseudo-random numbers.

Expanding a regular expression set into an expanded expression set that recognizes a same language as the regular expression set and includes more expressions than the regular expression set, with less operators per expression includes: logically connecting the expressions in the regular expression set; parsing the expanded expression set; transforming the parsed expanded expression set into a Glushkov automata; transforming the Glushkov automata into a modified deterministic finite automaton in order to maintain fundamental graph properties; combining the modified DFA into a keyword graph using a combining algorithm that preserves the fundamental graph properties; and computing an Aho-Corasick fail function for the keyword graph using a modified algorithm to produce a modified Aho-Corasick graph with a goto and a fail function and added information per state.

A fast combinatorial algorithm can significantly reduce the computational burden when solving general equality and inequality constrained least squares problems with large numbers of observation vectors. The combinatorial algorithm provides a mathematically rigorous solution and operates at great speed by reorganizing the calculations to take advantage of the combinatorial nature of the problems to be solved. The combinatorial algorithm exploits the structure that exists in large-scale problems in order to minimize the number of arithmetic operations required to obtain a solution.

The invention provides a simple and reliable inertia/GPS (global positioning system)/milemeter combined algorithm for solving the precision positioning problem of vehicles in complex environments, such as bridges, trees, tunnel barriers, urban canyons and the like. The method comprises the following steps of: respectively independently calculating position information of a carrier through an inertia/GPS combined navigation algorithm and a milemeter dead reckoning algorithm, further fusing the position information obtained by calculation through the two different algorithms through an output correction filter with simple design, and finally giving out high-precision vehicle position information. Compared with a traditional single-filter deep combined algorithm, the method has the advantages of stronger environmental adaptability, no sensitivity to error models of GPS, inertial navigation and a milemeter, high reliability, high output precision, easiness in implementation and the like, and can well solve the precision positioning problem of the vehicles in the complex environments.

The invention relates to a map optimization method and system for a mobile robot SLAM. The method comprises the steps: acquiring the environment information collected by a mobile robot, wherein the environment information is obtained by scanning in an environment of a to-be-constructed map by the mobile robot; obtaining a plurality of indexes representing the quality of the environment grid map, wherein the plurality of indexes comprise a grid occupancy rate, an angular point number and a closed area number; taking the plurality of indexes as targets, and performing multi-target iterative optimization according to the environment information and the ranges of the plurality of parameters to be optimized in the SLAM algorithm to obtain an optimal parameter combination in the SLAM algorithm,wherein the SLAM algorithm is used for generating an environment grid map according to the environment information; generating an optimal environment grid map by adopting an SLAM algorithm of the optimal parameter combination according to the environment information, wherein the optimal environment grid map is used for navigation and positioning of the mobile robot. According to the invention, themap construction efficiency and the map quality of the SLAM can be improved.

The invention discloses a transparent floor tile screen with full transparency and force perception. The transparent floor tile screen comprises an electromechanical structure and a software module, the electromechanical structure comprises a transparent liquid crystal screen, a pressure sensing array, a transparent plastic layer, a metal support, a communication module, a pick array and a microcomputer. And the software module comprises a screen combination algorithm and a pressure analysis algorithm. By implementing the above content, the transparent floor tile screen based on the transparent liquid crystal screen and the pressure sensing array is realized, the floor tile screen can directly see the under-foot scenery from the upper part of the high altitude, the under-foot real sceneryand the stimulated virtual effect are combined, and the effect of augmented reality is achieved.

The invention provides a satellite and inertia combined dynamic-to-dynamic real-time precise relative positioning method. The method comprises the following steps of: acquiring a relative positioningvector between a mobile station and a dynamic reference based on a carrier phase real-time dynamic differential relative positioning method; acquiring a mobile station position increment, a dynamic reference position increment and a position increment of the mobile station within a measurement updating time interval delta tTC based on a carrier phase GNSS/inertial navigation tight combination algorithm; and acquiring the dynamic reference position increment within a forecast time delta tp based on a polynomial forecast method of a sliding window; and finally synthesizing and outputting a relative positioning result. The method can overcome the influence caused by the position increment and GNSS original observation data broadcast delay, and can provide a precise relative positioning resultwith an extremely high update rate through a low data broadcast rate and a sampling rate.

The invention discloses a distribution transformer heavy overload prediction method and system based on a Prophet-LSTM combinatorial algorithm. The method comprises the steps of obtaining and preprocessing historical load data of a distribution transformer; determining influence factors having correlation with the heavy and overload load values of the distribution transformer as characteristic factors for prediction of the distribution transformer; decomposing the load data of the distribution transformer into a trend component, a periodic component and a data mutation item component; and respectively establishing a corresponding prediction model for each component for prediction, and integrating predicted values of each component to obtain a predicted value of the load data of the distribution transformer. The invention provides a new algorithm of the distribution transformer load data cleaning and processing method, the periodicity, the missing property and the continuity of the data are considered, the data can be restored to the maximum extent, and the preprocessing precision of the data is improved.

