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Research of immune clone algorithm applying in the LED lamp automatic lock screw workstation

JOURNAL OF COMPUTATIONAL METHODS IN SCIENCES AND ENGINEERING 2023年第6期23卷 3081-3091页

作者： Ding, Dukun Deng, Jianxin Ye, Hui Dongguan Polytech Dongguan Intelligent Mfg Engn Technol Res Ctr Dongguan 523808 Guangdong Peoples R China Guangxi Univ Guangxi Key Lab Mfg Syst & Adv Mfg Technol Nanning Guangxi Peoples R China ABB China Ltd Guangzhou Branch Guangzhou Guangdong Peoples R China

A new automatic lock screw machine for LED lamp has been researched in the paper, which is based on the immune clone algorithm. Firstly, the robot automatic lock screw system has been setup. Vision sensor captured LED lampshade images in real-time. Median filtering operation has been performed to the captured images. On this basis, a new image segmentation method based on the immune clone algorithm has been researched. The antibody and antigen of LED lampshade image have been defined. The immune affinity function has been setup at the same time. Several artificial immune operators have been designed, which can be used to obtain the optimum image segmentation threshold value in real time. The final results showed that the optimum image threshold value can been obtained after less than ten times iterative computation. Compared with the traditional Ostu method, the new method can reduce the disturbance information around the threaded hole, which made basis for threaded hole recognition and location.

关键词： Automatic screw locking machine robot station machine vision immune clone algorithm

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Compressed Sensing Reconstruction for Hyperspectral Images Using immune clone algorithm Based on Gaussian Dictionary

International Core Journal of Engineering

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International Core Journal of Engineering 2020年第5期6卷 269-275页

作者： Li Wang Wei Wang Boni Liu

An immune clone algorithm (ICA) for compressed sensing (CS) reconstruction for hyperspectral images is proposed. The core idea of compressed sensing theory is that, an image of interest is sparse or compressible in some domain, and then it could be reconstructed accurately through a complex optimization algorithm. ICA is a global optimal search algorithm which could ensure the algorithm converges to the optimal solution with probability 1. The paper takes advantage of the ICA to solve a complex optimization problem to reconstruct the images which are sampled by compressed sensing. The proposed algorithm was evaluated on some hyperspectral images and the results illustrate that the reconstructed images has high peak signal-to-noise ratio (PSNR) owing to the merit of ICA.

关键词： Hyperspectral images Compressed sensing reconstruction immune clone algorithm Reconstructed peak signal-to-noise ratio

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Journal of Mathematical Research with Applications 2019年第6期39卷 745-754页

作者： Chunhua Chao ZHANG Yan LIU Wei WU School of Mathematical Sciences Dalian University of Technology College of Computer Sciences and Technology Inner Mongolia University for Nationalities Department of General Education Dalian Polytechnic University

Text clustering is an important research issue of clustering technique. It aims to use the similar characteristics or similar expression to group the text so that the texts in the same clusters have the greatest similarity, and those in different clusters have the greatest *** are many characteristics in Mongolian structure and writing-mode compared with other kinds of characters. By combining K-means and clone immune algorithm, we propose a novel clustering technique called ICKM. Numerical experiments on four elements sets illustrate the validity of our method in the clustering task for Mongolian.

关键词： immune clone algorithm Mongolian similar elements clustering K-means

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Berth and quay cranes allocation problem with on-shore power supply assignment in container terminals

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COMPUTERS & INDUSTRIAL ENGINEERING 2024年 188卷

作者： Wang, Zhu Hu, Hongtao Zhen, Lu Shanghai Maritime Univ Logist Engn Coll Shanghai 201306 Peoples R China Shanghai Maritime Univ Container Supply Chain Technol Engn Res Ctr Minist Educ Shanghai 201306 Peoples R China Shanghai Univ Sch Management Shanghai 200444 Peoples R China

On -shore power supply (OPS) is a promising carbon emission -reduction technology for vessels and ports. Optimizing its allocation for berthing vessels is a new operational challenge due to different deployments on shore and on board. This article proposes an innovative solution to enhance the effectiveness of berths and on -shore power utilization in container terminals. The proposed solution integrates continuous berth allocation, quay crane assignment, and OPS allocation to address optimization challenges. First, a mixed -integer programming model is formulated based on the in-depth analysis of the OPS service coverage and carbon emissions of vessels, aiming to increase service efficiency, reduce energy consumption, and minimize carbon taxation. Then, an adaptive immune clone selection algorithm is developed to solve this problem. Adaptive and elite strategies are adopted to enrich population diversity. To improve convergence speed, a heuristic algorithm is designed based on the established model. Numerical experiments based on practical instances confirm the model's validity and the proposed algorithm's superiority over benchmark methods. The proposed integrated optimization strategy yields an average cost reduction of 2.14% and reduces carbon emissions by 2.90% by combining carbon taxation and OPS implementation. The study also highlights that OPS utilization is determined by fuel price and vessel retrofit ratio. Managerial insights suggest that raising the OPS service coverage to 50% and the vessel retrofit ratio to 70% would greatly benefit the port both economically and environmentally. To increase OPS utilization, coordination between port and shipping companies is necessary.

