Design of Vision Measurement Device for Seeding Robot based on Ant Colony Algorithm and Nonlinear Circuit System

2017 ◽  
Vol 12 (3) ◽  
pp. 42-50 ◽  
Author(s):  
Liu Xiaojie ◽  
Zhu Hongjin ◽  
Fan Honghui ◽  
Zhang Min
Keyword(s):  
Ant Colony Algorithm ◽  
Control Process ◽  
Border Crossing ◽  
Ant Colony ◽  
Nonlinear Circuit ◽  
Measurement Device ◽  
Vision Measurement ◽  
Low Efficiency

In order to solve the problem of low efficiency and accuracy in the control process of seeding robot, a vision measurement device based on ant colony algorithm and nonlinear circuit system is proposed in this paper. By scanning the trunks areas, border crossing points of the bottom of the tree and ground were detected, and these points were divided into two clusters on both sides based on neighbouring relationship. The simulation result is compared with artificial recognition in a two-orchard environment. The result shows that the proposed method is reliable, safe and can satisfy the moving request of seeding robot.

Design of Vision Measurement Device for Seeding Robot based on Ant Colony Algorithm and Nonlinear Circuit System

2020 ◽  
pp. 400-408
Author(s):  
Liu Xiaojie ◽  
Zhu Hongjin ◽  
Fan Honghui ◽  
Zhang Min
Keyword(s):  
Ant Colony Algorithm ◽  
Control Process ◽  
Border Crossing ◽  
Ant Colony ◽  
Nonlinear Circuit ◽  
Measurement Device ◽  
Vision Measurement ◽  
Low Efficiency

In order to solve the problem of low efficiency and accuracy in the control process of seeding robot, a vision measurement device based on ant colony algorithm and nonlinear circuit system is proposed in this paper. By scanning the trunks areas, border crossing points of the bottom of the tree and ground were detected, and these points were divided into two clusters on both sides based on neighbouring relationship. The simulation result is compared with artificial recognition in a two-orchard environment. The result shows that the proposed method is reliable, safe and can satisfy the moving request of seeding robot.

Effective ACPS-Based Rescheduling of Parallel Batch Processing Machines with MapReduce

2014 ◽  
Vol 575 ◽  
pp. 820-824
Author(s):  
Bin Zhang ◽  
Jia Jin Le ◽  
Mei Wang
Keyword(s):  
Big Data ◽  
Parallel Computing ◽  
Ant Colony Algorithm ◽  
Search Algorithm ◽  
Ant Colony ◽  
Search Problem ◽  
Parallel Search ◽  
Good Efficiency ◽  
Heuristic Scheduling ◽  
Low Efficiency

MapReduce is a highly efficient distributed and parallel computing framework, allowing users to readily manage large clusters in parallel computing. For Big data search problem in the distributed computing environment based on MapReduce architecture, in this paper we propose an Ant colony parallel search algorithm (ACPSMR) for Big data. It take advantage of the group intelligence of ant colony algorithm for global parallel search heuristic scheduling capabilities to solve problem of multi-task parallel batch scheduling with low efficiency in the MapReduce. And we extended HDFS design in MapReduce architecture, which make it to achieve effective integration with MapReduce. Then the algorithm can make the best of the scalability, high parallelism of MapReduce. The simulation experiment result shows that, the new algorithm can take advantages of cloud computing to get good efficiency when mining Big data.

Ant Colony Algorithm Application In Glass Fiber Textile Machine Parameter Tuning

2012 ◽  
Vol 462 ◽  
pp. 71-76 ◽  
Author(s):  
Li Hong Zhang ◽  
Shu Qian Chen ◽  
Gui Zhi Bai
Keyword(s):  
Glass Fiber ◽  
Pid Control ◽  
Ant Colony Algorithm ◽  
Control Process ◽  
Parameter Tuning ◽  
Integral Function ◽  
Parameters Optimization ◽  
Ant Colony ◽  
Control Parameters ◽  
Optimization Strategy

In glass fiber textile process, non-axis volume cloth drive motor with glass fabric volume increases, increasing the pressure on the drive shaft, moreover, because of cloth non-axis volume makes the pressure in the process of change is evident, that causes the motor load changing constantly, the traditional PID control system controller cannot timely tracking response. In order to solve the problem which the control parameters optimizes, improves the system performance, proposed a new Ant colony algorithm PID parameters optimization strategy, this solution can combine characteristics that Ant colony algorithm can fast find the most superior parameter solution stably and PID can precise adjustment. In the control process, taken the PID parameters as a colony of ants, used to control the absolute error integral function as the optimization objective, dynamically adjust the PID control parameters in the control process, so as to realize the PID parameters on-line tuning.