The invention discloses a path optimization method based on a dynamic window and redundant node filtering, which comprises the following steps of determining coordinate information of a starting position and a target position of motion by utilizing an existing grid map data set, and marking a target node and an obstacle node in a grid map; planning a global path by using an A * algorithm; performing global optimization by using a global path planned by an A * algorithm, and filtering redundant nodes; and performing segmented local optimization on the optimized global path in combination with a dynamic window method to obtain a final global path. According to the invention, the combinatorial algorithm is used to reduce the single motion duration of the mobile robot and improve the smoothness of the motion path curve; and meanwhile, the problem of the robot in a static driving route process is solved, and a flexible obstacle avoidance function can be realized in a planned route section.

The invention provides a method for economically optimizing a design scheme of an electrical collection system of a large-scale offshore wind farm, which is characterized by comprising the following steps: 1) selecting the large-scale offshore wind farm, and carrying out fan string division on the wind farm in a power transformation area by adopting a regional radiation fuzzy clustering algorithm; and 2) searching an optimal cable topology link path for the fan after each partition and string division, wherein the step can be completed by using a graph theory and a minimum spanning tree Primer shortest path optimization algorithm; 3) calculating the total cost of the optimal collection topology under all the sub-methods according to the sub-regions and the types of the fan strings, seeking the optimal cost, and ending the algorithm. The combinatorial algorithm solves the problem of curse of dimensionality of a topological structure optimized by an exhaustion method, and provides support for simply and quickly solving the problem of economical efficiency optimization of a large offshore wind power plant collection system. And finally, example analysis of the combinatorial optimization algorithm is performed on a wind power plant example in northern peninsula of Shandong, and the effectiveness of the combinatorial optimization algorithm is proved.

The invention discloses a power equipment defect text feature classification method based on a combinatorial algorithm. The method comprises the following steps: establishing a dictionary and a stop word table according to defect description of power equipment; performing Jieba word segmentation on the defect text; representing the text subjected to word segmentation in a distributed manner according to a word vector representation method; carrying out weight distribution according to an Attention mechanism, carrying out further extraction of features according to a CNN algorithm, and then carrying out feature weight distribution according to the Attention mechanism to obtain Attention-CNN extraction features; extracting text features according to an RNN algorithm to obtain RNN extraction features; and fusing and inputting the two extracted features into an SVM classifier to obtain the division of the defect features of the power equipment. According to the method, the text features are subjected to weight distribution, the two extracted features are fused, comprehensive extraction of the text features and distribution of feature weights are achieved, and therefore the accuracy of power equipment defect text classification is effectively improved.

The invention relates to the field of artificial intelligence, in particular to an electric power professional lexicon construction method based on a hybrid model and a clustering algorithm. The method includes preprocessing the power text and the parallel corpus; performing word segmentation through a word segmentation model, performing word combination on a Jieba word segmentation result through a mutual information and left and right entropy algorithm and a TextRank algorithm, wherein text keywords are extracted from the Jieba word segmentation result through a TF-IDF algorithm and a Word2Vec word clustering algorithm, and text word segmentation is directly carried out through an information entropy word segmentation algorithm; summarizing the results, and comparing to obtain feature corpus words; selecting power professional words from the feature corpus words as seed words; meanwhile, using the exported power text lexicon as candidate words to perform word segmentation on the power text, and then using a word2vec algorithm to convert the words into word vectors; obtaining similar words through clustering, and then obtaining a power professional word library through rule filtering. According to the invention, most professional words in the non-power field can be filtered by using one clustering model, and the professional words are relatively complete.

The invention provides a rendering image super-resolution texture enhancement method and device, equipment and a storage medium. The method comprises the steps: generating a rendering effect picture of a first resolution of a target scene; generating a non-illumination texture graph of a second resolution, a non-illumination normal graph with concave-convex textures of the second resolution and a rendering effect graph of the second resolution of the target scene, wherein the second resolution is greater than the first resolution; synthesizing the non-illumination texture graph of the second resolution and the non-illumination normal graph with the concave-convex texture of the second resolution into a composite graph according to a preset data combination algorithm; and reconstructing the rendering effect picture of the first resolution of the target scene into a rendering effect picture of a second resolution according to a super-resolution reconstruction algorithm and the composite picture. According to the invention, it is ensured that the low-resolution image is rendered into the high-resolution image, and meanwhile, the rendering time consumption and the calculation amount are reduced.

The invention discloses an informatization management system for construction projects of protection areas along a subway. The informatization management system comprises a navigation positioning terminal, a monitoring platform and a mobile terminal APP, wherein the navigation positioning terminal is interconnected with the monitoring platform through a data transmission technology and is used for transmitting current position information of inspectors along a subway to the monitoring platform in real time; the monitoring platform is interconnected with the mobile terminal APP through an HTTP (Hyper Text Transport Protocol), and is used for receiving the current position information, sent by the navigation positioning terminal, of the inspector along the subway in real time, displaying the current position information on a Web terminal and sending the current position information to the mobile terminal APP; and the mobile terminal APP is used for receiving the position information sent by the monitoring platform and then displaying the current position in real time. According to the intelligent subway protection area construction project informatization management system, the technology and the scene are combined, a WHCORS platform and an RTK/INS combination algorithm are combined, a high-precision surveying and mapping service system is established, meanwhile, the system is integrated into a mobile phone APP of a high-precision map, and an intelligent and convenient management scheme is achieved.

