In the paper a concept of creating a filtering network based on filtering sockets is presented. The basic parallel and serial structures was described. Shaping frequency response was achieved by minimizing the cost fu...
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In the paper a concept of creating a filtering network based on filtering sockets is presented. The basic parallel and serial structures was described. Shaping frequency response was achieved by minimizing the cost function using firefly algorithm. Replacing gain coefficient k and time constant T with gain function and time function reduced the duration of the transition processes. The results are presented and compared with the stationary counterpart.
Gene regulatory network(GRN) inference from gene expression data remains a big challenge in system biology. In this paper, flexible neural tree(FNT) model is proposed as a binary classifier for inference of gene regul...
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Gene regulatory network(GRN) inference from gene expression data remains a big challenge in system biology. In this paper, flexible neural tree(FNT) model is proposed as a binary classifier for inference of gene regulatory network. A novel tree-based evolutionary algorithm and firefly algorithm(FA) are used to optimize the structure and parameters of FNT model, respectively. The two *** networks are used to test FNT model and the results reveal that FNT model performs better than state-of-the-art unsupervised and supervised learning methods.
Different from changeable chromosome length genetic algorithm,a new method based on firefly optimization algorithm is put forward to search a train’s energy saving operation strategy under running disturbance conditi...
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Different from changeable chromosome length genetic algorithm,a new method based on firefly optimization algorithm is put forward to search a train’s energy saving operation strategy under running disturbance condition in railway network. The algorithm is designed and validated using a referenced simulation case. Compared with other methods,it demonstrates this new FA-based algorithm has a better result in computation efficiency and may be considered to use in other energy efficient train operation models.
This paper presents a pattern synthesis method based on two powerful tools of the Evolutionary computing i.e Differential Evolution, Invasive weed optimization and firefly technique, to provide a significant side lobe...
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ISBN:
(纸本)9781479922765
This paper presents a pattern synthesis method based on two powerful tools of the Evolutionary computing i.e Differential Evolution, Invasive weed optimization and firefly technique, to provide a significant side lobe reduction. The Antenna elements are embedded on a hemispherical array that leads to one of the geometry of a conformal shape. The array elements are excited with uniform amplitude excitation and progressively phased. The calculation of the element position is presented. The hemispherical array geometry is designed to meet multi objective criteria such as to achieve the desired side lobe reduction, null point detection and main beam enhancement. The exploitative changes of the Invasive Weed Optimization, Differential Evolution and firefly algorithms have been applied for this array pattern synthesis. Simulation results of the conformal array design have been presented to illustrate the effectiveness and robustness of the Weed technique on the Differential Evolution and firefly algorithm . Empirical results clearly demonstrate the ability of IWO outperforming its competitors. By this method, arrays have the ability to produce the desired radiation pattern and could satisfy requirements for many applications.
Software Testing is the most time consuming activity in the software development lifecycle. It is impossible to test everything. Hence, several automated test data generation techniques have been introduced in recent ...
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ISBN:
(纸本)9781509014903
Software Testing is the most time consuming activity in the software development lifecycle. It is impossible to test everything. Hence, several automated test data generation techniques have been introduced in recent times in order to reduce the effort spent during testing. Search based techniques have been found to be more efficient than normal or random testing. In this paper, we propose to demonstrate the designing framework, implementation and explore the capabilities of a tool to aid in the generation of test data. Our tool is based on generating the optimal set of test cases based on the user defined coverage criteria. We have implemented the system in C++ language and have restricted ourselves to the use of command line interface. We provide the path as well as the test cases generated to the tester making his work of testing a lot easier.
＜正＞People have learnt from biological system behaviours and structures to design and develop a number of different kinds of optimisation algorithms that have been widely used in both theoretical study and practical...
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＜正＞People have learnt from biological system behaviours and structures to design and develop a number of different kinds of optimisation algorithms that have been widely used in both theoretical study and practical applications in engineering and business *** efficient supply chain is very important for companies to survive in global competitive ***
This paper is aimed at conducting technical and economical analysis of hybrid PV-Biomass micro-grid, which to electrify a remote apple farm located in Albaha region, KSA. To accomplish this goal, the system components...
