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Real-time detection of burst faults of key nodes in optical transmission networks based on fireworks algorithm

INTERNATIONAL JOURNAL OF SENSOR NETWORKS 2020年第2期33卷 98-108页

作者： Wang, Peng Zhang, Ningchao Xian Technol Univ Dept Elect Informat Engn Xian 710021 Peoples R China

In order to overcome the problems of poor real-time performance and low fitting degree of real-time detection methods for burst faults of key nodes in existing optical transmission networks, a new real-time detection method for burst faults of key nodes in optical transmission networks based on fireworks algorithm is proposed. The experimental results show that, compared with the traditional methods, the proposed real-time detection method for burst faults of key nodes in optical transmission network based on fireworks algorithm greatly improves the real-time performance and fitness, fully demonstrating that the proposed real-time detection method for burst faults of key nodes in optical transmission network based on fireworks algorithm has better detection effect.

关键词： fireworks algorithm optical transmission key nodes burst faults detection networks

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Phase partition and identification based on kernel entropy component analysis and multi-class support vector machines-fireworks algorithm for multi-phase batch process fault diagnosis

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TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL 2020年第12期42卷 2324-2337页

作者： Zhang, Min Wang, Ruiqi Cai, Zhenyu Cheng, Wenming Southwest Jiaotong Univ Sch Mech Engn Chengdu 61003 Peoples R China Technol & Equipment Rail Transit Operat & Mainten Chengdu Peoples R China

For the characteristics of nonlinear and multi-phase in the batch process, a self-adaptive multi-phase batch process fault diagnosis method is proposed in this paper. Firstly, kernel entropy component analysis (KECA) method is used to achieve multi-phase partition adaptively, which makes the process data mapped into the high-dimensional feature space and then constructs the core entropy and the angular structure similarity. Then a multi-phase KECA failure monitoring model is developed by using the angular structure similarity as the statistic, which is based on the partitioned phases and the effective failure features by the KECA feature extraction method. A multi-phase batch process fault diagnosis method, which applies the multi-class support vector machines (MSVM) and fireworks algorithm (FWA), is proposed to recognize each sub-phase fault diagnosis automatically. The effectiveness and advantages of the proposed multi-phase fault diagnosis method are illustrated with a case study on a fed-batch penicillin fermentation process.

关键词： Batch process multi-phase fault diagnosis kernel entropy component analysis fireworks algorithm multi-class support vector machine

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Planning capacity for 5G and beyond wireless networks by discrete fireworks algorithm with ensemble of local search methods

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EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING 2020年第1期2020卷 1-24页

作者： Ali, Hafiz Munsub Liu, Jiangchuan Ejaz, Waleed Simon Fraser Univ Sch Engn Sci 8888 Univ Dr Burnaby BC V5A 1S6 Canada Simon Fraser Univ Sch Comp Sci 8888 Univ Dr Burnaby BC V5A 1S6 Canada Lakehead Univ Barrie Campus Dept Elect Engn Orillia ON Canada

In densely populated urban centers, planning optimized capacity for the fifth-generation (5G) and beyond wireless networks is a challenging task. In this paper, we propose a mathematical framework for the planning capacity of a 5G and beyond wireless networks. We considered a single-hop wireless network consists of base stations (BSs), relay stations (RSs), and user equipment (UEs). Wireless network planning (WNP) should decide the placement of BSs and RSs to the candidate sites and decide the possible connections among them and their further connections to UEs. The objective of the planning is to minimize the hardware and operational cost while planning capacity of a 5G and beyond wireless networks. The formulated WNP is an integer programming problem. Finding an optimal solution by using exhaustive search is not practical due to the demand for high computing resources. As a practical approach, a new population-based meta-heuristic algorithm is proposed to find a high-quality solution. The proposed discrete fireworks algorithm (DFWA) uses an ensemble of local search methods: insert, swap, and interchange. The performance of the proposed DFWA is compared against the low-complexity biogeography-based optimization (LC-BBO), the discrete artificial bee colony (DABC), and the genetic algorithm (GA). Simulation results and statistical tests demonstrate that the proposed algorithm can comparatively find good-quality solutions with moderate computing resources.

关键词： Fifth generation and beyond wireless networks Swarm intelligence fireworks algorithm Ensemble of local search methods

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Locating the critical slip surface in a slope stability analysis by enhanced fireworks algorithm

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CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS 2019年第1-Sup期22卷 719-729页

作者： Xiao, Zeyun Tian, Bin Lu, Xiaochun Wuhan Univ Sch Water Resources & Hydropower Engn Wuhan 430072 Hubei Peoples R China China Three Gorgers Univ Coll Hydraul & Environm Engn Yichang 443002 Peoples R China

In this paper we propose an enhanced fireworks algorithm for locating the critical slip surface giving the minimum safety factor in slope stability analysis, and we employ a concise algorithm of the Morgenstern and Price method to calculate the safety factor. To demonstrate its applicability and to illustrate the reliability and effectiveness of the proposed method, we present three benchmark examples with varying complex slopes. By comparing the minimum safety factor and the total number of iterations, the proposed method is proved to be highly competitive in terms of efficiency and accuracy.

