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Modelling the Selection of Waiting Areas on Subway Platforms Based on the bacterial chemotaxis algorithm

TEHNICKI VJESNIK-TECHNICAL GAZETTE 2023年第1期30卷 207-216页

作者： Yuan, Guang Kong, Dewen Sun, Lishan Liu, Guangtong Chen, Yingda Beijing Univ Technol Beijing Key Lab Traff Engn Beijing Peoples R China Beijing Univ Technol Engn Res Ctr Digital Community Minist Educ Beijing Peoples R China Beijing Univ Technol Beijing Lab Urban Mass Transit 100 Pingleyuan Beijing 100124 Peoples R China Beijing Inst Econ & Social Dev 55 Yunhe East St Beijing 101160 Peoples R China Qingdao Municipal Engn Design Res Inst 222 Shenzhen Rd Qingdao 266100 Peoples R China Tongji Univ Key Lab Rd & Traff Engn Minist Educ 4800 Caoyang Rd Shanghai 201804 Peoples R China

Based on the bacterial chemotaxis algorithm, a new waiting-area selection model (WASM) is proposed that predicts well the pedestrian distribution in subway waiting areas. WASM regards passengers waiting on a subway platform as two-dimensional points and adopts an essential rejection factor to determine the target waiting area. Based on WASM, three experiments were carried out to explore how passenger volume, waiting-area capacity, and staircase position affect the number and distribution of waiting passengers. The experimental results show the following. 1) Regardless of the passenger flow, passengers prefer waiting areas that are between the stairs. 2) Setting proper capacity limits on waiting areas can help to improve subway transportation efficiency when passenger flow is relatively high. 3) The experimental results show that the closer the staircases, the more passengers are left stranded on the platform.

关键词： bacterial chemotaxis algorithm pedestrian distribution subway platform waiting area selection

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Application of the bacterial chemotaxis algorithm for Solving Nonlinear Optimal Control Problem

Application of the Bacterial Chemotaxis Algorithm for Solvin...

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24th Chinese Control and Decision Conference (CCDC)

作者： Ren, Ping Gao, Liqun Li, Nan Shenyang Univ Sch Informat Engn Shenyang 110044 Peoples R China Northeastern Univ Sch Informat Sci & Engn Shenyang 110044 Peoples R China Shenyang Univ Shenyang 110044 Peoples R China

ISBN: (纸本)9781457720727

In this paper, the nonlinear optimal control problem is formulated as a multi-objective mathematical optimization problem. bacterial chemotaxis (BC) algorithm is one of the new heuristic algorithms based on colony intelligence. The BC optimization algorithm is introduced for the first time in solving the nonlinear optimal control problem. A case on the nonlinear optimal control problem is presented to show the methodology's feasibility and efficiency, compared with the existing optimal planning methods, the search time of the BC optimization algorithm is shorter and the result is close to the ideal solution, simultaneously.

关键词： Nonlinear optimal control problem Multi-objective mathematical optimization problem bacterial chemotaxis algorithm Application

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Application of the bacterial chemotaxis algorithm for Solving Nonlinear Optimal Control Problem

Application of the Bacterial Chemotaxis Algorithm for Solvin...

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The 24th Chinese Control and Decision Conference (第24届中国控制与决策学术年会 2012 CCDC)

作者： Ping Ren Liqun Gao Nan Li School of Information Engineering Shenyang University Shenyang 110044 School of Information Science and Engineering Northeastern University Shenyang 110004 Shenyang University Shenyang 110044 China

In this paper, the nonlinear optimal control problem is formulated as a multi-objective mathematical optimization problem. bacterial chemotaxis (BC) algorithm is one of the new heuristic algorithms based on colony intelligence. The BC optimization algorithm is introduced for the first time in solving the nonlinear optimal control problem. A case on the nonlinear optimal control problem is presented to show the methodology’s feasibility and efficiency, compared with the existing optimal planning methods, the search time of the BC optimization algorithm is shorter and the result is close to the ideal solution, simultaneously.

关键词： Nonlinear optimal control problem Multi-objective mathematical optimization problem bacterial chemotaxis algorithm Application

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A PSO-Based bacterial chemotaxis algorithm and Its Application

A PSO-Based Bacterial Chemotaxis Algorithm and Its Applicati...

