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10th International Conference on Traffic and Logistic Engineering (ICTLE)

作者： Zhang, You Tian Zhe Jiang Gong Shang Univ Coll Business Adm Hangzhou Zhejiang Peoples R China

ISBN: (数字)9781665486309

ISBN: (纸本)9781665486309

Under the background of frequent international exchanges and the rapid development of international logistics, the cost optimization of international marine transportation as the main mode of transportation of goods has become more and more important. Under the premise of ensuring the safety and stability, the transformable container ship can improve the space utilization of cargo ships with maximum efficiency, thereby reducing the number of rounds or increasing the revenue to optimize the cost. The research method of this paper uses the differentiation of large and small cargoes based on the rules of determining the order, positioning and three space segmentation. Priority is given to loading small cargoes into containers, and then loading large cargoes and containers into the cargo hold. Finally, the remaining cargo is loaded onto the deck to maximize space utilization. Using genetic coding expressed in loading order, the way of loading cargo is coded to obtain the solution of the fitness function, and then an adaptive step size bacterial foraging algorithm is used to derive an optimal solution. Optimizing cargo ship loading strategy by designing model algorithms is of certain practical significance for the development of transnational logistics transportation activities.

关键词： transformable container ship three-dimensional crating three-space segmentation rule bacterial foraging algorithm

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Brownian Distribution Guided bacterial foraging algorithm for Controller Design Problem

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48th Annual Convention of Computer Society of India (CSI)

作者： Raja, N. Sri Madhava Rajinikanth, V. St Josephs Coll Engn Dept Elect & Instrumentat Madras 600119 Tamil Nadu India

ISBN: (纸本)9783319031071

bacterial foraging Optimization (BFO) algorithm is widely adopted to solve a variety of engineering optimization tasks. In this paper, the Brownian Distribution (BD) strategy guided BFO algorithm is proposed. During the optimization exploration, BD monitors and controls the chemotaxis operation of the BFO algorithm inorder to enhance the search speed and optimization accuracy. In the proposed algorithm, after undergoing a chemotaxis step, each bacterium gets mutated by a BD operator. In the proposed work, this algorithm is employed to design the PID controller for an AVR system and unstable reactor models. The success of the proposed method has been confirmed through a comparative analysis with PSO, BFO, adaptive BFO and PSO + BFO based hybrid methods existing in the literature. The result shows that, for unstable reactor models, the BD guided BFO algorithm provides better optimization accuracy compared to other algorithms considered in this study.

关键词： bacterial foraging algorithm Brownian Distribution PID controller design AVR system unstable reactor

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Image Matching based on bacterial foraging algorithm

Image Matching based on Bacterial Foraging Algorithm

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2nd International Conference on Advanced Measurement and Test (AMT 2011)

作者： Tian, Hongpeng Xian Univ Sci & Technol Coll Comp Sci & Technol Xian 710054 Shaanxi Peoples R China

ISBN: (纸本)9783037851975

To increase the speed of image matching, this paper combines bacterial foraging algorithm (BFA) of swarm intelligence with wavelet transform, and presents a fast matching method. The method regards the problem of image matching as a search for the optimal solution. To provide artificial bacterial swarm algorithm with an appropriate fitness function, the Normalized Product con:elation (NPROD) is employed to measure the similarity between the template image and the searching image. Then the best coarse matching position is gradually approaching by chemotaxis, elimination and dispersal, and reproduction behaviors of artificial bacterial. Finally, the best matching position is found out according to the coarse matching position. Experimental results show that the proposed method is fast and efficient.

关键词： image matching bacterial foraging algorithm swarm intelligence

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Collision Avoidance Strategy Optimization of Ship's Speed Alteration with bacterial foraging algorithm

Collision Avoidance Strategy Optimization of Ship's Speed Al...

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International Conference on Mechatronics and Control Engineering (ICMCE 2012)

作者： Ma, Wenyao Yang, Jiaxuan Guangdong Ocean Univ Nav Dept Zhanjiang 524025 Peoples R China Dailian Maritime Univ Navigat Coll Dalian 116026 Peoples R China

ISBN: (纸本)9783037855959

When ship navigates at sea, collision avoidance of ship's speed alteration is frequently adopted by officer on watch in order to prevent from forming collision situation with target ship(s). bacterial foraging algorithm (BFA) that imitates the social foraging behavior of Escherichia coli is an optimal search method suitable for complex problems. This research adopts the bacterial foraging algorithm to find the speed alteration collision avoidance strategy from an economical viewpoint, combining the international regulations for preventing collisions at sea (COLREGS) and the safety domain of ship. An optimal time of changing speed, amplitude of speed alteration and navigation restoration time will also be provided. The effectiveness of the algorithm has been verified by simulation. The study offers new thinking and a practical method for collision avoidance decision.

关键词： collision avoidance bacterial foraging algorithm safety domain of a ship optimization

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Research on Health Big Data Preprocessing Technology Based on AHSMM and bacterial foraging algorithm 2

Research on Health Big Data Preprocessing Technology Based o...

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IEEE 2nd International Conference on Electronic Information and Communication Technology (ICEICT)

作者： Liu, Zhen Liang, Xu Huang, Ming Dalian Jiaotong Univ Dalian 116052 Peoples R China

ISBN: (纸本)9781538692981

With the development of big data technology and the popularity of Internet of Things technology, the demand for management is becoming more and more serious. In order to solve the problem of health big data preprocessing technology, the method of Adaptive Hidden Semi-Markov Model (AHSMM) based on bacterial foraging algorithm is proposed. First of all, the bacterial foraging algorithm referring health big data is used to apply the equipment health diagnosis and prediction methods to the actual case of the United States Caterpillar company's standard health prediction experiments. Next, the proposed method is applied to the actual case of hydraulic pump of Caterpillar company. The results verify the effectiveness and stability of the proposed algorithm.

