scholarly journals Node Depth Adjustment Based Target Tracking in UWSNs Using Improved Harmony Search

Sensors ◽  
2017 ◽  
Vol 17 (12) ◽  
pp. 2807 ◽  
Author(s):  
Meiqin Liu ◽  
Duo Zhang ◽  
Senlin Zhang ◽  
Qunfei Zhang
2017 ◽  
Vol 2017 ◽  
pp. 1-17 ◽  
Author(s):  
Yi-zhe Chang ◽  
Zhan-wu Li ◽  
Ying-xin Kou ◽  
Qing-peng Sun ◽  
Hai-yan Yang ◽  
...  

A new approach to solving weapon-target assignment (WTA) problem is proposed in this paper. Firstly, relative superiority that lays the foundation for assignment is calculated based on the combat power energy of the fighters. Based on the relative superiority, WTA problem is formulated. Afterwards, a hybrid algorithm consisting of improved artificial fish swarm algorithm (AFSA) and improved harmony search (HS) is introduced and furthermore applied to solve the assignment formulation. Finally, the proposed approach is validated by eight representative benchmark functions and two concrete cooperative air combat examples. The results show that the approach proposed in this paper achieves good performances in solving WTA problem in cooperative air combat.


2018 ◽  
Vol 7 (2.14) ◽  
pp. 177
Author(s):  
Mustafa Raad Hammoodi ◽  
Ravie Chandren Muniyand

Vehicle Ad-hoc Network (VANET) is a direct application of Mobile Ad-hoc Network (MANET). Nodes in VANET are vehicles that communicate using vehicle to vehicle (V2V) or vehicle to infrastructure (V2I). These types of communications have led to the emergence of various applications that provide safer driving. Due to the high changing of topology and frequent fragmentation of VANET, routing pack-ets in this type of network is a hard task. In this work, the authors deal with the well-known MANET proactive Optimized Link State Rout-ing protocol (OLSR). The deployment of OLSR in VANET gives the moderate performance; this is due to its necessity of constant ex-changing of control packets. The performance of OLSR is highly dependent on its parameters, thus finding optimal parameters configura-tions that best fit VANETs environment and improves the network is essential before its deployment. Therefore, this research proposes a modified Harmony Search optimization (HSO) by incorporating selection methods in its memory consideration; roulette wheel selection to obtain fine-tuned OLSR for high density and velocity scenario. The experimental analysis showed that the OLSR with the proposed ap-proach acquired promising results regarding packet delivery ratio, end-to-end delay and overhead when compared with previous approaches.  


Author(s):  
Erwin Erwin ◽  
Saparudin Saparudin ◽  
Wulandari Saputri

This paper proposes a new method for image segmentation is hybrid multilevel thresholding and improved harmony search algorithm. Improved harmony search algorithm which is a method for finding vector solutions by increasing its accuracy. The proposed method looks for a random candidate solution, then its quality is evaluated through the Otsu objective function. Furthermore, the operator continues to evolve the solution candidate circuit until the optimal solution is found. The dataset used in this study is the retina dataset, tongue, lenna, baboon, and cameraman. The experimental results show that this method produces the high performance as seen from peak signal-to-noise ratio analysis (PNSR). The PNSR result for retinal image averaged 40.342 dB while for the average tongue image 35.340 dB. For lenna, baboon and cameramen produce an average of 33.781 dB, 33.499 dB, and 34.869 dB. Furthermore, the process of object recognition and identification is expected to use this method to produce a high degree of accuracy.


Symmetry ◽  
2018 ◽  
Vol 10 (8) ◽  
pp. 337 ◽  
Author(s):  
Chui-Yu Chiu ◽  
Po-Chou Shih ◽  
Xuechao Li

A novel global harmony search (NGHS) algorithm, as proposed in 2010, is an improved algorithm that combines the harmony search (HS), particle swarm optimization (PSO), and a genetic algorithm (GA). Moreover, the fixed parameter of mutation probability was used in the NGHS algorithm. However, appropriate parameters can enhance the searching ability of a metaheuristic algorithm, and their importance has been described in many studies. Inspired by the adjustment strategy of the improved harmony search (IHS) algorithm, a dynamic adjusting novel global harmony search (DANGHS) algorithm, which combines NGHS and dynamic adjustment strategies for genetic mutation probability, is introduced in this paper. Moreover, extensive computational experiments and comparisons are carried out for 14 benchmark continuous optimization problems. The results show that the proposed DANGHS algorithm has better performance in comparison with other HS algorithms in most problems. In addition, the proposed algorithm is more efficient than previous methods. Finally, different strategies are suitable for different situations. Among these strategies, the most interesting and exciting strategy is the periodic dynamic adjustment strategy. For a specific problem, the periodic dynamic adjustment strategy could have better performance in comparison with other decreasing or increasing strategies. These results inspire us to further investigate this kind of periodic dynamic adjustment strategy in future experiments.


2009 ◽  
Vol 95 (4) ◽  
pp. 401-426 ◽  
Author(s):  
Prithwish Chakraborty, ◽  
Gourab Ghosh Roy ◽  
Swagatam Das ◽  
Dhaval Jain ◽  
Ajith Abraham

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