Zhihui Zhan

Bio: Zhihui Zhan is an academic researcher. The author has contributed to research in topics: Wireless sensor network & Node (networking). The author has an hindex of 6, co-authored 8 publications receiving 86 citations.

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

Abstract: 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.

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

Abstract: 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 through a simulation test.

Wireless sensor network node coverage optimization method based on genetic algorithm

Abstract: 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 use.

Airplane arrival scheduling method based on ant colony algorithm

Abstract: Arrival sequencing and scheduling (ASS) is an important study of air traffic flow management. High-efficiency ASS optimization is very important to improve the efficiency, the space utilization rate and the safety of airports. In the invention, the ASS in dynamic environment is taken into consideration, receding horizon control is introduced and ant colony algorithm is applied in arrival sequencing and scheduling. The simulation results show that the ant colony algorithm based on receding horizon control strategy can not only effectively solve the problems of ASS in dynamic environment, but also greatly lower the computation complexity. Accordingly, the method is suitable for real-time ASS in terminal areas.

Method for planning airplane flight based on inheritance algorithm

Abstract: The invention solves the problem of planning flights in the airplane dispatching problem by applying a heredity algorithm. Through unknown variables or integer coding of the number of flights for each airplane type on the airline, the invention realizes expression of the solution target in the heredity algorithm. The chromosome practicability is patched by adopting an effective patching strategy based on a punishment style so as to reduce the appearance of an illegal solution, so that a solution result conforms to the practical situation. The algorithm in the invention is verified to be correct and effective through illustrations, and the invention has the advantages of strong extendibility and practicability.

Multi-objective optimization method for collaborative allocation of time slots of multi-runway approaching-departing flights

Abstract: The invention relates to a multi-objective optimization method for collaborative allocation of time slots of multi-runway approaching-departing flights, belonging to the technical field of civil aviation. The multi-objective optimization method is mainly based on a collaborative decision-making idea and comprises the following steps of: firstly, dividing a time interval into a plurality of time slots, determining the approaching-departing capacity of an airport and dynamically creating time slots; secondly, establishing a multi-objective optimization model with minimum total delay cost, fair delay loss of each aviation company and balanced use frequency of each runway as objectives and with the effectiveness and the approaching-departing capacity of the airport as constraining conditions; and finally, solving by using a genetic algorithm to obtain an optimal flight time slot allocation scheme. The multi-objective optimization method disclosed by the invention is suitable for solving the time slot allocation problem of the approaching-departing flights of each airport.

Unmanned aerial vehicle route planning system and unmanned aerial vehicle route planning method based on genetic programming

Abstract: Disclosed are an unmanned aerial vehicle (UAV) route planning system and a UAV route planning method based on genetic programming. The method comprises the following steps: initial populations of a tree structure are built through a UAV model module; each individual is decoded and the fitness value of each individual is calculated through a genetic programming algorithm module; selecting and breeding operations are performed between the populations, and an optimal population is obtained through a plurality of iteration processes; and finally, an optimal individual is selected from the optimal population and decoded through a UAV task module to obtain an optimal route of genetic programming. According to the invention, initializing, decoding, selecting and breeding steps are performed by use of the tree structure to optimize the route constantly. The optimization process is quick, the method is visual, the performance of the planned route is improved, the computing time is reduced, the degree of fitness is optimized, and the system and the method are of very high feasibility and robustness.

Dynamic scheduling method for multi-runway flight getting in and out

Abstract: The invention discloses a dynamic scheduling method for multi-runway flight getting in and out. The method comprises the following steps that flight delay cost is analyzed, and a flight delay cost minimization objective function for multi-runway flight getting in and out scheduling is provided; theoretic delay time is calculated, and flight delay time of different aircraft types is converted into delay time of unit delay cost; fairness of multi-runway scheduling is analyzed, and the objective function considering the fair factor is built; ordinary constrain conditions of multi-runway flight dynamic scheduling are provided; the multi-runway flight scheduling constrain conditions considering flight delay are designed; the dynamic scheduling problem of multi-runway flight getting in and out is solved by adopting the genetic algorithm, dynamic scheduling of multi-runway flight getting in and out is achieved, and the purposes of improving the runway using rate and reducing the flight delay cost are achieved. According to the method, influence on multi-runway scheduling caused by flight delay is sufficiently considered, and the purposes of improving the runway using rate and reducing the flight delay cost are achieved.

Network coding-based multicast routing method applied to vehicular ad hoc network

Abstract: The invention provides a network coding-based multicast routing method applied to a vehicular ad hoc network by combining the characteristics of the vehicular ad hoc network. The method comprises the following steps of: acquiring information of two-hop neighboring nodes of a node sending a data packet to form a two-hop neighbor information sheet by the node sending the data packet; selecting a routing mode according to the relationship between the number of the neighboring nodes and the threshold value of the number of the nodes existing in every kilometer, which is recorded in the two-hop neighbor information sheet, if the number is more than the threshold value, entering a network coding mode, and otherwise entering an opportunistic routing mode; determining a forward node set and then determining the data sending rate k and local topological max-flow min-cut value n of the current node in the network coding mode; calculating a minimum finite field by combining maximum distance separable codes and selecting nonzero elements from the field to construct an overall coding matrix which meets k-row linear independence relationship; transmitting a coding rule according to the coding matrix by the node and coding in strict accordance with the rule by a downstream node; and repeating the processes until information arrives at a target node. The routing method has the advantages of expandability, high efficiency and high adaptability.

Aviation hub emergency management and control method

Abstract: The invention relates to the technical field of communication and transportation design and management. Foundation support and a method are provided for a purpose that an aviation hub center specifically schedules and emergently manages. The adopted technical scheme is that an aviation hub emergency management and control method comprises a step of making a preliminary evaluation on an aviation hub comprehensive service level for a flight timetable influenced by real-time information such as possible abnormal states of airplanes and passengers. If the service level is not changed greatly, the timetable does not need to be optimized, and flying time is executed according to the timetable. If the service level is changed greatly, an emergency management plan is optimized and adjusted according to the flight timetable, the real-time information, specific characteristics and various restraints of the an aviation hub, and an optimized and adjusted timetable is fast worked out. Similarly, a preliminary evaluation of the aviation hub comprehensive service level is made for the timetable, if the service level is not improved, the timetable is continuous to be optimized, and if the service level is improved, the optimized and adjusted timetable is executed. At last, a comprehensive assessment is made on a practical implementation result. The aviation hub emergency management and control method is mainly applied to the planning design and management of the communication and transportation.