scholarly journals Jammer Localization in Multihop Wireless Networks Based on Gravitational Search

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Tongxiang Wang ◽  
Xianglin Wei ◽  
Jianhua Fan ◽  
Tao Liang
Keyword(s):  
Wireless Networks ◽  
Search Algorithm ◽  
Fitness Function ◽  
Gravitational Search Algorithm ◽  
Multihop Wireless Networks ◽  
Wireless Channel ◽  
Localization Algorithm ◽  
Multihop Wireless ◽  
Gravitational Search ◽  
Range Free

Multihop Wireless Networks (MHWNs) can be easily attacked by the jammer for their shared nature and open access to the wireless medium. The jamming attack may prevent the normal communication through occupying the same wireless channel of legal nodes. It is critical to locate the jammer accurately, which may provide necessary message for the implementation of antijamming mechanisms. However, current range-free methods are sensitive to the distribution of nodes and parameters of the jammer. In order to improve the localization accuracy, this article proposes a jammer localization method based on Gravitational Search Algorithm (GSA), which is a heuristic optimization evolutionary algorithm based on Newton’s law of universal gravitation and mass interactions. At first, the initial particles are selected randomly from the jammed area. Then, the fitness function is designed based on range-free method. At each iteration, the mass and position of the particles are updated. Finally, the position of particle with the maximum mass is considered as the estimated jammer’s position. A series of simulations are conducted to evaluate our proposed algorithms and the simulation results show that the GSA-based localization algorithm outperforms many state-of-the-art algorithms.

Automatic Mining of Quantitative Association Rules with Gravitational Search Algorithm

2017 ◽  
Vol 27 (03) ◽  
pp. 343-372 ◽  
Author(s):  
Umit Can ◽  
Bilal Alatas
Keyword(s):  
Association Rules ◽  
Optimization Problems ◽  
Search Algorithm ◽  
Fitness Function ◽  
Optimization Algorithms ◽  
Gravitational Search Algorithm ◽  
Search Space ◽  
Search Method ◽  
Quantitative Association Rules ◽  
Gravitational Search

The classical optimization algorithms are not efficient in solving complex search and optimization problems. Thus, some heuristic optimization algorithms have been proposed. In this paper, exploration of association rules within numerical databases with Gravitational Search Algorithm (GSA) has been firstly performed. GSA has been designed as search method for quantitative association rules from the databases which can be regarded as search space. Furthermore, determining the minimum values of confidence and support for every database which is a hard job has been eliminated by GSA. Apart from this, the fitness function used for GSA is very flexible. According to the interested problem, some parameters can be removed from or added to the fitness function. The range values of the attributes have been automatically adjusted during the time of mining of the rules. That is why there is not any requirements for the pre-processing of the data. Attributes interaction problem has also been eliminated with the designed GSA. GSA has been tested with four real databases and promising results have been obtained. GSA seems an effective search method for complex numerical sequential patterns mining, numerical classification rules mining, and clustering rules mining tasks of data mining.

OPTIMAL TIMAH TASOH RESERVOIR IN, PERLIS: AN OPERATION USING THE GRAVITATIONAL SEARCH ALGORITHM (GSA)

2015 ◽  
Vol 77 (30) ◽  
Author(s):  
Asmadi Ahmad ◽  
Siti Fatin Mohd Razali ◽  
Ahmed El-Shafie ◽  
Zawawi Samba Mohamad
Keyword(s):  
Search Algorithm ◽  
Fitness Function ◽  
Gravitational Search Algorithm ◽  
Inertial Mass ◽  
Storage Condition ◽  
Sustainable Engineering ◽  
Release Policy ◽  
Gravitational Search ◽  
The Times ◽  
Law Of Gravity

The construction of a dam or a reservoir can have a serious impact the environment. When dealing with the increasing water demand from irrigation and water supply, alternative solution has to be sought way rather than building a new dam. Therefore, reservoir optimization can be employed as a new approach in sustainable engineering to solve this kind of problem. In this paper an optimization algorithm based on the Newton law of gravity, which is called Gravitational Search Algorithm (GSA), is introduced for optimal reservoir operation study. In GSA, every mass has four specifications, which are position, inertial mass, active gravitational mass, and passive gravitational.  The location of the mass is the solution of the problem, with the gravitational and inertial masses being determined by using a fitness function. Furthermore, The algorithm was applied to the Timah Tasoh reservoir and the release policy was tested by using simulation of demand and release. The result revealed that 72% of the times the reservoir managed to fulfill the demand to the users. Moreover, with the new optimized release policy, the dam operator can manage the reservoir release for the users by determining the inflow pattern, as well as by and observing the current storage condition as a guideline

scholarly journals Optimal backstepping control of quadrotor UAV using gravitational search optimization algorithm

