Analysis of service satisfaction in web auction logistics service using a combination of Fruit fly optimization algorithm and general regression neural network

Lin, Song

doi:10.1007/s00521-011-0769-1

Cited by 135 publications

(57 citation statements)

References 12 publications

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“…In [21], FOA was adopted to optimize general regression neural network, and the simulation result showed the superiority compared with other intelligent optimization algorithms. In [29], an annual electric load forecasting method was proposed by the least squares support vector machine (LSSVM) model.…”

Section: Fruit Fly Optimization Algorithmmentioning

confidence: 99%

Adaptive Wavelet Threshold Denoising Method for Machinery Sound Based on Improved Fruit Fly Optimization Algorithm

Wang

Tan

et al. 2016

Applied Sciences

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Abstract:As the sound signal of a machine contains abundant information and is easy to measure, acoustic-based monitoring or diagnosis systems exhibit obvious superiority, especially in some extreme conditions. However, the sound directly collected from industrial field is always polluted. In order to eliminate noise components from machinery sound, a wavelet threshold denoising method optimized by an improved fruit fly optimization algorithm (WTD-IFOA) is proposed in this paper. The sound is firstly decomposed by wavelet transform (WT) to obtain coefficients of each level. As the wavelet threshold functions proposed by Donoho were discontinuous, many modified functions with continuous first and second order derivative were presented to realize adaptively denoising. However, the function-based denoising process is time-consuming and it is difficult to find optimal thresholds. To overcome these problems, fruit fly optimization algorithm (FOA) was introduced to the process. Moreover, to avoid falling into local extremes, an improved fly distance range obeying normal distribution was proposed on the basis of original FOA. Then, sound signal of a motor was recorded in a soundproof laboratory, and Gauss white noise was added into the signal. The simulation results illustrated the effectiveness and superiority of the proposed approach by a comprehensive comparison among five typical methods. Finally, an industrial application on a shearer in coal mining working face was performed to demonstrate the practical effect.

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Section: Fruit Fly Optimization Algorithmmentioning

confidence: 99%

Adaptive Wavelet Threshold Denoising Method for Machinery Sound Based on Improved Fruit Fly Optimization Algorithm

Wang

Tan

et al. 2016

Applied Sciences

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“…To the fly, attractiveness is not necessarily profitable; (4) while foraging or mating, the fly also sends and receives messages with its friends about its food and their mates. The original FOA in [17,[20][21][22][23] can be divided into several necessary steps and the main steps are described as follows:…”

Section: Original Foa Techniquementioning

confidence: 99%

“…The main inspiration of FOA is that the fruit fly itself is superior to other species in sensing and perception, especially in osphresis and vision [18,19]. Since FOA is simple and elegant in concept, easy to implement and has few parameters, it has been applied in many areas [20][21][22][23][24]. In order to improve the exploration and exploitation ability, several kinds of improved FOA were proposed in [24][25][26][27].…”

mentioning

confidence: 99%

Parameter identification of BIPT system using chaotic-enhanced fruit fly optimization algorithm

Yuan

Liu

Xiang

et al. 2015

Applied Mathematics and Computation

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(2015) Parameter identification of BIPT system using chaotic-enhanced fruit fly optimization algorithm. Applied Mathematics and Computation, 268 . pp. 1267-1281 Bidirectional inductive power transfer (BIPT) system facilitates contactless power transfer between two sides and across an air-gap, through weak magnetic coupling. Typically, this system is nonlinear high order system which includes nonlinear switch components and resonant networks, developing of accurate model is a challenging task. In this paper, a novel technique for parameter identification of a BIPT system is presented by using chaotic-enhanced fruit fly optimization algorithm (CFOA). The fruit fly optimization algorithm (FOA) is a new metaheuristic technique based on the swarm behavior of the fruit fly. This paper proposes a novel CFOA, which employs chaotic sequence to enhance the global optimization capacity of original FOA. The parameter identification of the BIPT system is formalized as a multi-dimensional optimization problem, and an objective function is established minimizing the errors between the estimated and measured values. All the 11 parameters of this system (L pi , L T , L si , L so , C T , C s , M, R pi , R T , R si and R so ) can be identified simultaneously using measured input-output data. Simulations show that the proposed parameter identification technique is robust to measurements noise and variation of operation condition and thus it is suitable for practical application.

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“…Compared with other existed swarm intelligence methods, FOA has some attractive characteristics including few parameters to adjusted, simple computation process, ease to understand and implement, and good convergence. Owing to these merits, the FOA has been successfully applied to tackling some academic and engineering optimization problems and becomes a competitive optimizer [8,9,10].…”

Section: Introductionmentioning

confidence: 99%

A Novel Discrete Fruit Fly Optimization Algorithm for Intelligent Parallel Test sheets Generation

Wang

Dong

et al. 2015

MATEC Web of Conferences

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Analysis of service satisfaction in web auction logistics service using a combination of Fruit fly optimization algorithm and general regression neural network

Cited by 135 publications

References 12 publications

Adaptive Wavelet Threshold Denoising Method for Machinery Sound Based on Improved Fruit Fly Optimization Algorithm

Adaptive Wavelet Threshold Denoising Method for Machinery Sound Based on Improved Fruit Fly Optimization Algorithm

Parameter identification of BIPT system using chaotic-enhanced fruit fly optimization algorithm

A Novel Discrete Fruit Fly Optimization Algorithm for Intelligent Parallel Test sheets Generation

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