8 results about "Combination algorithm" patented technology

The application belongs to the technical field of path planning, and discloses a robot path planning method based on combination of particle swarm, ant colony and A-Star algorithm, which comprises the following steps: generating a grid map, obtaining positions of obstacles and feasible areas in the grid map, constructing an accessible distance matrix, determining starting positions and target positions of each robot in the grid map in a robot cluster; and using the particle swarm, ant colony combination algorithm and A-Star algorithm to perform path optimization planning on the robot cluster based on the accessible distance matrix, the starting positions and the target positions of the robots in the grid map, so as to obtain an optimal path. The application combines the ant colony algorithm, the algorithm and the simulated annealing algorithm with the particle swarm algorithm, and performs robot obstacle avoidance path optimization, so that the robot can quickly find a path from the starting point to the end point while completing obstacle avoidance.

This invention provides a bidding information management system and method based on Internet technology. It collects and preprocesses bidding data from participating parties; employs a combined algorithm combining the Analytic Hierarchy Process (AHP) and entropy weighting to perform multi-dimensional real-time comparison and comprehensive scoring of the preprocessed bidding data, yielding bidding results and rankings; it encrypts the bidding data and calculation results using dual encryption technology and constructs a secure transmission channel with firewall protection; it pushes the bidding results to all participants in real time through diversified notification channels; and it displays detailed results, rankings, and scoring criteria through a visual interface, enabling transparent querying of bidding information. This invention solves the problems of delayed result calculation, untimely notification, insufficient data security, and low transparency in existing bidding systems, significantly improving bidding efficiency and enhancing public trust.

The embodiment of the application discloses a multi-modal data-driven intelligent cabin parameter adaptation method and system, and relates to the technical field of intelligent cabin human-computer interaction. The method synchronously collects physiological data, multi-modal interaction data, driving behavior and scene data, extracts core features after preprocessing, adopts an evidence theory attention mechanism combination algorithm to construct a dynamic fusion adaptation model, realizes accurate and real-time adaptation of multiple cabin parameters such as sitting posture, vision, control and environment, and covers special groups such as the elderly, children and disabled users and all driving scenes. The application solves the defects of the prior art, such as insufficient data fusion dimension, static adaptation model, lack of psychological support and special group adaptation, parameter prediction error and whole-process delay, significantly improves driving safety and driving comfort, and is suitable for parameter optimization of various intelligent cabin products.

This invention discloses a method and apparatus for evaluating wind turbine retrofitting schemes based on operational data, relating to the field of wind power engineering technology. The method includes: collecting at least five years of operational data from the target wind farm; preprocessing the data using the DBSCAN-segmented quartile combination algorithm; restoring the free-flow wind speed through primary and secondary correction functions to separate the impact of wind resource fluctuations and obtain the net power generation revenue increment from the retrofit; and establishing a multi-dimensional comprehensive evaluation system to assess the degree to which the technological upgrade improves the overall benefits of the wind farm. The apparatus includes a data acquisition module, a correction module, and an evaluation module, which execute the steps described above. This invention solves the problems of insufficient representative wind measurement data and single evaluation indicators for retrofitting schemes. By utilizing existing operational data from wind farms, it can effectively isolate the impact of wind resource fluctuations, explore the net power generation revenue increment brought about by the technological upgrade of wind turbines, improve the accuracy and comprehensiveness of the evaluation, and provide a scientific basis for the selection of retrofitting schemes.

This application provides a path planning method and system for collaborative coverage search of unmanned surface vessel (USV) swarms. The method includes: dividing the USV swarm into several subsets and determining the candidate path points and corresponding search intensities for each subset; using an ant colony algorithm based on multi-ant combinations to determine the optimal global path for each subset to conduct collaborative coverage search of the target water area, wherein the multi-ant combination algorithm is implemented through several multi-ant combinations, each multi-ant combination consisting of several ants representing each subset, and in each iteration, each ant in each multi-ant combination sequentially and cyclically selects the next path point from the candidate path points corresponding to the subset it represents; and assigning the optimal global path corresponding to each subset to all USVs in that subset. The technical solution of this application can rationally plan the path for collaborative coverage search of the target water area by multiple USV swarms.

The application relates to a regional ionospheric delay generation method based on space-time constraint enhancement, which comprises the following steps: obtaining original data of reference stations in a target region and completing preprocessing; based on the preprocessed data, adopting an M-W combination model and an ionosphere-free combination algorithm to solve and fix double-difference integer ambiguity between a main reference station and an auxiliary reference station; based on the obtained double-difference integer ambiguity, solving carrier phase double-difference ionospheric delay between the main reference station and the auxiliary reference station through a carrier phase double-difference equation; adopting a linear combination model to perform spatial interpolation on the carrier phase double-difference ionospheric delay, obtaining regional ionospheric delay correction based on spatial interpolation; constructing a regional ionospheric delay short-term change prediction model, obtaining regional ionospheric delay correction based on time series prediction; combining the obtained regional ionospheric delay correction and the regional ionospheric delay correction, weighting with a weight coefficient to generate a final regional ionospheric delay.

The application discloses a Korean input method, an input device and an electronic device, and relates to the technical field of input methods. The Korean input method comprises the following steps: obtaining a Korean character input by a user; performing single-character processing on the Korean character based on the input sequence of the Korean character, determining combinations capable of forming a single character and characters incapable of forming a single character; directly decoding the combinations capable of forming a single character into single characters, and performing a completion operation based on the single characters and / or the characters incapable of forming a single character to obtain new candidate words and / or candidate characters. The application firstly establishes a Korean basic term model, performs character forming processing on Korean characters through a Korean maximum combination algorithm, expands single characters into word groups through the Korean basic term model, expands Korean characters into Korean single characters, and trains the Korean basic term model according to the last selection of a user, thereby providing more suitable expansion results for the user and improving input efficiency during input.

The present application provides a kind of real-time online early warning method of supersonic inlet non-start state based on deep learning, combined algorithm can receive sensor historical pressure signal, automatically segmented pressure signal by WCA-PCCD, constructs training data set, trains in single channel and multichannel WPT-CNN network, obtains the classifier for real-time online early warning, receives real-time dynamic test data by classifier, realizes inlet non-start early warning.The present application proposes two innovations for real-time online supersonic inlet non-start state early warning, respectively WCA-PCCD and MC-WPT-CNN, for different stages of pattern recognition.Compared with previous time series segmentation and pattern recognition, with the help of optimization algorithm and multidimensional deep learning model, early warning task is more simple and fast, with stronger accuracy, relatively simple implementation process, suitable for different types of inlet and various working conditions.Compared with traditional early warning method, the difficulty and complexity of early warning work are greatly reduced.