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8th International Symposium on Neural Networks

作者： Zhang, Rui Zhou, Jianzhong Lu, Youlin Qin, Hui Zhang, Huifeng Huazhong Univ Sci & Technol Coll Hydorpower Informat Engn Wuhan 430074 Hubei Peoples R China

ISBN: (纸本)9783642211102

In this paper, a new two-phased optimization algorithm called BC-PSO is presented. bacterial chemotaxis algorithm is a biologically inspired optimization method which is analyzing the way bacteria react to chemoattractants in concentration gradients. Aiming at the shortcomings of BC which is lack of global searching ability with low speed, PSO is introduced to accelerate convergence before BC works. With some famous test functions been used, the numerical experiment results and comparative analysis prove that it outperforms standard PSO and GA. Finally, the hybrid algorithm is applied to solve the problem of mid-long term optimal operation of cascade hydropower stations. Comparing with the other algorithms, the operation strategy shows its higher efficiency.

关键词： bacterial chemotaxis algorithm particle swarm operation optimal operation cascade hydropower station

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bacterial chemotaxis shape optimization of electromagnetic devices

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INVERSE PROBLEMS IN SCIENCE AND ENGINEERING 2014年第6期22卷 910-923页

作者： Coco, Salvatore Laudani, Antonino Fulginei, Francesco Riganti Salvini, Alessandro Univ Catania DIEEI Catania Italy Roma Tre Univ Dept Engn Rome Italy

In this paper, a bacterial chemotaxis shape optimization algorithm is presented for the optimal design of electromagnetic devices. The bacterial chemotaxis algorithm exploits the conceptual analogy between bacteria and mesh nodes, improving the devices performance by moving the specific mesh nodes/bacteria defining the shape in the same way the bacteria move toward regions presenting better life conditions. Validation tests are also presented in order to show the performance of the developed shape optimizer.

关键词： bacterial chemotaxis algorithm finite element method shape optimization soft computing metaheuristics

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Mean Shift Segmentation algorithm Based on Hybridized bacterial chemotaxis

Mean Shift Segmentation Algorithm Based on Hybridized Bacter...

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3rd International Conference on Manufacturing Science and Engineering (ICMSE 2012)

作者： Li Yan-ling Li Gang Xinyang Normal Univ Coll Comp & Informat Technol Xinyang 464000 Peoples R China

ISBN: (纸本)9783037853696

Mean shift, like other gradient ascent optimization methods, is susceptible to local maximum/minimum, and hence often fails to find the desired global maximum/minimum. For this reason, mean shift segmentation algorithm based on hybridized bacterial chemotaxis (HBC) is proposed in this paper. In HBC, particle swarm operation algorithm(PSO) is introduced before bacterial chemotaxis(BC) works. And PSO is firstly introduced to execute the global search, and then stochastic local search works by BC. Meanwhile, elitism preservation is used in the paper in order to improve the efficiency of the new algorithm. After mean shift vector is optimized using HBC algorithm, the optimal mean shift vector is updated using mean shift procedure. Experimental results show that new algorithm not only has higher convergence speed, but also can achieve more robust segmentation results.

关键词： image segmentation mean shift particle swarm operation bacterial chemotaxis algorithm

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Fuzzy C-means Cluster Segmentation algorithm Based on bacterial Colony chemotaxis

Fuzzy C-means Cluster Segmentation Algorithm Based on Bacter...

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2nd International Conference on Advances in Materials and Manufacturing Processes (ICAMMP 2011)

作者： Li Yan-ling Li Gang Xinyang Normal Univ Coll Comp & Informat Technol Xinyang 464000 Peoples R China

ISBN: (纸本)9783037853276

Fuzzy C-Means(FCM) algorithm is one of the most popular methods for image segmentation, but it is in essence a technology of searching local optimal solution. The algorithm's initial clustering centers are stochastic selection which causes it to depend on the selection of the initial cluster centers excessively. For this reason, fuzzy C-means cluster segmentation algorithm based on bacterial colony chemotaxis (BCC) is proposed in this paper. Firstly, initial cluster centers of FCM algorithm is get by BCC algorithm. Then, the images are segmented using FCM algorithm. Experimental results show that the proposed algorithm used for image segmentation can segment images more effectively and can provide more robust segmentation results.