关键词： health big data bacterial foraging algorithm AHSMM

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Application of bacterial foraging algorithm for Fault Location in Distribution Networks with DG

Application of Bacterial Foraging Algorithm for Fault Locati...

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China International Conference on Electricity Distribution (CICED)

作者： Kong, Tao Jia, Mingna Sun, Guihua Shandong Univ Technol Zibo 255049 Peoples R China Shandong Kehui Power Automat Co LTD Zibo 255087 Peoples R China

ISBN: (纸本)9781467390682

For the difficulty of traditional fault location method brought by DG, an improved bacterial foraging algorithm is applied to fault location in distribution networks with DG. This method abandoned the construction of complex switching functions in the original intelligent bionic method. The relationship between the switch and the line is hided in the network relationship matrix, and the impact brought by DG is hided in the DG matrix. The mathematical model is improved so that it can be better adapt to multi-DG, multi-fault case. Even when the information is distorted, this method still has the ability of fault tolerance. Simulation examples demonstrate the feasibility of this program.

关键词： bacterial foraging algorithm distribution network DG fault location

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Proportional and Integral constants Optimization Using bacterial foraging algorithm for Boost Inverter 5th

Proportional and Integral constants Optimization Using Bacte...

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5th International Conference on Advances in Energy Research (ICAER)

作者： Arunkumar, G. Gnanambal, I Karthik, P. C. Naresh, S. Vellore Inst Technol Vellore Tamil Nadu India Anna Univ Govt Coll Engn Salem India

A boost dc-ac inverter is one which is capable of generating in a single stage ac voltage whose peak value can be higher or lower than the given input dc voltage. The major problem with this system is that the closed loop gain parameters kp and ki have to be optimized because these parameters help us to get desired result with better system response by lowering the rise time, settling time, peak overshoot and steady state error. Moreover when they are not optimized load line disturbances arise because of which the stability of output voltage decreases and THD value increases. So to overcome these difficulties bacterial foraging algorithm is being used. (C) 2016 The Authors. Published by Elsevier Ltd.

关键词： Boost Inverter bacterial foraging algorithm PI Controller

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bacterial foraging algorithm based parameter estimation of solar PV model

Bacterial Foraging Algorithm based parameter estimation of s...

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Annual International Conference on Emerging Research Areas

作者： Neeraja Krishnakumar Rini Venugopalan N. Rajasekar School of Electrical Engineering VIT University

ISBN: (纸本)9781467351508

The abundance and non-polluting nature of solar energy has aroused the interest of many researchers. This worldwide attention of photovoltaic panels has led to the need of generating accurate model of photovoltaic module before proceeding to the installation part. However, the modeling-of solar PV characteristics is difficult since the manufacturer's datasheet provides only four values such as V_(mp), I_(mp), V_(oc), and I_(sc). For the accurate modeling of photovoltaic panels, the precise estimation of model parameters at different environmental conditions is very essential. Optimization technique is a very powerful tool to obtain the solution of complex non-linear problems. In this paper, the application of the bacterial foraging algorithm (BFA) for the accurate extraction of model parameters has been discussed. A systematic evaluation and performance comparison of BFA with other optimization techniques such as Genetic algorithm, Artificial Immune System etc. has been done and the best computational technique is determined based on certain criteria such as accuracy, consistency, speed of convergence etc. The computed data is compared with experimental data and the results are validated using two photovoltaic modules of different nature (multicrystalline and thin film).

关键词： bacterial foraging algorithm Genetic algorithm Artificial Immune algorithm Photovoltaic module

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Quantum-inspired bacterial foraging algorithm for parameter adjustment in green cognitive radio

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Journal of Systems Science & Complexity 2015年第5期28卷 897-907页

作者： Hongyuan Gao Chenwan Li School of Information and Communication Engineering Harbin Engineering University

Parameter adjustment that maximizes the energy efficiency of cognitive radio networks is studied in this paper where it can be investigated as a complex discrete optimization problem. Then a quantum-inspired bacterial foraging algorithm(QBFA)is proposed. Quantum computing has perfect characteristics so as to avoid local convergence and speed up the optimization of QBFA. A proof of convergence is also given for this *** superiority of QBFA is verified by simulations on three test functions. A novel parameter adjustment method based on QBFA is proposed for resource allocation of green cognitive radio. The proposed method can provide a globally optimal solution for parameter adjustment in green cognitive radio networks. Simulation results show the proposed method can reduce energy consumption effectively while satisfying different quality of service(Qo S)requirements.

关键词： green cognitive radio parameter adjustment quantumcomputing bacterial foraging algorithm

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PHASE-ONLY PATTERN NULLING OF LINEAR ANTENNA ARRAYS WITH THE USE OF A bacterial foraging algorithm

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NEURAL NETWORK WORLD 2008年第4期18卷 257-273页

作者： Guney, Kerim Basbug, Suad Erciyes Univ Fac Engn Dept Elect & Elect Engn TR-38039 Kayseri Turkey Nevsehir Univ Dept Ind Elect Vocat Coll Nevsehir Turkey

In this paper, a bacterial foraging algorithm (BFA) has been used for null steering in the antenna radiation pattern by controlling only the element phases of a linear array. The BFA is an optimization algorithm based on the foraging behavior of Escherichia (E.) coli bacteria in human intestine. Numerical examples of Chebyshev pattern with the single, multiple and broad nulls imposed at the directions of interference are given to show the accuracy and flexibility of the BFA. The sensitivity of the nulling patterns due to small variations of the element phases is also investigated.

关键词： Antenna array pattern nulling bacterial foraging algorithm phase-only pattern synthesis

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