Power Transformer being essential and costlier equipment in the power sector, maintaining its healthiness is a crucial task. Condition monitoring of transformers can help in predicting the kinds of fault and prevent t...
详细信息
ISBN:
(数字)9781728132617
ISBN:
(纸本)9781728132624
Power Transformer being essential and costlier equipment in the power sector, maintaining its healthiness is a crucial task. Condition monitoring of transformers can help in predicting the kinds of fault and prevent the mishap. It can be achieved through Dissolved Gas Analysis. But interpretation of DGA to find the nature of fault that has occurred within transformer is a difficult job. There are many conventional methods like key gas method, Rogers ratio method, Duval triangle etc. These methods may not provide accurate and precise results in desired time. Therefore, modern heuristic methods can be helpful in reducing the computation time. One on such heuristic method is artificial bee colony algorithm. The results of this method are validated by comparing with the Fuzzy Inference System method on the basis of accuracy, precision, specificity and sensitivity.
In order to improve the power density of the in-wheel motor and reduce its cost of materials. A multi-objective optimization method of in-wheel motor for electric vehicles (EV) is proposed based on an improved artific...
详细信息
ISBN:
(纸本)9781450376259
In order to improve the power density of the in-wheel motor and reduce its cost of materials. A multi-objective optimization method of in-wheel motor for electric vehicles (EV) is proposed based on an improved artificialcolonyalgorithm. The new improved artificialcolonyalgorithm is used to implement motor optimizing design with the geometry size and material parameters of motor as variables and the quality, cost and power consumption of the motor as the optimization goal. The results show that compared with conventional artificialcolonyalgorithm, the convergence speed and global search ability of improved artificialcolonyalgorithm is better and the quality, cost and power loss of optimized motor is relatively reduced, and the efficiency is improved.
artificial bee colony algorithm is an effective optimization algorithm. In this paper, a novel artificial bee colony algorithm is developed based on a self-adaptive greedy strategy (SAGABC). Each bee should select whe...
详细信息
ISBN:
(纸本)9781538643624
artificial bee colony algorithm is an effective optimization algorithm. In this paper, a novel artificial bee colony algorithm is developed based on a self-adaptive greedy strategy (SAGABC). Each bee should select whether adopts greedy strategy or not based on its fitness value on each generation. Individuals with worse fitness value update with non-greedy strategy then they have more opportunity to get a better score while individuals with better fitness value update with greedy strategy to speed up convergence. In other word, non-greedy part improves diversity of population which contributes to a better global searching ability. Finally, the experience results demonstrate that the developed method shows a competitive performance compared with traditional ABC and other optimization algorithms on a number of benchmark functions.
In this study, magnetic positioning process is performed by WCE method which is mostly preferred in recent years. In order to make 5D magnetic positioning possible, two different algorithms were used to solve nonlinea...
详细信息
ISBN:
(纸本)9781538693582
In this study, magnetic positioning process is performed by WCE method which is mostly preferred in recent years. In order to make 5D magnetic positioning possible, two different algorithms were used to solve nonlinear mathematical dipole equations;artificial bee colony algorithm and Levenberg-Marquardt method. In case of using both algorithms separately and hybrid, performance comparison was made and the effect of noise on positioning error was investigated. As a result, we obtained a position error of less than 0.65 mm and orientation error of less than 0.8 degrees in the absence of noise and in case of noise addition, we had an average position error of 6.45 mm and a 9% angle error.
In order to quickly and efficiently simulate the crowd movement process under the evacuation scene, so as to reduce the casualties in emergency evacuation, this article proposes an indoor emergency evacuation model ba...
详细信息
ISBN:
(纸本)9781728140698
In order to quickly and efficiently simulate the crowd movement process under the evacuation scene, so as to reduce the casualties in emergency evacuation, this article proposes an indoor emergency evacuation model based on the improved artificial swarm algorithm. In this article, the cellular automata (CA) model is used to establish the evacuation environment, and then the artificialbeecolony (ABC) algorithm is used to simulate the crowd evacuation. However, due to too many obstacles existing in the neighboring cells of some position, the individual in that position have to wait. If the distance equation is used to calculate the fitness, it may cause other individuals to choose these positions as new position and repeat the same mistake above. To reduce the occurrence of such cases, we improve the fitness function of the ABC algorithm. In the fitness function, the factors of attraction and repulsion force in social force model are introduced. And on the basis of the ABC algorithm, we propose the visual employed bee. The visual employed bee leads the onlooker bee to evacuate, so as to improve the efficiency of evacuation. The research results of this article can provide ideas for evacuation modeling and useful guidance for formulating evacuation strategies to reduce evacuation time and disaster losses.
