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International Conference on Dependable Systems and Their Applications (DSA)

作者： Cheng Li Liang Kou Xu Zhang College of Computer and Control Engineering Qiqihar University Qiqihar Heilongjiang School of Cyberspace Hangzhou Dianzi University Hangzhou Zhejiang P. R. China

ISBN: (数字)9780738124223

ISBN: (纸本)9781665419536

The research on traffic flow prediction has gained the considerable social value, especially for the short-term traffic flow prediction. The prediction of traffic flow is the theoretical basis of intelligent transportation as well as the key technology in traffic flow induction system. Currently, support vector regression(SVR) intelligent prediction model has been adopted in this research domain. Aiming at parameter selection difficulty solution and prediction accuracy improvement, the artificial bee colony(ABC) intelligent algorithm is applied to carry out the SVR parameter optimization in the paper, which is based on the analysis of the impact of SVR model parameters on short-term traffic flow prediction results. Accordingly, the intelligent combination short-term traffic flow prediction algorithm by ABC and SVR (ABC-SVR) is presented in the research. The simulation experiments are carried out by comparing the proposed algorithm with other algorithms. The feasibility and accuracy of the proposed ABC-SVR algorithm have been proved by the experimental results, and the further investigations and explorations of the future research are illustrated in the conclusion.

关键词： Support vector machines Transportation Predictive models Prediction algorithms artificial bee colony algorithm Computational complexity Optimization

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Design and analysis of the artificial bee colony algorithms for domain-oriented QoS-aware service composition

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INTERNATIONAL JOURNAL OF SERVICES TECHNOLOGY AND MANAGEMENT 2016年第6期22卷 378-405页

作者： Wang, Haifang Xu, Xiaofei Wang, Zhongjie Liu, Zhizhong Harbin Inst Technol Sch Comp Sci & Technol Harbin Peoples R China

Recently, various evolutionary algorithms have been successfully applied to acquire approximately optimal solutions for QoS-aware service composition problems. Especially, artificial bee colony algorithm (ABC) stands out due to its advantages of few parameters, strong robustness and search capability. In addition, for these algorithms, domain features are widely utilised as heuristic. However, how to combine these two points to achieve more optimal solutions is becoming a challenge. To address this critical challenge, this paper summarises three domain features (priori, similarity and correlation) and proposes the artificial bee colony algorithms for domain-oriented service composition named S-ABCsc paradigm. Besides, the framework of the paradigm is presented, and its seven configurable points are identified. Moreover, two types of algorithms are derived from the paradigm. To apply the paradigm, a support tool is realised, which helps users obtain a concrete algorithm. Furthermore, several comparison experiments are conducted, which have proved the effectiveness of the paradigm.

关键词： service composition service-oriented ABC paradigm artificial bee colony algorithm domain service QoS support tool algorithm generation domain features evolutionary algorithms parameter setting

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Optimal Placement of Actuator for Vibration Suppression Based on Intelligent PID Controller

Optimal Placement of Actuator for Vibration Suppression Base...

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IEEE International Conference on Intelligent Energy and Power Systems (IEPS)

作者： Muhamad Sukri Hadi Nadzirah Mohd Mokhtar Intan Zaurah Mat Darus Faculty of Mechanical Engineering Universiti Teknologi MARA Selangor Malaysia Faculty of Civil Engineering Technology Universiti Malaysia Pahang Pahang Malaysia Universiti Teknologi Malaysia Johor Malaysia

ISBN: (数字)9780738105680

ISBN: (纸本)9781665405157

Many attempts have been proposed by the previous researchers due to reduce the undesired vibration by considering several control strategies. The simplest way in reducing the vibration is to build more rigid structure so that less vibration will be produced. Nevertheless, this strategy is usually not applicable since the structures are need high power consumption and limitation in operation speed. Furthermore, it becomes a growing trend among the industries to use light weight of mechanical structure known as flexible plate. However, the critical problem faced by the industries is vibration on the structure that can lead to structural damage. Hence, this research presents the optimal placement of actuator and sensor on the experimental rig for vibration cancelation of the flexible plate structure based on intelligent PID controller. The PID controller tuned by artificial bee colony (ABC) algorithm was used to control the undesired vibration on the structure. The robustness of developed controller was validated by varying the position of actuator on the experimental rig. It was indicated that point A2 leads to the good attenuation level by achieving highest attenuation value at the first mode of vibration with 28.83 dB which is equivalent to 21.62 % attenuation, after the introduction of vibration control.

