A new hybrid evolutionary algorithm based on the Grey wolf optimizer and the bees algorithm is proposed. Embedded hybridization allows combining the strengths of original methods. A comparative analysis of the new hyb...
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A new hybrid evolutionary algorithm based on the Grey wolf optimizer and the bees algorithm is proposed. Embedded hybridization allows combining the strengths of original methods. A comparative analysis of the new hybrid method is performed on benchmark functions. (C) 2019 The Authors. Published by Elsevier B.V.
Mathematical models of metabolic processes are the cornerstone of computational systems biology. In model building, the task of parameter estimation is difficult due to the huge numbers of kinetics parameters involved...
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ISBN:
(纸本)9783319987026;9783319987019
Mathematical models of metabolic processes are the cornerstone of computational systems biology. In model building, the task of parameter estimation is difficult due to the huge numbers of kinetics parameters involved. The common way of estimating the parameters is to formulate it as an optimization problem. Global optimization methods can be applied by minimizing the distance between experimental data and predicted models. This paper proposes the Hybrid of bees algorithm and Harmony Search (BAHS) to estimate the kinetics parameters of essential amino acid production in the aspartate metabolism for Arabidopsis thaliana. The performance of the BAHS is evaluated and compared with other algorithms. The results show that BAHS performed better as it improved the performance of the original BA by 60%. Meanwhile, it takes less computational time to estimate the kinetics parameters of essential amino acid production for Arabidopsis thaliana.
The control of vibration and displacement in structures under seismic excitation is very challenging, and designing a structural control system against disturbances has drawn great attention. This paper concentrates o...
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The control of vibration and displacement in structures under seismic excitation is very challenging, and designing a structural control system against disturbances has drawn great attention. This paper concentrates on implementing the bees algorithm to tune gains of traditional PID controller for active vibration control of a building-like structure with two floors under Northridge Earthquake excitation. bees algorithm is a diverse method to ensure an efficient solution for optimisation of a controller according to customary trial-error design methods. The main aim of this study is optimisation of K-P, K-I and K-D gains with bees algorithm in order to obtain a more effective PID controller to suppress vibrations of the floors during the earthquake excitation. After definition of the system and bees algorithm, PID controller offline tuned with bees algorithm using mathematical model of system. Moreover, the aim is to compare the performances of the BA with an existing optimisation method, genetic algorithm (GA), implemented on the system. The paper presents the experimental results that were obtained from the structure system to show the efficiency of the tuned PID controller. As a result, the performance and effectiveness of the tuned PID controller are investigated and verified experimentally. The displacements and accelerations of the floors and the cart are decreased considerably. The experimental responses of the system are given in graphical form.
A multivariate method based on solvent terminated dispersive liquid-liquid microextraction was developed for the determination of Cu2+ ions in aqueous samples. In the proposed approach, di-2-ethylhexylphosphoric acid,...
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A multivariate method based on solvent terminated dispersive liquid-liquid microextraction was developed for the determination of Cu2+ ions in aqueous samples. In the proposed approach, di-2-ethylhexylphosphoric acid, xylene and acetone were used as chelating agent, dispersive and extraction solvents, respectively. The effects of various factors on the extraction efficiency such as extraction and dispersive solvent volumes, salt addition and pH were studied using central composite design (CCD) and artificial neural networks coupled bees algorithm (ANN-BA). Upon comparison of these techniques, ANN-BA model was considered to be better optimization method due to its higher percentage relative recovery (about 5%) as compared to the CCD approach. The linear range and the limits of detection (S/N = 3) and quantitation (S/N = 10) were 0.22-140, 0.08 and 0.22 A mu g L-1, respectively. Under the optimal conditions, the recoveries for real samples spiked with 0.1 and 0.3 mg L-1 were in the range of 85-98%.
A new hybrid evolutionary algorithm based on the Grey wolf optimizer and the bees algorithm is proposed. Embedded hybridization allows combining the strengths of original methods. A comparative analysis of the new hyb...
详细信息
A new hybrid evolutionary algorithm based on the Grey wolf optimizer and the bees algorithm is proposed. Embedded hybridization allows combining the strengths of original methods. A comparative analysis of the new hybrid method is performed on benchmark functions.
Non-destructive testing methods have gained popularity as they become more widely available. Although there are several techniques that could be used for this purpose, this paper focuses on acoustic emission sensors f...
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Non-destructive testing methods have gained popularity as they become more widely available. Although there are several techniques that could be used for this purpose, this paper focuses on acoustic emission sensors for detecting surface fractures and the use of the bees algorithm, a swarm-based technique, for optimizing the number of sensors required to reliably detect surface fractures. The paper describes the approach that has been used in this study where the dimension of the surface is specified by the user. The results show that, in theory and through simulation, that the bees algorithm is capable of determining the minimum number of sensors needed to locate the surface fracture with an acceptable level of accuracy. The method described could be used for the purpose of optimization in other engineering as well as nonengineering applications. (C) 2017 The Authors. Published by Elsevier B.V.