Aiming at the problem of large amount of space-time adaptive processing technology for airborne early warning radar, a sub-array partitioning method based on artificial bee colony algorithm is proposed. The method use...
详细信息
ISBN:
(纸本)9781538662434
Aiming at the problem of large amount of space-time adaptive processing technology for airborne early warning radar, a sub-array partitioning method based on artificial bee colony algorithm is proposed. The method uses the maximal improvement factor of the sub-array level as the optimization criterion, and uses the artificial bee colony algorithm to search for the optimal sub-matrix division method. Firstly, the basic principle of sub-array division is introduced, and then the sub-array division method of airborne early warning radar based on artificial bee colony algorithm is given in detail. The simulation analysis shows that compared with the traditional sub-matrix weighting method and the sub-array partitioning method based on genetic algorithm, the performance of the proposed space-time two-dimensional frequency response graph and improvement factor is significantly improved, and the actual performance of the current airborne early warning radar is improved. Engineering application has great reference value.
This paper considers a distributed planner method for multiple unmanned aerial vehicles (UAV), based on a leaderless approach, using an artificialbeecolony (ABC) optimization algorithm. The ABC algorithm is a metahe...
详细信息
ISBN:
(纸本)9781728103808
This paper considers a distributed planner method for multiple unmanned aerial vehicles (UAV), based on a leaderless approach, using an artificialbeecolony (ABC) optimization algorithm. The ABC algorithm is a metaheuristic optimization method inspired by the intelligent behavior of the honeybee swarm. The proposed ABC, implemented on each UAV independently, is used to compute velocity profiles that avoid obstacles and collisions between the UAVs while ensuring the fleet formation control and the target tracking. The proposed algorithm is demonstrated by simulations on Matlab/Simulink in different scenarios.
In this study, a harmonic estimation approach based artificial bee colony algorithm is proposed to identify and reduce the harmonic distortion caused by electrical and mechanical parts in the hydraulic shaking table. ...
详细信息
ISBN:
(纸本)9781728119045
In this study, a harmonic estimation approach based artificial bee colony algorithm is proposed to identify and reduce the harmonic distortion caused by electrical and mechanical parts in the hydraulic shaking table. Reducing harmonic distortion and increasing acceleration in the hydraulic shaking table depend on modeling and cancelling of disruptive harmonics. Therefore, it is important to develop fast and accurate harmonic estimation applications. The proposed harmonic estimation approach was applied to the literature problems and the results were compared.
In this paper, we propose a novel artificial bee colony algorithm for solving the multi-objective flexible job shop scheduling problem. In this algorithm, the whole population is divided into multiple subpopulations a...
详细信息
ISBN:
(纸本)9781728101057
In this paper, we propose a novel artificial bee colony algorithm for solving the multi-objective flexible job shop scheduling problem. In this algorithm, the whole population is divided into multiple subpopulations at each generation, and the size of each subpopulation is adaptively adjusted based on the information derived from its search results. Furthermore, the two mutation strategies implemented in the differential evolution algorithm are embedded in the proposed algorithm to facilitate the exchange of information in each subpopulation and between different subpopulations, respectively. Experimental results on the well-known benchmark multi-objective problems show that the improvements of the strategies are positive and that the proposed algorithm is better than or at least competitive to some previous multi-objective evolutionary algorithms.
Mining epistatic gene locus which influence complex disease has great research significance. Bayesian network (BN) has been widely used in many researches of epistasis mining. However, Bayesian network methods have di...
详细信息
ISBN:
(纸本)9781728118673
Mining epistatic gene locus which influence complex disease has great research significance. Bayesian network (BN) has been widely used in many researches of epistasis mining. However, Bayesian network methods have disadvantages of being easily trapped into local optimum, low learning efficiency and not being able to handle large-scale network. In this work, we propose an epistasis mining approach based on artificial bee colony algorithm optimizing Bayesian network (BnbeeEpi). We apply artificial bee colony algorithm into the heuristic search strategy of Bayesian network, and then use two kinds of BN scoring functions (BIC and MIT) to calculate the network fitness value to avoid overfitting and reduce false positive rate. Moreover, we introduce decomposable BIC scoring to solve the large-scale network learning problem. Finally, we compare BnbeeEpi with current popular epistasis mining algorithms by using both simulated and real datasets. Experiment results show that omb-Fast has very short running time with its accuracy is as good as other methods, and BnbeeEpi has better F1-score and lower false positive rate compared to others.
暂无评论