Research of Hybrid Mobile Agent Routing in Wireless Sensor Network

2013 ◽  
Vol 341-342 ◽  
pp. 1181-1186
Author(s):  
Li Hong Zhang ◽  
Shu Qian Chen
Keyword(s):  
Mobile Agent ◽  
Ant Colony Algorithm ◽  
Data Transfer ◽  
Average Energy ◽  
Optimal Solution ◽  
Global Search ◽  
Ant Colony ◽  
Feedback Information ◽  
Low Efficiency ◽  
Average Energy Consumption

The mobile agent route is essentially a multi-constraint optimization problem, Genetic Algorithms has fast random global search ability, but the feedback information of the system does not use and has the problem of low efficiency of finding exact solutions, propose a genetic hybrid ant colony algorithm for WSN mobile agent route. Use of the fast random global search capabilities of genetic algorithm to find better solutions, then the better solution replaced by the initial pheromone of the ant colony algorithm, finally use the advantages of convergence speed of ant colony algorithm to find the global optimal solution for mobile agent route. Simulation results show that the algorithm can find optimal mobile agent route in a relatively short time, relative to other routing algorithms, reducing network latency and average energy consumption, improving the speed and efficiency of data transfer.

Ant Colony Algorithm Application in Water Treatment Control System Parameter Tuning

2012 ◽  
Vol 433-440 ◽  
pp. 4354-4360
Author(s):  
Shu Qian Chen ◽  
Li Hong Zhang
Keyword(s):  
Control System ◽  
Water Treatment ◽  
Pid Control ◽  
Ant Colony Algorithm ◽  
Thermal Power ◽  
Control Process ◽  
Parameters Optimization ◽  
Ant Colony ◽  
Control Parameters ◽  
Treatment Control

In Thermal Power Generation and heating Water Treatment process, duo to the water supply pipeline pressure and flow changes, the traditional PID control system controller cannot the prompt track response, PH value of water changes in a larger range, increased damage to the boiler pipes. In order to solve the problem which the control parameters optimizes, improves the system performance, proposed a new Ant colony algorithm PID parameters optimization strategy, this solution can combine characteristics that Ant colony algorithm can fast find the most superior parameter solution stably and PID can precise adjustment. In the control process, taken the PID parameters as a colony of ants, used to control the absolute error integral function as the optimization objective, dynamically adjust the PID control parameters in the control process, so as to realize the PID parameters on-line tuning, to improve real-time of the water treatment control system, improved the stability of the system, and achieve a better control effect.

Application Research of Improved Ant Colony Algorithm in Hybrid Mobile Agent Routing

2013 ◽  
Vol 734-737 ◽  
pp. 3093-3097
Author(s):  
Li Hong Zhang ◽  
Shu Qian Chen ◽  
Gui Zhi Bai
Keyword(s):  
Mobile Agent ◽  
Ant Colony Algorithm ◽  
Average Energy ◽  
Optimal Solution ◽  
Residual Energy ◽  
Ant Colony ◽  
Wireless Sensor Node ◽  
Feedback Information ◽  
Low Efficiency ◽  
Improved Ant Colony Algorithm

Mobile agent routing essentially is a multi-constraint optimization problem, for Ant Colony algorithm for global search capability is weak, the feedback information of the system does not use and has the problem of low efficiency of finding exact solutions, propose an improved Ant Colony Algorithm for WSN mobile agent routing. This algorithm takes full use of the wireless sensor node energy, the direction of ants is determined according to the residual energy and the distance of nodes, quickly find the global optimal solution for mobile agent route. Simulation results show that the algorithm can find optimal mobile agent route in a relatively short time, relative to other routing algorithms, reducing network latency and average energy consumption, effectively alleviate network congestion, and extend the network lifetime.

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