In this work, the capability of bees-inspired algorithm with the aid of artificial neural networks (ANN-BA) for optimization of acid red 27 dye removal was studied using polypyrrole/SrFe12O19/graphene oxide (GO) as a ...
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In this work, the capability of bees-inspired algorithm with the aid of artificial neural networks (ANN-BA) for optimization of acid red 27 dye removal was studied using polypyrrole/SrFe12O19/graphene oxide (GO) as a novel nanocomposite. The nanocomposite fabricated through in situ polymerization and its characteristics were investigated by means of several instrumental techniques. The prepared polypyrrole/SrFe12O19/GO nanocomposite was employed to adsorb acid red 27 from aqueous solution. Based on the cost function as a nonlinear relation between some factors influencing the adsorption efficiency including adsorbent dosage, initial concentration, pH, shaking rate and contact time with percentage removal which were obtained by a multilayer perceptron artificial neural networks, bees metaheuristic algorithm was utilized to optimize of the batch sorption process. In addition, D-optimal response surface methodology (RSM) was also employed as a comparative study. In comparison with the D-optimal RSM, the ANN-BA model gave higher percentage removal (99%) about 4%. Under optimal conditions obtained by ANN-BA, equilibrium isotherms, kinetic behaviors and thermodynamics of the dye adsorption were thoroughly investigated. The pseudo-second-order model and the Langmuir adsorption model [with maximum capacity (q(max)) of 294.11 mg g(-1)] fitted the experimental results with the determination coefficients (R-2) of 0.94 and 0.99, respectively. The thermodynamic parameters have also been evaluated which showed the sorption procedure was endothermic and spontaneous. The findings obtained from the sorbent usage in wastewater treatment and its regeneration investigation revealed that the nanocomposite can be applied as an effective dye sorbent for removing acid red 27 dye in real samples with a reusable property.
The Interline Power Flow Controller (IPFC) is a series FACTS (Flexible AC Transmission Systems) that has been used fur various applications such as power flow control, automatic generation control, oscillation damping...
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ISBN:
(纸本)9781538636954
The Interline Power Flow Controller (IPFC) is a series FACTS (Flexible AC Transmission Systems) that has been used fur various applications such as power flow control, automatic generation control, oscillation damping, congestion management, power system state estimation and power system protection. The effectiveness of the IPFC varies with position in the power system and so there is motivation to determine the optimal location of the device. Additionally, the optimal location for one application need not necessarily be the optimal location for other applications as well. This study optimally locates the device in order to minimize the power losses in the power system using the bees algorithm. Simulations were run on a 5 bus system in MATLAB. Finally, the results obtained from using the bees algorithm were compared with results obtained using Particle Swarm Optimization.
In a resource-constrained environment project planning and scheduling becomes an extremely complex problem. For real life project schedules multi-mode resource requirements remarkably increase the complexity of and en...
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In a resource-constrained environment project planning and scheduling becomes an extremely complex problem. For real life project schedules multi-mode resource requirements remarkably increase the complexity of and enlarge the respective solution spaces. Therefore schedulers require systematic methodologies compatible with the real world implementations in order to generate cost effective schedules. Similarly, plastic injection molding is known to be a "make-to order" process. The manufacturing of the mold which is a unique and essential component of plastic injection is considered kind of a project. The aim of this study is set to investigate the possibility of utilizing bees algorithm for single-resource, multi-mode, resource-constrained mold project scheduling in order to generate a systematic approach to solve the problems of this nature. A Bee-Based Mold Scheduling Model is therefore proposed and employed on a set of problems with different dimensions for the proof of concept. Detail description of an injection molding project together with respective performance analysis is also provided. After the implementation of the proposed methodology, it is well proven that, even for high number of activities and limited resources, the proposed method generates suitable schedules for the projects of this kind the implementation and respective modelling is explained and the results are discussed in detail within the text. (C) 2017 Elsevier Ltd. All rights reserved.
Non-destructive testing methods have gained popularity as they become more widely available. Although there are several techniques that could be used for this purpose, this paper focuses on acoustic emission sensors f...
详细信息
Non-destructive testing methods have gained popularity as they become more widely available. Although there are several techniques that could be used for this purpose, this paper focuses on acoustic emission sensors for detecting surface fractures and the use of the bees algorithm, a swarm-based technique, for optimizing the number of sensors required to reliably detect surface fractures. The paper describes the approach that has been used in this study where the dimension of the surface is specified by the user. The results show that, in theory and through simulation, that the bees algorithm is capable of determining the minimum number of sensors needed to locate the surface fracture with an acceptable level of accuracy. The method described could be used for the purpose of optimization in other engineering as well as non-engineering applications.
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