关键词： Continuous berth and quay crane allocation Carbon taxation On-shore power supply Mixed-integer programming immune clone algorithm

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Charging and Discharging Control of Plug-In Electric Vehicle Based On immune clone algorithm

Charging and Discharging Control of Plug-In Electric Vehicle...

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International Conference on Advances in Energy and Environmental Science (ICAEES)

作者： Wang, Min Zhang, Yang Li, Yongqing Zhang, Chengfei Yuan, Yue Hohai Univ Coll Energy & Elect Engn Nanjing 211100 Jiangsu Peoples R China

ISBN: (纸本)9783037858615

When a large scale of plug-in electric vehicles connected to the grid, which will be bound to deteriorate the load curve and will affect the safe and stable operation of the grid without a reasonable means of control. immune clone algorithm is applied to control the electric vehicles' charging and discharging strategy and to develop a optimized scheduling scheme throughout the day. In this way not only can it avoid electric vehicles disorderly charging and discharging disorderly so that to optimize grid load curve, but also can reduce the loss of electric power lines and delay investment.

关键词： immune clone algorithm plug-in electric vehicles load curve variance

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A powerful tool for near-infrared spectroscopy: Synergy adaptive moving window algorithm based on the immune support vector machine

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SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2022年第0期282卷 121631页

作者： Wang, Shenghao Zhang, Peng Chang, Jing Fang, Zeping Yang, Yi Lin, Manman Meng, Yanhong Lin, Zhixin Zhongyuan Univ Technol Sch Elect & Informat Engn Zhengzhou Peoples R China Zhongyuan Univ Technol Sch Polit Sci & Law Zhengzhou Peoples R China

Traditional trial-and-error methods are time-consuming and inefficient, especially very unfriendly to inexperienced analysts, and are sometimes still used to select preprocessing methods or wavelength variables in near-infrared spectroscopy (NIR). To deal with this problem, a new optimization algorithm called synergy adaptive moving window algorithm based on the immune support vector machine (SA-MW-ISVM) is proposed in this paper. Following the principle of SA-MW-ISVM, the original problem of calibration model optimization is transformed into a mathematical optimization problem that can be processed by the proposed immune support vector machine regression algorithm. The main objective of this optimization problem is the calibration model performance;meanwhile, the constraint conditions include a reasonable spectral data value, spectral data preprocessing method, and calibration model parameters. A unique antibody structure and specific coding and decoding method are used to achieve collaborative optimization in NIR spectroscopy. The tests on four actual near-infrared datasets, including a group of gasoline and three groups of diesel fuels, have shown that the proposed SA-MW-ISVM algorithm can significantly improve the calibration performance and thus achieve accurate prediction results. In the case of gasoline, the SA-MW-ISVM algorithm can decrease the prediction error by 44.09% compared with the common benchmark partial least square (PLS). Meanwhile, in the case of diesel fuels, the SA-MW-ISVM algorithm can decrease the prediction error of cetane number, freezing temperature, and viscosity by 9.99%, 28.69%, and 43.85%, respectively, compared with the PLS. The powerful prediction performance of the SA-MW-ISVM algorithm makes it an ideal tool for modeling near-infrared spectral data or other related application fields.

关键词： Near-infrared spectrum Support vector machine immune clone algorithm Optimization calculation Gasoline Diesel fuel

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A study on car flow organization in the loading end of heavy haul railway based on immune clonal selection algorithm

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NEURAL COMPUTING & APPLICATIONS 2019年第5期31卷 1455-1465页

作者： Jing, Yun Zhang, Zhenhua Beijing Jiaotong Univ Sch Traff & Transportat Beijing 100044 Peoples R China

Both empty and heavy car flows should be taken into consideration in the study of the Optimization Model of Car Flow Organization, in the Loading End of Heavy Haul Railway. Firstly, through the analysis of empty and heavy car flow organization in the semi-closed heavy haul railway loading end, comprehensive optimization model based on ability of station and railway can beestablished in order to obtain car flow organization scheme with minimum residencetime of both empty and heavy cars in the loading end. Secondly, immune clone algorithm is applied to solve the model in which the objective function is regarded as antibody and the constrained condition is considered as antigen to calculate the affinity, further to conduct the mutation, based on information entropy. Mutation is conducted according to the affinity. In the solving process, reproduction can be realized with the use of immune clone selection algorithm. Besides, premature convergence can be prevented by using the antibody concentration which can control the population size. Finally, simulation results show that the average search time of the proposed algorithm is reduced by 36 and 51% respectively compared with the GA and PSO.

