Papers by Keyword: Ant Colony Algorithm (ACA)

Abstract: For real-time monitoring the behavior of pigs in piggery, the method that combined the advantages of wavelet multi-scale analysis with invariant moments is proposed. Firstly, the original image is pre-processed by using ant colony algorithm to extract object contour. Then the target contour edge growth method and binary morphology are used, and the outlines of pigs are extracted by canny operator. Wavelet moment was used to get the global features of an image and increase the structural details of the image feature description. Finally, the neural network is applied to identify four behaviors including normal walking, walking down, looked up walking and lying of pigs. Experimental results show that the accuracy of the classification and identification of swine gesture reached more than 95%. This method has a better effect in the recognition of pigs and the noise resistance.

Abstract: Dynamic RWA algorithm which supports differentiating business service quality levels becomes a hot research in optical networks. This paper proposes a better ant colony algorithm for routing and wavelength assignment in ASON with supporting differentiating SLA of services and 10P bps network capacity. Firstly, the algorithm adds the concept of business interval period M to dynamically adjust the wavelength grouped in different periods So as to better meet the sercice requests of different levels; Secondly the algorithm adds a link selection control factor in the transition probability function ACA in order to achieve a better link load balancing. Simulation results show that after joining the cyclical and link selection control factor, blocking rate becomes lower and the load of network becomes more evenly.

Abstract: The paper, aiming at status of car networking, researched the key technology of dynamic traffic information services under the condition of car networking, proposed overall system structure based on the framework of car networking. Through traffic perception technology and dynamic induction technology and on the basis of analyzing the entire working process of car networking, the paper also realized the effective management and control on car networking. Experimental results show that this control technology model can better deal with data processing under the car networking.

Abstract: Aimed at solving premature convergence and low speed in heuristic algorithms for TSP problems, this paper analyzed the principle of Max-Min Ant colony algorithm (MMAS) and Lin-Kernighan algorithm, then proposed a dynamic exchange of Max-Min Ant colony algorithm (MMAS-LK). The new algorithm used MMAS to initially a set of the solutions in the early state, then utilized the improved Lin-Kernighan algorithm for local optimization, and dynamic adjustment parameters according to the process of computing avoid falling into local optimum. The simulation results showed that the proposed algorithm compared with the original MMAS and Lin-Kernighan algorithm, it has a better speed and precision in the TSP problem.

Abstract: According to real-time and limited energy of the wireless sensor network (WSN), this paper proposed an ant-colony algorithm (ACO) for optimal routing. The algorithm limited the search space to next node based on search angle and designed directional pheromones to guide ants to the destination node. Using negative feedback mechanism encouraged later ants to choose the optimal path. When ants are timeout with limited life cycle, go back along the way and reduce the pheromone. Probability-transfer function contained the factors of distance, energy, pheromones and search angle. Compared with other ACOs, the results show that it can balance the energy consumption and improve the routing in aspects of energy, dead nodes, short path and time delay.

Abstract: Object: To optimize the rigidity registration algorithm between X-ray fluoroscopy and CT, and improve the accuracy of registration. Method: By changing the transmission parameters of the ray tracing, it can obtain the original DRR images and the float DRR image for registration. In trials, it uses ant colony algorithm as the optimized search strategy and Mutual information as the similarity measure. Result: ant colony algorithm and the improved ant colony algorithm compared to the classic Powell algorithm to improve the accuracy of registration about 10% and 20%, achieved good results. Conclusion: Ant Colony Algorithm as optimization search strategy can effectively solve the local minima problem in 2D-3D medical image registration, and further improve the accuracy of registration.

Abstract: The optimization of scheduling is an important aspect of the construction project plan, the paper proposes applying improved ant colony optimization to solve the public construction projects scheduling optimization problem under limited resource condition and constructs the mathematical model of the project construction schedule optimization. Further verify the validity of the model and the improved ant colony optimization on the schedule of the optimization problem solving has universal applicability.

Abstract: This paper established the mathematical model of Logistics distribution routing problem,and departed the multiple vehicle routing problem into a single vehicle distribution problem with the save mileage method ,then the ant colony algorithm were used to optimize the single vehicle distribution problem. Finally through a case shows that the model for the practical application of logistics distribution has certain reference significance.

Abstract: Bus routing problem is the basic work of public transit planning and operation. This paper develops a solution for the optimal routing problem of bus connected with a passenger transfer center based on the research of vehicle routing problem (VRP), which is an important issue in the logistics distribution. The optimal routing solution is formulated as linking a series of bus stops in a certain order, aiming at minimizing the total cost, which includes user and supplier costs. To solve the problem, a weighting function is established to determine the weight of every link first and then an ant colony algorithm (ACO) is used to calculate the optimal solution. At last, a case study is presented based on the existing routes and stops served for the Huilongguan Community in Beijing, and the results shows that the set of routes obtained from the optimal solution costs less than the existing one.

Abstract: It has discussed the approach to establish the models of terrain, threat and the evaluation of route cost in the route planning for UAV in low-altitude penetration. An Ant Algorithm is introduced into UAV route planning, since stagnation may appear during searching in use of traditional ant colonies algorithm,this paper introduces yaw angle to improve heuristic information, establishes the prior search set, makes ant colony algorithm the more rapid and effective search to the best route, simulation results prove the efficiency of the planning method.