Chaotic binary bat algorithm for analog test point selection

Zhao, Dongsheng; He, Yuzhu

doi:10.1007/s10470-015-0548-5

Cited by 30 publications

(8 citation statements)

References 27 publications

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“…BA has been applied in the multiobjective function optimization with the artificial neural network model [11], economic operation [6], and economic load dispatch in wind power generation system [12]. BBA has been applied in the simulation test point selection [13], low speed rolling bearing fault [14], and the optimization of the echo state network [15].…”

Section: Introductionmentioning

confidence: 99%

Optimized Parameter Settings of Binary Bat Algorithm for Solving Function Optimization Problems

Wang

2018

Journal of Electrical and Computer Engineering

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The bat algorithm (BA) is a new bionic intelligent optimization algorithm to simulate the foraging behavior and the echolocation principle of the bats. The parameter initialization of the discussed binary bat algorithm (BBA) has important influence on the convergence speed, convergence precision, and good global searching ability of the BBA. The convergence speed and algorithm searching precision are determined by the pulse of loudness and pulse rate. The simulation experiments are carried out by using the six typical test functions to discuss this influence. The simulation results show that the convergence speed of the BBA is relatively sensitive to the setting of the algorithm parameters. The convergence precision reduces when increasing the rate of bat transmitted pulse alone and the convergence speed increases the launch loudness alone. The proper combination of BBA parameters (the rate of bat transmitted pulse and the launch loudness) can flexibly improve the algorithm's convergence velocity and improve the accuracy of the searched solutions.

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Section: Introductionmentioning

confidence: 99%

Optimized Parameter Settings of Binary Bat Algorithm for Solving Function Optimization Problems

Wang

2018

Journal of Electrical and Computer Engineering

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“…Step 5 Update velocities v t and locations x t according to updating rule of the standard BA algorithm, Equations (8)- (10); if (β > r i ), select a local solution x t+1 around selected best solution as Equation (11); assign the function value F new to fitness x t+1 .…”

Section: Compact Bat Algorithmmentioning

confidence: 99%

“…This BBA has been used in several tasks, e.g., it was adopted 2 of 18 in [9] as the feature selection part of a fault diagnosis scheme for failures of incipient low-speed rolling element bearings. As another example, a chaotic version of the algorithm, namely CBBA, was used to select points in an analog circuit diagnosis system [10]. A similar BBA algorithm, with a multi V-shaped version of the transfer function, was adopted in order to solve a large scale 0-1 knapsack problem [11].…”

Section: Introductionmentioning

confidence: 99%

A Compact Bat Algorithm for Unequal Clustering in Wireless Sensor Networks

2019

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Everyday, a large number of complex scientific and industrial problems involve finding an optimal solution in a large solution space. A challenging task for several optimizations is not only the combinatorial operation but also the constraints of available devices. This paper proposes a novel optimization algorithm, namely the compact bat algorithm (cBA), to use for the class of optimization problems involving devices which have limited hardware resources. A real-valued prototype vector is used for the probabilistic operations to generate each candidate for the solution of the optimization of the cBA. The proposed cBA is extensively evaluated on several continuous multimodal functions as well as the unequal clustering of wireless sensor network (uWSN) problems. Experimental results demonstrate that the proposed algorithm achieves an effective way to use limited memory devices and provides competitive results.

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“…In this paper, a logistic map [20] is introduced as a typical chaotic sequence to fulfill the requirements of CGS.…”

Section: Chaotic Global Search (Cgs)mentioning

confidence: 99%

“…Chaos theory, which can provide a powerful global search tool, is usually used to improve the global search ability of swarm intelligence algorithms [18][19][20]. The ergodicity of the chaotic mechanism can make the individuals travel through all positions in the whole space to the greatest extent possible.…”

Section: Introductionmentioning

confidence: 99%

A novel hybrid approach based on a chaotic cloud gravitational search algorithm to complicated image template matching

Cui¹,

He²

2017

Turk J Elec Eng & Comp Sci

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Abstract:Template matching is the process of accurately extracting the interesting regions in a source image according to reference templates. In this paper, the gravitational search algorithm (GSA) is employed as a novel search strategy for template matching. However, the basic GSA is easily trapped in a local optimum and has a poor exploitation ability.In this paper, to enhance the optimization performance of GSA, a novel cross-search strategy based on chaotic global search (CGS) and cloud local search (CLS) is incorporated into GSA. The new variant is named chaotic cloud GSA (CCGSA). CGS makes full use of the ergodicity of chaos theory to improve global search ability and to avoid premature convergence. Inspired by the randomness and stable tendency of the normal cloud model, CLS was formed to realize a refined exploitation in the neighborhood of the current best solution; therefore, it can enhance optimization efficiency.Comparative experiments on six composite benchmark functions indicate that CCGSA convergence performance is superior to that of two advanced variants of GSA. Moreover, when applied to template matching, CCGSA performs better than the other selected intelligent optimization algorithms.

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Chaotic binary bat algorithm for analog test point selection

Cited by 30 publications

References 27 publications

Optimized Parameter Settings of Binary Bat Algorithm for Solving Function Optimization Problems

Optimized Parameter Settings of Binary Bat Algorithm for Solving Function Optimization Problems

A Compact Bat Algorithm for Unequal Clustering in Wireless Sensor Networks

A novel hybrid approach based on a chaotic cloud gravitational search algorithm to complicated image template matching

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