Multi-group ant colony algorithm based on simulated annealing method

To overcome the default of single search tendency, the ants in the colony are divided into several sub-groups. The ants in different subgroups have different trail information and expectation coefficients. The simulated annealing method is introduced to the algorithm. Through setting the temperature changing with the iterations, after each turn of tours, the solution set obtained by the ants is taken as the candidate set. The update set is obtained by adding the solutions in the candidate set to the previous update set with the probability determined by the temperature. The solutions in the candidate set are used to update the trail information. In each turn of updating, the current best solution is also used to enhance the trail information on the current best route. The trail information is reset when the algorithm is in stagnation state. The computer experiments demonstrate that the proposed algorithm has higher stability and convergence speed.

Numerical simulation of solitary wave propagation based on MPS method

The concept of candidate particle set is introduced in the MPS gridless numerical method to generate neighboring particle set ma- trix, which can reduce the CPU time to 1/11 of that before introduction. The Bi-CGSTAB （bi-conjugate gradient stabilized） algorithm is applied to solving the Poisson pressure equation, by which the solving speed is significantly accelerated. The process of solitary waves propagating over a numerical flume and interacting with a vertical wall is simulated. The simulated results of water surface elevation are in good agreement with the analytical solution as well as the measured data. The predicted maximum values of the run-up of solitary waves with various relative incident wave heights agree well with the measured results.

Complete coverage path planning for an Arnold system based mobile robot to perform specific types of missions

We propose a contraction transformation algorithm to plan a complete coverage trajectory for a mobile robot to ac-complish specific types of missions based on the Arnold dynamical system. First, we construct a chaotic mobile robot by com-bining the variable z of the Arnold equation and the kinematic equation of the robot. Second, we construct the candidate sets including the initial points with a relatively high coverage rate of the constructed mobile robot. Then the trajectory is contracted to the current position of the robot based on the designed contraction transformation strategy, to form a continuous complete cov-erage trajectory to execute the specific types of missions. Compared with the traditional method, the designed algorithm requires no obstacle avoidance to the boundary of the given workplace, possesses a high coverage rate, and keeps the chaotic characteristics of the produced coverage trajectory relatively unchanged, which enables the robot to accomplish special missions with features of completeness, randomness, or unpredictability.

Differential Privacy Trajectory Protection Method Based on Spatiotemporal Correlation

Location-based services provide service and convenience,while causing the leakage of track privacy.The existing trajectory privacy protection methods lack the consideration of the correlation between the noise sequence,the user’s original trajectory sequence,and the published trajectory sequence.And they are susceptible to noise filtering attacks using filtering methods.In view of this problem,a differential privacy trajectory protection method based on spatiotemporal correlation is proposed in this paper.With this method,the concept of correlation function was introduced to establish the correlation constraint of release track sequence,and the least square method was used to fit the user’s original track and the overall direction of noise sequence to construct noise candidate set.It ensured that the added noise sequence has spatiotemporal correlation with the user’s original track sequence and release track sequence.Also,it effectively resists attackers’denoising attacks,and reduces the risk of trajectory privacy leakage.Finally,comparative experiments were carried out on the real data sets.The experimental results show that this method effectively improves the privacy protection effect and the data availability of the release track,and it also has better practicability.