关键词： fireworks algorithm Critical slip surface Safety factor Slope stability Optimization

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Cooperative Global Path Planning for Multiple Unmanned Aerial Vehicles Based on Improved fireworks algorithm Using Differential Evolution Operation

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INTERNATIONAL JOURNAL OF AERONAUTICAL AND SPACE SCIENCES 2023年第5期24卷 1346-1362页

作者： Zhang, Xiangyin Zhang, Xiangsen Miao, Yang Beijing Univ Technol Fac Informat Technol Beijing 100124 Peoples R China Beijing Univ Technol Fac Mat & Mfg Beijing 100124 Peoples R China

Multiple unmanned aerial vehicles' (multi-UAVs) cooperative global path planning is considered as a complexed nonlinear optimization problem. The improved hybrid fireworks algorithm with differential evolution (HDEFWA) is put forward herein to handle the problem and yield optimal flyable paths for multi-UAVs. The UAV paths are expected to be safe and short, of which the cost function is modeled according to realistic scenarios. The proposed HDEFWA can generate the extra DE-sparks through the mutation, crossover, and selection operators using the highly ranked individuals, which greatly enhances the information sharing capacity among the better individuals and thus effectively strengthen the capacity to escape from local optima. To handle the multi-UAVs cooperative planning, the whole firework population in HDEFWA is divided into a series of parallel firework groups, and the information interaction mechanism is established to calculate the cooperative cost of solutions to achieve the collision-free among UAV paths. Simulation results demonstrate that our HDEFWA can effectively settle multi-UAVs cooperative path planning with the better performance than other population-based algorithms.

关键词： Cooperative path planning fireworks algorithm Multiple unmanned air vehicles Differential evolution

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An improved fireworks algorithm for discrete sizing optimization of steel skeletal structures

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ENGINEERING OPTIMIZATION 2018年第11期50卷 1829-1849页

作者： Gholizadeh, Saeed Milany, Arman Urmia Univ Dept Civil Engn Orumiyeh Iran

The fireworks algorithm (FWA), a newly introduced metaheuristic algorithm, has exhibited remarkable performance in a variety of optimization problems. However, FWA still has some shortcomings that need to be addressed. In the present study, an improved fireworks algorithm (IFWA) is proposed to mitigate the drawbacks of the original algorithm. In the IFWA, the possibility of interaction among different solutions during the optimization process is provided. Moreover, a strategy is considered to decrease the computational effort of the algorithm. The IFWA is used to deal with the discrete structural optimization problems of steel trusses and frames. The results demonstrate the efficiency of the proposed IFWA compared with other well-known metaheuristics in the literature, in terms of the optimum solutions and the convergence rate.

关键词： Structural optimization discrete variable metaheuristic fireworks algorithm

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Reliable and efficient emergency rescue networks: A blockchain and fireworks algorithm-based approach

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COMPUTER COMMUNICATIONS 2023年第1期206卷 172-177页

作者： Chen, Bin Zhang, Weihua Shi, Yijin Lv, Di Yang, Zilan Lijiang Cultural & Tourism Coll Lijiang Peoples R China Lijiang Jingcheng Educ Training Co Ltd Lijiang Peoples R China

In recent years, coronavirus disease 2019 (COVID-19) has been a severe issue the world faces. Emergency rescue networks concerning the distribution of relief materials have gained extensive attention to tackle COVID-19 and related emergency issues. However, it is challenging to establish reliable and efficient emergency rescue networks due to information asymmetry and lack of trust among different rescue stations. In this work, we propose blockchain-based emergency rescue networks to track every transaction of the relief materials reliably and make decisions to deliver relief materials efficiently. More specifically, we propose a hybrid blockchain architecture that employs on-chain data verification to authenticate data records and off-chain data storage to reduce storage overhead. Furthermore, we propose a fireworks algorithm to efficiently calculate the optimal allocation strategies for relief materials. The algorithm provides chaotic random screening and node request guarantee techniques with good convergence. The simulation results show that integrating blockchain technology and the fireworks algorithm can significantly improve relief materials' operation efficiency and distribution quality.