关键词： Actuators Vibrations Attenuation Vibration control artificial bee colony algorithm Industries Time factors

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Optimization of Capacitor Placement in Radial Distribution System Using Integer Encoding Genetic algorithm

Optimization of Capacitor Placement in Radial Distribution S...

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International Conference on Applied Science and Technology (iCAST)

作者： I Ketut Suryawan Igna Dwijaya Saputra Politeknik Negeri Bali Bali Indonesia

There are some problems in the distribution system such as, real power losses, lagging components of the current circuit that happened due to the growth of the load. These problems will impact in increasing the annual cost of the distribution system. One of the methods to avoid these problems is by installing the capacitors on several buses. These capacitors can reduce real power losses and also improve the bus voltage profile. The effectiveness of the capacitor installation depends on the location and size of the capacitor. In this paper, the tracing of the optimal capacitor location and size was carried out using an integer encoding genetic algorithm. Numerical simulation with a test system of 10 and 34 buses have been conducted and found that the proposed method was able to trace the optimal capacitor location and its size. This proposed method was able to provide more saving annual cost and better voltage improvement compared to the Modified ABC algorithm.

关键词： Costs Capacitors Voltage Numerical simulation artificial bee colony algorithm Encoding Computational efficiency

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Research on Prediction Method of Finish Rolling Power Consumption of Multi-Specific Strip Steel Based on Random Forest Optimization Model

Research on Prediction Method of Finish Rolling Power Consum...

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第三十九届中国控制会议

作者： XIAO Xiong DENG Daoming XIAO Yuxiong GUO Qiang ZHANG Yongjun Institute of Engineering Technology University of Science and Technology Beijing

The prediction of energy consumption data is of great importance in industrial process, among which the accurate prediction of power consumption at the production line level plays an even more essential role for energy conservation and consumption reduction under the background of steel intelligent manufacturing. In this paper, a random forest prediction model based on principal component dimensionality reduction and artificial bee colony dynamic search fusion is proposed to predict the power consumption prediction of multi-standard rolling stock in strip hot rolling finishing control section. The accurate prediction of the power consumption of the rolling section is realized with methods including data dimensionality reduction and parameter optimization. Firstly, principal component analysis is used to extract the principal components of the parameters affecting the strip rolling power consumption. Under the premise of ensuring the prediction accuracy, the computation time cost is reduced, random forest prediction model based on principal component extraction is established, and artificial bee colony is used. The dynamic search method optimizes the key parameters that affect the accuracy of random forest prediction, and further improves the prediction accuracy. The algorithm verification by using the pre-processed plant-level real-time data shows that the method can accurately predict the power loss of multi-size rolled parts with a low calculation time and a high prediction accuracy. This result indicates that the proposed model can meet the actual production of factory-level rolling demand for forecasting.

关键词： rolling power consumption principal component analysis random forest artificial bee colony algorithm multi-standard rolling

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Unknown Parameter Estimation of a Detailed Solar PV Cell Model

Unknown Parameter Estimation of a Detailed Solar PV Cell Mod...

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IEEE Region 10 International Conference TENCON

作者： Duy C. Huynh Loc D. Ho Matthew W. Dunnigan Ho Chi Minh City University of Technology (HUTECH) Ho Chi Minh City Vietnam Heriot-Watt University Edinburgh United Kingdom

ISBN: (数字)9781728184555

ISBN: (纸本)9781728184562

This paper proposes a novel technique for unknown parameter estimation of a detailed solar photovoltaic (PV) cell model based on the artificial bee colony (ABC) algorithm and particle swarm optimization (PSO) algorithm. This combination allows to balance between the exploration and exploitation abilities of each algorithm for achieving a good optimization performance. The detailed solar PV cell model is the double-diode model with seven unknown parameters which are estimated by using the hybrid ABC-PSO algorithm. The numerical results of the parameter estimation using the hybrid ABC-PSO algorithm are compared with those using the PSO, advanced PSO and ABC algorithms showing that the convergence speed and value of the hybrid ABC-PSO algorithm are always better than the PSO, advanced PSO and ABC algorithms.

关键词： artificial bee colony algorithm Parameter estimation Numerical models Optimization Mathematical model Convergence Integrated circuit modeling

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artificial bee colony optimised controller for small-scale unmanned helicopter

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AERONAUTICAL JOURNAL 2017年第1246期121卷 1879-1896页

作者： Ma, R. Wu, H. Ding, L. Nanjing Univ Aeronaut & Astronaut Coll Mech & Elect Engn Nanjing Jiangsu Peoples R China

In this paper, an efficient approach to design and optimize a flight controller of a small-scale unmanned helicopter is proposed. Given the identified helicopter model, the Linear Quadratic Gaussian/Loop Transfer Recovery (LQG/LTR) robust control method is applied for trajectory tracking and attitude control of the helicopter with a two-loop hierarchical control architecture. Since the performance of the controller extremely depends on its weighting matrices, the artificial bee colony (ABC) algorithm is introduced to automatically select the parameters of the matrices. Comparative studies between optimal algorithms are also carried out. A series of flight experiments and simulations are conducted to investigate the effectiveness and robustness of the proposed optimised controller.