关键词： Semi-closed heavy haul railway Comprehensive optimization model of empty and heavy cars immune clone algorithm Antibody concentration

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A Spatial Fuzzy Clustering algorithm With Kernel Metric Based on immune clone for SAR Image Segmentation

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IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 2016年第4期9卷 1640-1652页

作者： Shang, Ronghua Tian, Pingping Jiao, Licheng Stolkin, Rustam Feng, Jie Hou, Biao Zhang, Xiangrong Xidian Univ Key Lab Intelligent Percept & Image Understanding Minist Educ Xian 710071 Peoples R China Univ Birmingham Sch Mech Engn Birmingham B15 2TT W Midlands England

The fuzzy c-means (FCM) clustering algorithm has been widely used in image segmentation. However, FCM exhibits poor robustness to noise, often leading to unsatisfactory segmentations on noisy images. Additionally, the FCM algorithm is sensitive to the choice of initial cluster centers. In order to solve these problems, this paper proposes clone kernel spatial FCM (CKS_FCM), which improves segmentation performance in several ways. First, in CKS_FCM, an immune clone algorithm is used to generate the initial cluster centers, which helps prevent the algorithm from converging on local optima. Second, CKS_FCM improves the robustness to noise by incorporating spatial information into the objective function of FCM. Third, CKS_FCM uses a non-Euclidean distance based on a kernels metric, instead of the Euclidean distance conventionally used in FCM, to enhance the segmentation accuracy (SA). We present experimental results on both real and synthetic SAR images, which suggest that the proposed method can generate higher accuracy, and obtain more robustness to noise, as compared against six state-of-the-art methods from the literatures.

关键词： Fuzzy C-means (FCM) cluster immune clone algorithm kernels metric spatial information

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Optimization of part supply of assembly lines with line-integrated supermarket 14

Optimization of part supply of assembly lines with line-inte...

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IEEE International Conference on Mechatronics and Automation (ICMA)

作者： Hao, Xu Zhou, Binghai Tongji Univ Sch Mech Engn 4800 Caoan Rd Shanghai Peoples R China

ISBN: (纸本)9781509067596

Line-integrated supermarkets establish a novel parts logistics concept for improving the feeding process in mixed-model assembly line. The task assignments and cyclic part feeding problems were described. Mathematical models were built to minimize the total cost of logistic workers and part supply. Based on the theorems, the dynamic programming embedded with heuristics was adopted to obtain the optimum for small scale problems. For medium and large-scale problems, a modified immune clone selection algorithm was presented to generate satisfactory solutions. To expedite the searching process, both the simulated annealing operator and neighborhood search operator were applied to overcome the defects of the original algorithm. Furthermore, Simulation experiments of the modified algorithm and comparison with other algorithms were carried out, and the results verified the effectiveness of the proposed algorithm.

关键词： part feeding line-integrated supermarkets cyclic delivery dynamic programming immune clone algorithm

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Throughput optimization in cognitive wireless network based on clone selection algorithm

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COMPUTERS & ELECTRICAL ENGINEERING 2016年 52卷 328-336页

作者： Chai Zheng-Yi Yan Xue-yang Li Ya-lun Zhu Si-feng Tianjin Polytech Univ Sch Comp Sci & Software Engn Tianjin 300387 Peoples R China Nanyang Med Coll Publ Teaching Dept Nanyang 473003 Henan Province Peoples R China Zhoukou Normal Univ Dept Math & Informat Sci Zhoukou 466001 Peoples R China

In cognitive wireless network, throughput scheduling optimization under interferebce temperature constraints has attracted more attentions in recent years. A lot of works have been investigated on it with different scenarios. However, these solutions have either high computational complexity or relatively poor performance. Throughput scheduling is a constraint optimization problem with NP(Non-deterministic Polynomial) hard features. In this paper, we proposed an immune-clone based suboptimal algorithm to solve the problem. Suitable immune clone operators are designed such as encoding, clone, mutation and selection. The simulation results show that our proposed algorithm obtains near-optimal performance and operates with much lower computational complexity. It is suitable for slowly varying spectral environments. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Cognitive wireless network Throughput optimization immune clone algorithm Constraint optimization

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