scholarly journals Coverage Strategy for Target Location in Marine Environments Using Fixed-Wing UAVs

Drones ◽  
2021 ◽  
Vol 5 (4) ◽  
pp. 120
Author(s):  
Javier Muñoz ◽  
Blanca López ◽  
Fernando Quevedo ◽  
Concepción A. Monje ◽  
Santiago Garrido ◽  
...  
Keyword(s):  
Differential Evolution ◽  
Target Location ◽  
Differential Evolution Algorithm ◽  
Maximum Probability ◽  
Sweep Angle ◽  
Data Set ◽  
Probabilistic Distribution ◽  
Sweep Direction ◽  
Gaussian Probability Distribution ◽  
Evolution Algorithm

In this paper, we propose a coverage method for the search of lost target or debris on the ocean surface. The OSCAR data set is used to determine the marine currents and the differential evolution genetic filter is used to optimize the sweep direction of the lawnmower coverage and get the sweep angle for the maximum probability of containment. The position of the target is determined by a particle filter, where the particles are moved by the ocean currents and the final probabilistic distribution is obtained by fitting the particle positions to a Gaussian probability distribution. The differential evolution algorithm is then used to optimize the sweep direction that covers the highest probability of containment cells before the less probable ones. The algorithm is tested with a variety of parameters of the differential evolution algorithm and compared to other popular optimization algorithms.

The Research on Fuzzy Clustering Method Based on Differential Evolution Algorithm in Intrusion Detection

2014 ◽  
Vol 651-653 ◽  
pp. 547-550
Author(s):  
Qi Fan Yang ◽  
Li Na Wang
Keyword(s):  
Intrusion Detection ◽  
Differential Evolution ◽  
Clustering Algorithm ◽  
Differential Evolution Algorithm ◽  
High Detection Rate ◽  
Data Set ◽  
Fuzzy Clustering Method ◽  
Fuzzy C Means Clustering ◽  
Evolution Algorithm ◽  
Final Answer

Fuzzy C-means clustering algorithm (FCM) is widely applied to the intrusion detection. To acquire a better division for intrusion data, a new method (DEFCM) presented in the paper which combines FCM and differential evolution algorithm (DE) is found application. As a start, several randomly initiated partitions are optimized by FCM, and then the result is provided to differential evolution algorithm. After that, the combined result is sent to FCM again to adjust the partition and obtain the final answer. The method can improve detection performance effectively. The KDDCUP1999 data set is used in the simulation experiment, and the result proves that the DEFCM algorithm has a comparatively high detection rate in intrusion detection.

Modified differential evolution algorithm for semi-supervised fuzzy clustering

2009 ◽  
Vol 29 (4) ◽  
pp. 1046-1047
Author(s):  
Song-shun ZHANG ◽  
Chao-feng LI ◽  
Xiao-jun WU ◽  
Cui-fang GAO
Keyword(s):  
Differential Evolution ◽  
Fuzzy Clustering ◽  
Differential Evolution Algorithm ◽  
Evolution Algorithm

Parameter Estimation By Using An Improved Bee Memory Differential Evolution Algorithm (Ibmde) To Simulate Biochemical Pathways

2013 ◽  
Vol 8 (999) ◽  
pp. 1-6
Author(s):  
Chuii Khim Chong ◽  
Mohd Saberi Mohamad ◽  
Safaai Deris ◽  
Mohd Shahir Shamsir ◽  
Lian En Chai ◽  
...  
Keyword(s):  
Parameter Estimation ◽  
Differential Evolution ◽  
Differential Evolution Algorithm ◽  
Biochemical Pathways ◽  
Evolution Algorithm

The Economic Dispatch of Wind Integrated Power System based on an Improved Differential Evolution Algorithm

2020 ◽  
Vol 13 (3) ◽  
pp. 384-395
Author(s):  
Haiqing Liu ◽  
Jinmeng Qu ◽  
Yuancheng Li
Keyword(s):  
Differential Evolution ◽  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Economic Dispatch ◽  
Differential Evolution Algorithm ◽  
Bee Colony ◽  
Evolution Algorithm ◽  
Improved Differential Evolution Algorithm ◽  
Dynamic Economic Dispatch ◽  
Integrated Power System

Background: As more and more renewable energy such as wind energy is connected to the power grid, the static economic dispatch in the past cannot meet its needs, so the dynamic economic dispatch of the power grid is imperative. Methods: Hence, in this paper, we proposed an Improved Differential Evolution algorithm (IDE) based on Differential Evolution algorithm (DE) and Artificial Bee Colony algorithm (ABC). Firstly, establish the dynamic economic dispatch model of wind integrated power system, in which we consider the power balance constraints as well as the generation limits of thermal units and wind farm. The minimum power generation costs are taken as the objectives of the model and the wind speed is considered to obey the Weibull distribution. After sampling from the probability distribution, the wind speed sample is converted into wind power. Secondly, we proposed the IDE algorithm which adds the local search and global search thoughts of ABC algorithm. The algorithm provides more local search opportunities for individuals with better evolution performance according to the thought of artificial bee colony algorithm to reduce the population size and improve the search performance. Results: Finally, simulations are performed by the IEEE-30 bus example containing 6 generations. By comparing the IDE with the other optimization model like ABC, DE, Particle Swarm Optimization (PSO), the experimental results show that obtained optimal objective function value and power loss are smaller than the other algorithms while the time-consuming difference is minor. The validity of the proposed method and model is also demonstrated. Conclusion: The validity of the proposed method and the proposed dispatch model is also demonstrated. The paper also provides a reference for economic dispatch integrated with wind power at the same time.

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