Motorcycle-Security using Position Searching Algorithm Based on Hybrid Fuzzy-Dijkstra

Abstract

As we all know, traditional electromagnetism mechanism (EM) algorithm has the disadvantage with low solution precision, lack of mining ability and easily falling into precocity. This paper proposes a new chaos electromagnetism mechanism algorithm combining chaotic mapping with limited storage QuasiNewton Method (EM-CMLSQN). Its main idea is that it adopts limit quasi-Newton Key words: electromagnetism mechanism, limited storage quasi-newton method, limit quasi-newton operator, chaos mapping, particle swarm optimization, discrete artificial bee colony algorithmCopyright © 2016 Institute of Advanced Engineering and Science. All rights reserved. Introduction.Electromagnetism Mechanism (EM) algorithm [1, 2] is a kind of random search methods based on principle of attraction and repulsion between different charged particles in Coulomb law and electromagnetic field. This algorithm firstly establishes the relationship of fitness function value and individual's value affected by electric field, then it is as the population movement trend according to the principle of "excellent solutions attract poor, poor solutions reject the excellent" and puts forward a global stochastic optimization heuristic algorithm [3]. The global stochastic optimization heuristic algorithm has been used in many aspects, such as fault location in distribution networks and pipeline assemble. Nevertheless, the EM algorithm has the shortcoming of premature convergence, low local search accuracy in late and slow convergence rate, which resembles other global intelligent algorithms. To solve these problems, this paper proposes an improved local optimization strategy using high precision local optimization operator and limited storage Quasi-Newton operator [4]. It seeks optimization value for solution domain near optimal individual and adopts chaos mapping [5] to increase the diversity of population. As a mature intelligent algorithm, Particle Swarm Optimization (PSO) algorithm [6,7] has a very good effect on searching the optimization value in continuous domain. There is an improved PSO algorithm named particle swarm optimization with TimeVarying Accelerator Coefficients (TVAC) [8,9], which has a better ability of searching optimization. Therefore, we compare TVAC with our new method (EM-CMLSQN), and the simulation results show that EM-CMLSQN has a better convergence rate and performance of jumping out of local solution than PSO and TVAC method. We also apply EMCMLSQN algorithm into path planning problem, and the results represent that EM-CMLSQN algorithm can search the optimal path more precisely and can be better applied into solving discrete domain problems than genetic algorithm and PSO algorithm [10,11].

Pursuit Algorithm for Robot Trash Can Based on Fuzzy-Cell Decomposition

“…The FCD algorithm was tested in the first experiment in an unknown environment without static obstacles as shown in Figure 8. In Figure 8(A) trash can robots is indicated by a yellow dot with the initial position of (50, 20) and the robot starts moving when viewed trash indicated a by green dot thrown from the position of (10,90) to the position of (20,80). Then the robot moves toward the goal position of the trash and stop at the position of (25,75).…”

“…Then the robot moves toward the goal position of the trash and stop at the position of (25,75). Figure 8(B) shows that the trash can robot remains at the position of (50, 20) and trash indicated by a green dot is in the position of (90, 80). When the trash fell on the position of (80, 80) the robot moves toward the position of the trash.…”

“…In this study, the trash can robot is controlled by reference values of grid distance obtained from fuzzy algorithm. Fuzzy is an artificial intelligence algorithm [19][20][21][22] found by Zadeh that has been used by several researchers to control quadrotor as practiced by Nia Maharani et al [23][24] to control the quadrotor altitude and Mohammad Reza Rahimi et al [25] to control the altitude on the fixed wing UAV type. This algorithm has been widely studied by previous researchers as conducted by Wen et al, [26] using fuzzy algorithm for UAV path planning to fly in dangerous environments at low altitude.…”

Uninterruptable Power Supply based on Switching Regulator and Modified Sine Wave

“…The control uses fuzzy algorithm control invented by zadeh that has been used for path planning decision making [13][14][15] and is used to control quadrotor [16][17][18]. Below is the flow chart of a program that will be loaded into the microcontroller.…”

Microcontroller-based RFID, GSM and GPS for Motorcycle Security System

“…All systems are regulated by a single component, namely Microcontroller [12], [20], [21]. The controller of the systems is Radio Frequency Identification (RFID).…”