RETRACTED ARTICLE: A study on car flow organization in the loading end of heavy haul railway based on immune clonal selection algorithm

Jing, Yun; Zhang, Zhenhua

doi:10.1007/s00521-018-3396-2

Cited by 12 publications

(3 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…FCSA Input: N (the size of the population), n (the number of antibodies selected for cloning), n c (the number of clones), m (the degree of variation), c (Rac1 protein activity threshold) Output: the best antibody (1) Begin (2) Randomly generate N antibodies to form the initial candidate set (3) while not meet algorithm termination conditions do (4) Calculate the affinity Aff ab i of each antibody for antigen in the candidate set and record antibody survival time T ab i (5) Sort the antibodies in the candidate set according to their affinity, and put the best n antibodies into the antibody set Ab s (6) forab i inAb s (7) Update the value of the appropriate memory of antibody ab i : S ab i + � 1. See CLONING METHOD, clone antibody ab i according to n c and Aff ab i , and put all antibodies obtained by cloning into antibody set Ab c (8) end for (9) forab i inAb c (10) See VARIATION METHOD, according to the degree of variation m and the affinity of the antibody for the antigen Aff ab i to mutate ab i (11) if antibody ab i is a variant antibody (12) e ab i survival time T ab i � 0, e appropriate memory intensity S ab i � 1 (13) end if (14) end for (15) Select the N antibodies with the highest antigen affinity in Ab c and Ab to replace the N antibodies in Ab (16) See FORGETTING METHOD, calculate the Rac1 protein activity of each antibody in Ab according to the ratio of T ab i to S ab i (17) if antibody ab i Rac1 protein activity > threshold (18) forget the antibody ab i (19)…”

Section: Resultsmentioning

confidence: 99%

“…Kim and Bentley [3] used a dynamic cloning selection algorithm to solve the problem of anomaly detection in the changing environment. In recent years, the cloning selection algorithm inspired by biological immunity has also been widely used in power industries such as power plant addressing [4], electricity price prediction [5], hybrid shop scheduling [6], car flow organization [7] and other power industries, playing an active role in the improvement of clustering [8] as well as machine learning algorithms [9][10][11].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Improved Clonal Selection Algorithm Based on Biological Forgetting Mechanism

et al. 2020

View full text Add to dashboard Cite

The antibody candidate set generated by the clonal selection algorithm has only a small number of antibodies with high antigen affinity to obtain high-frequency mutations. Among other antibodies, some low-affinity antibodies are replaced by new antibodies to participate in the next clonal selection. A large number of antibodies with high affinity make it difficult to participate in clonal selection and exist in antibody concentration for a long time. This part of inactive antibody forms a “black hole” of the antibody set, which is difficult to remove and update in a timely manner, thus affecting the speed at which the algorithm approximates the optimal solution. Inspired by the mechanism of biological forgetting, an improved clonal selection algorithm is proposed to solve this problem. It aims to use the abstract mechanism of biological forgetting to eliminate antibodies that cannot actively participate in high-frequency mutations in the antibody candidate set and to improve the problem of insufficient diversity of antibodies in the clonal selection algorithm, which is prone to fall into the local optimal. Compared with the existing clonal selection and genetic algorithms, the experiment and time complexity analysis show that the algorithm has good optimization efficiency and stability.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Improved Clonal Selection Algorithm Based on Biological Forgetting Mechanism

et al. 2020

View full text Add to dashboard Cite

show abstract

“…Jing and Zhang have proposed a immune clone selection algorithm for Optimization Model of Car Flow Organization. Besides, premature convergence can be prevented by using the antibody concentration which can control the population size [14].…”

mentioning

confidence: 99%