关键词： Small-scale unmanned helicopter LQG/LTR artificial bee colony algorithm flight experiments trajectory tracking

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Study on the Workforce Scheduling and Routing Strategies of Heterogeneous Agents in Call Centers

Study on the Workforce Scheduling and Routing Strategies of ...

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2020年第五届经济与企业管理国际学术会议

作者： Mengchen Wang Xiuli Wang School of Economics and Management Nanjing University of Science and Technology

The performance of call center operations is usually associated with two factors,agent scheduling shifts and calls routing strategy,and they are dependent to some *** order to decrease the operating cost greatly,call centers need to properly allocate human resources and determine appropriate routing *** agent heterogeneity exists in the call center service system,this paper no longer assumes that agent service rates are all the *** construct an integer linear programming of the scheduling problem for call centers with agent heterogeneity,and combine the use of a discrete-event simulation model with an artificial bee colony algorithm to solve the *** evaluate the performance of the call center through discrete-event simulation experiments,and the artificial bee colony algorithm takes this performance metric as a judgment condition for satisfying the constraints,and iteratively obtains a better scheduling ***,we compare the effects of three routing strategies on the control of labor costs in enterprise *** actual data of the call center proves that considering the scheduling scheme of heterogeneous agents and the fastest server first routing can significantly reduce labor cost,and achieve effective service management.

关键词： Agent heterogeneity workforce scheduling routing strategies simulation artificial bee colony algorithm

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Cuckoo Search algorithm Inspired by artificial bee colony and Its Application

Cuckoo Search Algorithm Inspired by Artificial Bee Colony an...

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7th International Conference on Swarm Intelligence (ICSI)

作者： Gao, Yin Lei, Xiujuan Dai, Cai Shaanxi Normal Univ Xian Sch Comp Sci Xian 710119 Shaanxi Peoples R China

ISBN: (纸本)9783319410005;9783319409993

Cuckoo search algorithm with advanced levy flight strategy, can greatly improve algorithm's searching ability and increase the diversity of population. But it also has some problems. We improve them in this paper. First, in order to address the randomness of levy flight fluctuating significantly in the later and its poor convergence performance, we combine artificial bee colony algorithm with cuckoo search algorithm since artificial bee colony algorithm considers the group learning and cognitive ability, individuals learn from each other in the iterative process, which improves the local search ability of the later, and can find the optimal solution more quickly. Second, we use mutation operation to create the worst nest's position so as to increase the diversity of the population. Then put forward the ABC-M-CS algorithm and use the thought of K-means to cluster UCI data. The experimental results on UCI data sets indicate that ABC-M-CS algorithm has the fastest convergence speed, highest accuracy and stability.

关键词： Cuckoo search algorithm artificial bee colony algorithm Mutation operation Clustering

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Water Quality Prediction Model of a Water Diversion Project Based on the Improved artificial bee colony-Backpropagation Neural Network

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WATER 2018年第6期10卷 806页

作者： Chen, Siyu Fang, Guohua Huang, Xianfeng Zhang, Yuhong Hohai Univ Coll Water Conservancy & Hydropower Engn Nanjing 210098 Jiangsu Peoples R China

Prediction of water quality which can ensure the water supply and prevent water pollution is essential for a successful water transfer project. In recent years, with the development of artificial intelligence, the backpropagation (BP) neural network has been increasingly applied for the prediction and forecasting field. However, the BP neural network frame cannot satisfy the demand of higher accuracy. In this study, we extracted monitoring data from the water transfer channel of both the water resource and the intake area as training samples and selected some distinct indices as input factors to establish a BP neural network whose connection weight values between network layers and the threshold of each layer had already been optimized by an improved artificial bee colony (IABC) algorithm. Compared with the traditional BP and ABC-BP neural network model, it was shown that the IABC-BP neural network has a greater ability for forecasting and could achieve much better accuracy, nearly 25% more precise than the BP neural network. The new model is particularly practical for the water quality prediction of a water diversion project and could be readily applied in this field.

关键词： BP neural network artificial bee colony algorithm water quality prediction water diversion project

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