关键词： Emergency rescue network Blockchain fireworks algorithm

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Short-term ice accretion forecasting model for transmission lines with modified time-series analysis by fireworks algorithm

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IET GENERATION TRANSMISSION & DISTRIBUTION 2018年第5期12卷 1074-1080页

作者： Huang, Xin-Bo Li, Hong-Bo Zhu, Yong-Can Xian Polytech Univ Coll Elect & Informat Xian 710048 Shaanxi Peoples R China CCCC First Highway Consultants Co Ltd Xian 710075 Shaanxi Peoples R China

In order to reduce the damages of transmission line icing, an effective ice accretion forecasting can be used to guide the de-icing work. The ice accretion on transmission lines varies slowly over time, and the icing data series is characteristic of timing sequence and autocorrelation. Time-series analysis is suitable for analysing the similar data series, and fireworks algorithm (FA) is used to determine the autoregressive order and the moving average order of time-series analysis. Then a short-term ice accretion forecasting for transmission lines with modified time-series analysis by FA is built. The ice accretion experiments were done in artificial icing laboratory. The results show that the modified time-series analysis model by the FA has higher accuracy than another five models, whose relative errors are <1.3% and closer to the experimental data. Field applications also show that the modified time-series analysis model has higher accuracy than the traditional one for the short-term ice accretion forecasting, whose average error rates are separately 2.6723 and 5.2654%.

关键词： freezing ice time series accretion forecasting theory power transmission lines short-term ice accretion forecasting model transmission line icing modified time-series analysis model fireworks algorithm de-icing work timing sequence autocorrelation icing data series similar data series analysis autoregressive order moving average order average error rates

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An effective fireworks algorithm for warehouse-scheduling problem

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TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL 2017年第1期39卷 75-85页

作者： Ye, Sengang Ma, Haiping Xu, Sheng Yang, Wenqiang Fei, Minrui Shaoxing Univ Dept Elect Engn Shaoxing Zhejiang Peoples R China Shanghai Univ Sch Mechatron Engn & Automat Shanghai Key Lab Power Stn Automat Technol Shanghai Peoples R China Henan Normal Univ Sch Comp & Informat Engn Xinxiang Henan Peoples R China

This paper proposes an effective fireworks algorithm (FWA), which is a new heuristic algorithm inspired by the phenomenon of a fireworks display, to solve the warehouse-scheduling problem. First, a real-world warehouse-scheduling problem is described in detail, and it is formulated as a constrained single-objective optimization problem. Then an effective FWA, FWA-LSCM, is developed by combining with a local search method and chaotic mutation, which are used to balance the exploration and exploitation of FWA. The experimental results show that FWA-LSCM is a competitive algorithm for a set of 2013 Congress on Evolutionary Computation (CEC) benchmark functions. Finally, the proposed FWA-LSCM is successfully applied to the warehouse-scheduling problem and outperforms other FWA algorithms studied in this paper.

关键词： fireworks algorithm heuristic algorithm local search travel time analysis warehouse scheduling

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Application of improved fireworks algorithm in grinding surface roughness online monitoring

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JOURNAL OF MANUFACTURING PROCESSES 2022年 74卷 400-412页

作者： Li, Yang Liu, Yanhou Tian, Yebing Wang, Yi Wang, Jinling Shandong Univ Technol Sch Mech Engn Zibo 255000 Peoples R China Shandong Key Lab Precis Mfg & Special Proc Zibo 255000 Peoples R China

The enclosed machining environment, the cutting fluid impact on the workpiece, the danger posed by high-speed rotation of the grinding wheel and the highly dynamic nature of the machine tool makes online monitoring surface roughness a self-evident conundrum in the grinding process. Guided by this difficulty, an online monitoring method of the grinding surface roughness based on Improved fireworks algorithm (IFWA) was proposed. According to the frequency spectrum analysis of grinding force signal and surface texture curve, and with the help of chi-square distribution density function, the functional relationship between grinding force signal and surface texture amplitude-frequency curve was established. Then, the Inverse Discrete Fourier Transform (IDFT) of the aforementioned mathematical function was executed to procure the mathematical relationship of the grinding force signal expressing the surface texture curve. Furthermore, the least square method was used to calibrate the profile least-square median of the surface texture curve. The calculation process of the surface texture curve to the surface roughness was then incorporated into the IFWA. Eventually, the elite retention strategy was introduced into the standard fireworks algorithm (FWA). An IFWA was designed to optimize the attenuation coefficient in the grinding force signal and surface texture curve function model. Taking the plane grinding of silica ceramic composites as an example, a theoretical model for online monitoring the grinding surface roughness was established based on the experimental data, and the prediction results in the accuracy of the method was the highest by comparing various algorithms. According to this model, the online monitoring of grinding roughness can be accomplished by the real-time acquisition of force signals in the grinding process.

关键词： Online monitoring Surface roughness Spectrum analysis Attenuation coefficient fireworks algorithm

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