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This paper is aimed at conducting technical and economical analysis of hybrid PV-Biomass micro-grid, which to electrify a remote apple farm located in Albaha region, KSA. To accomplish this goal, the system components are simulated, modelled and sizing. The objective function is formulated based on the Total Annual Cost (TAC). Two selected optimization methods are applied to achieve the optimum number of the PV panels and the biomass engine-generator set with the least Net Present Cost (NPC). The optimization algorithms are the Harmony Search (HS) and the firefly algorithm (FA). The Loss of Power Supply Probability (LPSP) is utilized to improve the performance of the proposed system. The final consequences of the optimal system display that it contains 25 PV modules, 2 biomass generators and 98 Nickel Iron (Ni-Fe) batteries at LPSP of 2% and lower NPC.
This paper considers the optimal distribution of wireless mesh network with reference to connectivity and *** very intensive problem of finding the Optimal Router Node Placement(RNP) problem addressed with firefly opt...
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This paper considers the optimal distribution of wireless mesh network with reference to connectivity and *** very intensive problem of finding the Optimal Router Node Placement(RNP) problem addressed with firefly optimization *** there are many Contemporary work with same optimization the proposed algorithm concentrates on the optimization of objective function in terms of Client Coverage and the Network *** generation of the seeds randomly uses the gradient decent *** obtained results demonstrate the effectiveness of our proposed approach when compared to the existing genetic algorithm.
in the studying process of fault prediction method during operating numerical control(NC) machine tool, using the current algorithm to predict fault in the running process of the NCmachine tool, iteration is easy to f...
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in the studying process of fault prediction method during operating numerical control(NC) machine tool, using the current algorithm to predict fault in the running process of the NCmachine tool, iteration is easy to fall into the local extremum problem. Therefore, a new method offault prediction based on the improved firefly algorithm for NC machine tool is proposed. First, thefirefly algorithm is used to analyze the running process of a NC machine tool, and NC machine toolfault diagnosis model is established. Then, the background value optimization and NC machine toolfault diagnosis model are combined and applied in NC machine tools fault prediction, in thepredicting process, the effect of background value and initial conditions on the fault predictionaccuracy of the operation process of the NC machine tool, using iterative process to update theoriginal data, and the particle swarm optimization algorithm is fused to optimize the backgroundvalue of each iteration, in the end, NC machine tool fault prediction can be completed *** simulation results prove that the method of fault prediction of the NC machine tool based onthe improved firefly algorithm has high accuracy and robustness.
The direct measurement of SOC is challenging, in order to further improve the prediction accuracy of SOC, a neural network prediction model of SOC for the discharging process is established; a bi-directional recurrent...
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ISBN:
(纸本)9798400708299
The direct measurement of SOC is challenging, in order to further improve the prediction accuracy of SOC, a neural network prediction model of SOC for the discharging process is established; a bi-directional recurrent neural network based on improved sparrow optimization algorithm(ISSA-BiLSTM), for the traditional sparrow search algorithm has weak convergence, easy to fall into the local optimal solution, the initial solution is not strong randomness, etc., the initial value of the sparrow search algorithm is improved by adopting chaotic mapping, and the firefly algorithm is adopted to avoid being trapped in a local optimum, and an improved sparrow search algorithm with strong convergence is obtained (ISSA), and then optimize the bidirectional recurrent neural network. Then by optimizing the number of hidden layer nodes and the learning rate to reduce the prediction error of the neural network; test experiments on the LSTM, BiLSTM, and BiLSTM optimized by Improved Sparrow algorithm (ISSA-BiLSTM) are carried out by using the data set of lithium battery of McMaster university LG18650. The experimental results show that the ISSA-BiLSTM has a high prediction accuracy of 0.34% MAE and 0.43% RMSE for the discharge process at 25℃ room temperature, which is significantly higher than that of the LSTM and unoptimized BiLSTM .
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