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Небесная энциклопедия

Космические корабли и станции, автоматические КА и методы их проектирования, бортовые комплексы управления, системы и средства жизнеобеспечения, особенности технологии производства ракетно-космических систем

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Мониторинг СМИ

Мониторинг СМИ и социальных сетей. Сканирование интернета, новостных сайтов, специализированных контентных площадок на базе мессенджеров. Гибкие настройки фильтров и первоначальных источников.

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Применить Всего найдено 8. Отображено 8.
06-07-2011 дата публикации

Intelligent logistics distribution and delivery based on discrete particle swarm optimization algorithm

Номер: CN0102117441A
Автор: ZHANG JUN, YUEJIAO GONG, GONG YUEJIAO
Принадлежит:

The invention discloses intelligent logistics distribution and delivery based on a discrete particle swarm optimization algorithm and aims at scheduling the path of a transportation vehicle so as to save the transportation cost. A coding mode and an operator based on the set and the probability are introduced on the basis of a framework of a standard particle swarm optimization algorithm, the particle swarm optimization algorithm which is originally suitable for a continuous space can be introduced into a discrete combined optimized space, so that the problem that the path of the vehicle is scheduled is solved and the advantages of high operation efficiency, strong optimization capacity, strong robustness, and the like endowed by the traditional particle swarm algorithm can be maintained. In addition, by using heuristic information to construct the positions of particles and introduce a local operator search, features of the problem and information contained in the data are utilized, and ...

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Номер записи: 1
17-06-2009 дата публикации

Wireless sensor network node coverage optimization method based on ant colony algorithm

Номер: CN0101459914A
Автор: ZHANG JUN, ZHAN ZHIHUI, GONG YUEJIAO, FENG XINLING, CHEN MENGJUN, CHEN NI, HUANG TAO, ZHIHUI ZHAN, YUEJIAO GONG, XINLING FENG, MENGJUN CHEN, NI CHEN, TAO HUANG
Принадлежит:

The invention relates to a method for exerting an ant colony algorithm on an optimal covering problem of a wireless sensor network node, the emphasis of the problem is emphasized on a random covering problem in wireless sensor network node covering when the ant colony algorithm is used as an optimal tool to solve the problem, and a problem model is divided to a 0/1 programming problem, and the ant colony algorithm is used to solve. The method comprises putting pheromones on a sensor network node in an algorithm which is proposed, endowing two pheromones to each node, and respectively indicating the selected and unselected information quantity of the node. And meanwhile, effective heuristic information is effectively arranged in the algorithm to guide the searching behaviors of ants, and the ants can decide which nodes to be used to cover according to the pheromones and the heuristic information. And finally, the efficiency and high efficiency of the algorithm which is invented are checked ...

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Номер записи: 2
14-07-2023 дата публикации

Method and system for estimating arrival time

Номер: CN116431253A
Автор: FANG JUN, MA NAN, GONG YUEJIAO, ZHOU WANYI, WU GUOBIN, CHAI HUA
Принадлежит:

The embodiment of the invention provides a user interface applied to a mobile travel system, and the user interface comprises a first display area which is used for displaying at least one planned path from a departure place to a destination, and the at least one planned path comprises a selected path; and the second display area is used for displaying the estimated time range of the selected path. The embodiment of the invention also provides a method for estimating the arrival time associated with the riding order, and the method comprises the steps: inputting the riding order information into a trained machine learning model, the riding order information comprises a departure place and a destination associated with riding, and the arrival time is estimated according to the arrival time. The trained machine learning model has a multi-task learning structure; and based on the trained machine learning model, obtaining the standard estimated time from the departure place to the destination ...

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Номер записи: 3
03-06-2009 дата публикации

Wireless sensor network node coverage optimization method based on particle swarm algorithm

Номер: CN0101448267A
Автор: ZHANG JUN, ZHAN ZHIHUI, GONG YUEJIAO, FENG XINLING, CHEN MENGJUN, CHEN NI, HUANG TAO, ZHIHUI ZHAN, YUEJIAO GONG, XINLING FENG, MENGJUN CHEN, NI CHEN, TAO HUANG
Принадлежит:

A particle swarm algorithm is applied to an optimum coverage problem of wireless sensor network nodes, and the invention provides a coverage mechanism of the particle swarm optimization algorithm based on a discrete binary edition, and the mechanism is used for performing optimal solution on the wireless sensor network node coverage problem. The method comprises the following steps: defining the wireless sensor network node coverage problem as a 0/1 planning problem, encoding individuals of a binary particle swarm algorithm as a 0/1 binary string and then performing optimization by an evolutionism of the particle swarm algorithm. In the method, two important indexes are defined to evaluate the solution results, one index is 'coverage' of a region, and the other index is 'consumption rate' of the sensor. Validity and high efficiency of the algorithm are verified by a simulation experiment.