2020 ◽  
Vol 9 (5) ◽  
pp. 1819-1826
Author(s):  
M. A. Basri ◽  
A. Noordin
Keyword(s):  
High Performance ◽  
Search Algorithm ◽  
Fitness Function ◽  
Gravitational Search Algorithm ◽  
Absolute Error ◽  
Difficult Problem ◽  
Quadrotor Uav ◽  
Search Optimization ◽  
Backstepping Controller ◽  
Gravitational Search

Quadrotor unmanned aerial vehicle (UAV) has superior characteristics such as ability to take off and land vertically, to hover in a stable air condition and to perform fast maneuvers. However, developing a high-performance quadrotor UAV controller is a difficult problem as quadrotor is an unstable and underactuated nonlinear system. The effort in this article focuses on designing and optimizing an autonomous quadrotor UAV controller. First, the aerial vehicle's dynamic model is presented. Then it is suggested an optimal backstepping controller (OBC). Traditionally, backstepping controller (BC) parameters are often selected arbitrarily. The gravitational search algorithm (GSA) is used here to determine the BC parameter optimum values. In the algorithm, the control parameters are calculated using an integral absolute error to minimize the fitness function. As the control law is based on the theorem of Lyapunov, the asymptotic stability of the scheme can be ensured. Finally, several simulation studies are conducted to show the efficacy of the suggested OBC.

Case-based reasoning adaptation based on fuzzy gravitational search algorithm for disaster emergency plan

2021 ◽  
pp. 1-16
Author(s):  
Xiaobing Yu ◽  
Xianrui Yu ◽  
Xueying Zhang
Keyword(s):  
Search Algorithm ◽  
Fitness Function ◽  
Gravitational Search Algorithm ◽  
Integrated System ◽  
Case Based Reasoning ◽  
Emergency Plan ◽  
Gas Leakage ◽  
Comparison Results ◽  
Gravitational Search ◽  
Case Based

Disasters can result in substantial destructive damages to the world. Emergency plan is vital to deal with these disasters. It is still difficult for the traditional CBR to generate emergency plans to meet requirements of rapid responses. An integrated system including Case-based reasoning (CBR) and gravitational search algorithm (GSA) is proposed to generate the disaster emergency plan. Fuzzy GSA (FGSA) is developed to enhance the convergence ability and accomplish the case adaptation in CBR. The proposed algorithm dynamically updates the main parameters of GSA by introducing a fuzzy system. The FGSA-CBR system is proposed, in which fitness function is defined based on the effectiveness of disaster emergency management. The comparison results have revealed that the proposed algorithm has good performances compared with the original GSA and other algorithms. A gas leakage accident is taken as an empirical study. The results have demonstrated that the FGSA-CBR has good performances when generating the disaster emergency plan. The combination of CBR and FGSA can realize the case adaptation, which provides a useful approach to the real applications.

scholarly journals Optimum PID controller for airplane wing tires based on gravitational search algorithm

2021 ◽  
Vol 10 (4) ◽  
pp. 1905-1913
Author(s):  
Ammar Hussein Mutlag ◽  
Omar Nameer Mohammed Salim ◽  
Siraj Qays Mahdi
Keyword(s):  
Pid Controller ◽  
Transfer Functions ◽  
Search Algorithm ◽  
Fitness Function ◽  
Gravitational Search Algorithm ◽  
Harmony Search ◽  
Absolute Error ◽  
Airplane Wing ◽  
Gravitational Search ◽  
Opening And Closing

In this paper, the gravitational search algorithm (GSA) is proposed as a method for controlling the opening and closing of airplane wing tires. The GSA is used to find the optimum proportional-integral-derivative (PID) controller, which controls the wing tires during take-off and landing. In addition, the GSA is suggested as an approach for overcoming the absence of the transfer function, which is usually required to design the optimum PID. The use of the GSA is expected to improve the system. Two of the most popular optimisation algorithms-the harmony search algorithm (HSA) and the particle swarm optimisation (PSO)-were used for the sake of comparison. Moreover, the GSA-, HSA- and PSO-based optimum PID controllers were compared with one of the most important PID tuning methods, the Ziegler-Nichols (ZN) method. In this study, the integral time absolute error (ITAE) was used as a fitness function. First, four transfer functions for different applications were used to compare the performance of the GSA-based PID (PID-GSA), HSA-based PID (PID-HSA), PSO-based PID (PID-PSO) and Ziegler-Nichols-based PID (PID-ZN). Next, the GSA was used to design the optimum PID controller for the opening and closing systems of the airplane wing tires. The results reveal that the GSA provides better outcomes in terms of ITAE when compared with the other adopted algorithms. Furthermore, the GSA demonstrates a fast and robust response to reference variation.

Analysis of Optimal Power Flow Using Gravitational Search Algorithm

2016 ◽  
Vol 3 (4) ◽  
pp. 1-11
Author(s):  
M. Lakshmikantha Reddy ◽  
◽  
M. Ramprasad Reddy ◽  
V.C. Veera Reddy ◽  
◽  
...  
Keyword(s):  
Power Flow ◽  
Optimal Power Flow ◽  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Optimal Power ◽  
Gravitational Search
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