The invention provides a method for determining the routing of a wireless sensor network based on energy and delay ant colony optimization. The method comprises the steps of: collecting energy, delay and data flow information of a source node, nodes passed by an advancing path and a target node of the wireless sensor network; and enabling return ants carrying the information to return to the resource node according to the advancing path of advancing ants from the target node. On the returning way, when the return ants reach at a node every time, the node updates a pheromone value list which contains the energy consumption and the transmission delay of the node and nodes adjacent to the node according to the energy and delay ant colony optimization, so that data packets or ants reaching atthe node subsequently determine advancing routes according to the updated pheromone value list. Compared with the traditional method based on PEGASIS and LEACH, the method has obvious advantages in energy efficiency, transmission real-time performance and network self-adaptation performance.

Method for determining routing of wireless sensor network based on energy and delay ant colony optimization

The invention discloses a network path finding method, an optimal path selecting method and a system thereof. The method comprises the steps: pre-establishing a topology file consisting of logic network nodes, an arc and magnitudes on the arc, wherein the arc is the connecting line between the two logic network nodes and the magnitudes on the arc are weights given to the arc; collecting actual data information of the topology file with different studying magnitudes and respectively updating the topology file; figuring out the shortest path between a first logic network node as the start and a second logic network node as the end by a path finding method of the shortest path between two nodes according to the topology file after each updating; and selecting the corresponding shortest path as the optimal path according to different studying magnitudes. The method can collect actual data information of the topology file with different studying magnitudes and respectively updates the topology file, figure out the shortest path according to the topology file after each updating, and precisely work out the optimal path between the start and the end or the logic nodes.

Network path finding method, optimal path selecting method and system thereof

The invention provides a method for predicting a three-dimensional protein structure. The method comprises the steps of: a, selecting a target ant colony and initializing parameters of an ant colony algorithm; b, initializing protein conformation and establishing a mapping relationship between the protein conformation and a fragment library; c, optimizing the target ant colony under the guidance of pheromones by taking any one position on the protein conformation as a starting point, performing energy calculation on the optimized protein conformation, and selecting the protein conformation with the minimum energy; d, locally optimizing the protein conformation with the minimum energy, performing energy calculation, updating a pheromone matrix according to a calculation result, comparing the energy of the locally optimized protein conformation and the energy of the protein conformation with the minimum energy, and selecting the protein conformation with the minimum energy; e, repeating the steps c-d to obtain better protein conformation; and f, performing Loop reconstruction on the better protein conformation to obtain the optimal protein conformation. The invention further provides a device for predicting the three-dimensional protein structure.

Method and device for predicting three-dimensional protein structure

Implementation method for test optimization of complex system

The invention relates to a routing selecting problem, belonging to the cognitive wireless multicasting routing field. A multicasting routing algorithm is designed aiming at dynamics and differentiation of wireless network frequency spectrum distribution. The algorithm of the invention mainly comprises the following steps: 1, establishing a single-stage game model of the multicasting routing algorithm; 2, participating in the end-to-end delay time of a node i; 3, establishing a multi-stage game model of the multicasting routing algorithm; and 4, checking the reliability of the algorithm. The routing history is participated in next routing by the invention, thereby simplifying redundancy of the algorithm. Moreover, based on the thoughts of repeated games in dynamic games, reputation is introduced into the routing so as to solve the problems that cognitive node not only ensures the selected route can meet the requirement of the minimal end-to-end delay time under the condition of not disturbing master users, but also causes redundancy of the routing algorithm to realize a design target to simplify the algorithm.

Repeated game-based multicast routing algorithm in cognitive wireless network

The invention discloses a protein folding optimizing method based on an ant colony algorithm. The method comprises the following steps that: firstly, ants are arranged in a left initial square grid and a right initial square grid by using a hydrophobic-polar model; then, amino acids in the protein are arranged into grids by the ants according to a pheromone and heuristic information, updating of the local pheromone is executed while the ants make a movement, if an occurrence of stasis occurs, a maintenance is performed to a corresponding pathway; finally, after all the ants complete a construction for protein folding pathways, updating for the global pheromone is executed. A protein structure with smallest free energy can be obtained by constantly repeating the steps. Compared with the prior algorithm for solving the problem of protein folding, the protein folding optimizing method provided by the invention has the advantages of high efficiency, quickness, etc.

Protein folding optimizing method based on ant group algorithm

The present invention discloses a multicast routing method based on a distance complete ant colony algorithm. Firstly, a distance complete graph is established for a multicast routing network; then multicast trees are constructed randomly based on the ant colony algorithm and a Prim algorithm, wherein, the setting of heuristic information makes the algorithm to be more disposed to select target nodes. A redundant detection and a correction are carried out on the generated multicast trees and the updating of local information elements is implemented. Lastly, after all of the ants accomplish the constitution of a solution, the updating of the entire information elements is implemented, the information elements on the side of the most preferable tree in history are reinforced. By simulating the test result and the comparison with the algorithms of the same type, it shows that the distance complete ant colony algorithm of the present invention is capable of solving the problem of multicast routing more quickly.

Zhang Jun

Papers

Protein folding optimizing method based on ant group algorithm

Multi-routing method for full ant group algorithm based on distance