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Номер записи: 4
04-04-2023 дата публикации

Method, system and device for optimizing crowd dredging route of high-speed rail station and medium

Номер: CN115907252A
Автор: CHEN WEINENG, OU WENJIE, GONG YUEJIAO
Принадлежит:

The invention discloses a high-speed rail station crowd guidance route optimization method, system and device and a medium, and the method comprises the steps: obtaining the layout information of a high-speed rail station, and representing a high-speed rail station scene as a complete graph according to the layout information; screening the edges in the complete graph according to a preset screening condition; according to the screened complete graph, representing the design problem of the crowd dispersion facility layout of the high-speed rail station as an optimization problem of solving a multi-dimensional binary coding vector; historical people flow data of the high-speed rail station are obtained, a simulation model of the high-speed rail station scene is constructed according to the historical people flow data and the optimization problem, the simulation model is optimized through a discrete competition particle swarm optimization algorithm, and a final crowd dispersion route is obtained ...

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Номер записи: 5
07-04-2023 дата публикации

Distributed clustering method and device on wireless sensor network and medium

Номер: CN115935203A
Автор: CHEN WEINENG, GUO XIAOQI, GONG YUEJIAO
Принадлежит:

The invention discloses a distributed clustering method and device on a wireless sensor network and a medium, and the method comprises the steps: employing NP optimal data in a respective database by each sensor, and training a local agent model; fusing and synthesizing a global proxy model through the global model; replacing real evaluation with a global agent model to carry out evolutionary optimization, and sending the found candidate solution to an unterminated sensor; the unterminated sensor receives the candidate solution, if the candidate solution is within the sensing range of the sensor, the adaptive value of the candidate solution is actually evaluated through a clustering evaluation criterion, and the database and the local agent model are updated; obtaining new offspring of each sensor, and adopting a local model to assist in evaluating new offspring individuals and historical optimal particles; and carrying out real evaluation on new offspring individuals with predicted values ...

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Номер записи: 6
17-06-2009 дата публикации

Wireless sensor network node coverage optimization method based on genetic algorithm

Номер: CN0101459915A
Автор: ZHANG JUN, ZHAN ZHIHUI, GONG YUEJIAO, FENG XINLING, CHEN MENGJUN, CHEN NI, HUANG TAO, ZHIHUI ZHAN, YUEJIAO GONG, XINLING FENG, MENGJUN CHEN, NI CHEN, TAO HUANG
Принадлежит:

The invention relates to a method for using a gen etic algorithm to solve an optical covering problem of a wireless sensor network node, which comprises dividing a problem model to an 0/1 programming problem when using the gen etic algorithm as an optimal tool to solve problems, and then, using a gen etic algorithm of binary code to solve the problems, coding colored bodies of the gen etic algorithm to a 0/1binary string in the algorithm, and then, optimizing through an evolutionary mechanism. Sensors with the number of N are scattered at random, and an individual coding is a 0/1binary string with N bit length. When the sensors are optimally selected, if a sensor is selected, and then, a relative bit in the individual coding is set to be 1, or the bit is set to be 0. An individual coding and a real network structure are directly corresponding to each other through the coding mode, the gen etic algorithm not only is easy to understand, but also is simple to achieve, and is convenient to ...

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Номер записи: 7
11-04-2023 дата публикации

Distributed sensor target positioning method and device and storage medium

Номер: CN115955656A
Автор: CHEN WEINENG, CHEN TAIYOU, GONG YUEJIAO
Принадлежит:

The invention discloses a distributed sensor target positioning method and device and a storage medium. The method comprises the following steps: acquiring node information of a sensor; performing optimization processing on node information by adopting a bidirectional learning particle swarm optimization framework containing an adaptive communication interval adjustment mechanism and an external learning particle update strategy; performing one or more internal learning on each node; the neighbor nodes communicate with each other and transmit a current population solution; performing primary external learning on the nodes; if the population converges, ending optimization; otherwise, the communication interval is adaptively adjusted according to the change of the adaptive value, and the next round of learning is continued. Through a distributed particle swarm optimization framework and an external learning strategy, the particle swarm optimization algorithm is applied to a distributed optimization ...

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Номер записи: 8