关键词： fuzzy C-means bacterial chemotaxis algorithm bacterial colony chemotaxis algorithm image segmentation

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Adaptive Mean Shift algorithm Based on Hybridized bacterial chemotaxis

Adaptive Mean Shift Algorithm Based on Hybridized Bacterial ...

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2012 International Conference on Modelling,Identification and Control(建模、辨别与控制国际会议 ICMIC 2012)

作者： Yanling Li Yi Shen College of Computer and Information Technology Xinyang Normal UniversityXinyang464000China Department of Control Science and Engineering Huazhong University of Science and TechnologyWuhan 43

Mean shift is an effective statistical iterative *** size of bandwidth has great impact on the accuracy and efficiency of the *** not only decides the number of sampling points in the iteration, but also affects the convergence speed and accuracy of the *** this reason, adaptive mean shift algorithm based on hybridized bacterial chemotaxis(HBC) is proposed in this *** HBC, particle swarm operation algorithm (PSO) is introduced before bacterial chemotaxis(BC) *** PSO is firstly introduced to execute the global search, and then stochastic local search works by ***, elitism preservation is used in this paper in order to improve the efficiency of the new *** the proposed new algorithm, bandwidth is calculated by HBC algorithm in which bandwidth is calculated adaptively according to the local structure of sampling *** results show that the proposed algorithm can achieve more robust segmentation results.

关键词： image segmentation mean shift particle swarm operation bacterial chemotaxis algorithm bandwidth

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A New Mean Shift algorithm Based on bacterial Colony chemotaxis

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INTERNATIONAL JOURNAL OF FUZZY SYSTEMS 2012年第2期14卷 257-263页

作者： Li, Yanling Li, Gang Xinyang Normal Univ Coll Comp & Informat Technol Xinyang 464000 Peoples R China

Mean shift is an effective statistical iterative algorithm. Like other gradient ascent optimization methods, it is susceptible to local maxima, and hence often fails to find the desired global maximum. And in the iterative process, size of bandwidth has great impact on the accuracy and efficiency of the algorithm. It not only decides the number of sampling points in the iteration, but also affects the convergence speed and accuracy of the algorithm. For the above reason, a new mean shift algorithm based on bacterial colony chemotaxis (BCC) is proposed in this paper. Firstly, the mean shift vector is optimized using BCC algorithm. Then, the optimal mean shift vector is updated using mean shift procedure. For the choice of bandwidth, bandwidth is calculated by BCC algorithm. Experimental results show that the proposed algorithm used for image segmentation can segment images more effectively and provide more robust segmentation results.

关键词： bacterial chemotaxis algorithm bacterial colony chemotaxis algorithm bandwidth image segmentation mean shift

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Adaptive Mean Shiftalgorithm Based on Hybridized bacterial chemotaxis

Adaptive Mean ShiftAlgorithm Based on Hybridized Bacterial C...

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4th International Conference on Modelling,Identification and Control(ICMIC 2012)

作者： Yanling LI is with College of Computer and Information Technology, Xinyang Normal University, Xinyang, 464000, China Yi SHEN is with Department of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China

Mean shift is an effective statistical iterative algorithm. But size of bandwidth has great impact on the accuracyand efficiency of the algorithm. It not only decides the number of sampling points in the iteration, but also affects the convergence speed and accuracy of the algorithm. For this reason, adaptive mean shift algorithm based on hybridized bacterial chemotaxis(HBC) is proposed in this paper. In HBC, particle swarm operation algorithm (PSO) is introduced before bacterial chemotaxis(BC) works. And PSO is firstly introduced to execute the global search, and then stochastic local search works by BC. Meanwhile, elitism preservation is used in this paper in order to improve the efficiency of the new algorithm. In the proposed new algorithm, bandwidth is calculated by HBC algorithm in which bandwidth is calculated adaptively according to the local structure of sampling points. Experimental results show that the proposed algorithm can achieve more robust segmentation results.

关键词： image segmentation mean shift particle swarm operation bacterial chemotaxis algorithm bandwidth

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