The invention belongs to the technical field of power grid systems, and particularly relates to a medium and long term unit combination accurate modeling technical method comprehensively considering complex large power grid operation constraint conditions, which comprises the following steps: establishing a medium and long term bus load prediction tool considering renewable energy output, including: restoring renewable energy associated bus load sample data; performing medium and long term bus load prediction considering renewable energy data correction; performing medium and long term bus load prediction considering equipment maintenance plan correction; and establishing a medium and long term unit combination and power generation plan compilation tool for promoting renewable energy consumption, wherein the medium and long term unit combination and power generation plan compilation tool comprises a medium and long term unit combination and a power generation plan optimization calculation function module. According to the method, the calculation dimension of the problem model is reduced by considering the aspects of model description, calculation time period, effective integer variable pre-recognition, effective security constraint pre-recognition and the like through the physical characteristics of an actual system, the solving efficiency is greatly improved on the premise of not losing the solving precision, and the engineering application of a medium-and-long-term unit commitment algorithm is realized.

The invention provides a gearbox parameter optimization method and system based on a combined intelligent algorithm. The gearbox parameter optimization method comprises the steps that according to the gearbox gear number, the maximum transmission ratio and the minimum transmission ratio, the transmission ratio of each gear distributed by geometric progression is obtained; obtaining a combination scheme of the transmission ratio of the gearbox according to a certain value range and a certain value step length for the transmission ratio of each gear distributed by the geometric progression; according to the obtained gearbox transmission ratio combination scheme, a preset dynamic property model and a fuel economy model, based on a combination algorithm of an ant colony algorithm and an artificial fish swarm algorithm, multi-objective optimization is carried out to determine a Pareto optimal solution, and an optimal gearbox transmission ratio scheme is selected according to different requirements; according to the method, the ant colony algorithm can rapidly converge to a local optimal value and the artificial fish swarm algorithm can obtain a wide robustness advantage, a combined intelligent algorithm is formed, the dynamic property and the fuel economy are considered, more accurate and rapid multi-objective optimization is realized, and an optimal gearbox matching scheme is efficiently and accurately obtained.

The invention discloses a scheduling, distributing and combining method and system for physical resources in cloud scene, and the method comprises the following steps: obtaining resource request data, and generating resource request object data, physical node data and distribution quantity data according to the processing of the resource request data; obtaining resource candidate data of the resource request object data from a resource database according to resource specification requirements in the resource request object data, and filling the resource request object data with the resource candidate data; combining the resource candidate data according to the physical node data to obtain a resource allocation list; and obtaining a corresponding amount of distribution data from a resource distribution list according to the distribution amount data. The system comprises a client, a server and a resource database, the server comprises a resource request analysis module, a resource candidate screening module, a resource candidate combinatorial algorithm module and an integration result processing module, the problems of time consumption and non-uniformity in allocation and acquisition under a large number of equipment scenes can be solved, and the effects of second-level return and uniform results are achieved.

The invention discloses a station flow prediction method and device. The method comprises the steps of obtaining log data, calculating a predicted value based on the log data according to a Kalman filtering algorithm and a support vector machine (SVM) in order to obtain effective data more conveniently, calculating a weight by comparing an actual flow value, and constructing a parallel combinationmodel, establishing a prediction model according to a flow sequence in log data, obtaining predicted site network flow values, and using test data to check model prediction precision. By comparing results of Kalman prediction, SVM prediction and parallel combination model prediction based on Kalman and SVM, it is proved that a combination algorithm is adopted to predict network traffic, and the defect of single prediction of a traditional time sequence model is overcome; and the flow prediction result of the parallel combination model is reliable and effective and is more suitable for predicting the station flow. The parallel combination model can be applied to prediction of network traffic in a high-performance computing environment.

The invention discloses a machine learning-based early accelerated aging diagnosis method for a ternary lithium ion battery. The method comprises the steps that 17 aging feature parameters representing the health state of the ternary lithium ion battery are extracted from a discharge capacity-voltage curve, a discharge IC curve and a discharge DV curve of the ternary lithium ion battery; then, a new combinatorial algorithm is utilized to accurately diagnose accelerated aging of the ternary lithium ion battery in an early stage, firstly, important features are selected through a random forest, then, linear correlation of the important features is reduced through linear correlation analysis, and finally, accelerated aging is judged through a logistic regression model. Accurate early diagnosis of accelerated aging of the ternary lithium ion battery is realized, so that whether accelerated aging of the ternary lithium ion battery occurs or not is judged in the early stage, and important information is provided for health state management and health state evaluation of the lithium ion battery.