A novel approach on Cuckoo search algorithm using Gamma distribution

Roy, Sourya; Mallick, Arijit; Chowdhury, Sheli Sinha; Roy, Sangita

doi:10.1109/ecs.2015.7124948

Cited by 10 publications

(3 citation statements)

References 16 publications

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“…However, when the step size is exceeded, the search accuracy degrades, and it is straightforward to converge; when the size is smaller, the search speed decreases, and simple to slip into a local optimal. To overcome those issues in this work introduced an improved CS algorithm [37][38][39] .…”

Section: Gene Selection Using Levy Flight Cuckoo Search Optimization ...mentioning

confidence: 99%

Lung cancer diagnosis based on weighted convolutional neural network using gene data expression

Koti,

B.A

et al. 2024

Sci Rep

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Lung cancer is thought to be a genetic disease with a variety of unknown origins. Globocan2020 report tells in 2020 new cancer cases identified was 19.3 million and nearly 10.0 million died owed to cancer. GLOBOCAN envisages that the cancer cases will raised to 28.4 million in 2040. This charge is superior to the combined rates of the former generally prevalent malignancies, like breast, colorectal, and prostate cancers. For attribute selection in previous work, the information gain model was applied. Then, for lung cancer prediction, multilayer perceptron, random subspace, and sequential minimal optimization (SMO) are used. However, the total number of parameters in a multilayer perceptron can become extremely large. This is inefficient because of the duplication in such high dimensions, and SMO can become ineffective due to its calculating method and maintaining a single threshold value for prediction. To avoid these difficulties, our research presented a novel technique including Z-score normalization, levy flight cuckoo search optimization, and a weighted convolutional neural network for predicting lung cancer. This result findings show that the proposed technique is effective in precision, recall, and accuracy for the Kent Ridge Bio-Medical Dataset Repository.

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Section: Gene Selection Using Levy Flight Cuckoo Search Optimization ...mentioning

confidence: 99%

Lung cancer diagnosis based on weighted convolutional neural network using gene data expression

Koti,

B.A

et al. 2024

Sci Rep

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“…Meanwhile, an adaptive parameter is introduced to dynamically determine whether to use the three new learning strategies or Lévy flights-based strategy in the search process. In Roy et al (2015), a modified CS algorithm is introduced by using the Gamma distribution to replace the conventional Lévy distribution such that the search efficiency can be increased. Wang et al (2016b) developed an NNCS algorithm by introducing a nearest neighbor strategy.…”

Section: Introductionmentioning

confidence: 99%

A collaborative cuckoo search algorithm with modified operation mode

Yang

Huang

Zhang

et al. 2023

Engineering Applications of Artificial Intelligence

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“…Roy et al [14] managed to improve CS by using a Gamma distribution instead of original Levy distribution. When tested on 6 mathematical test functions, the Gamma based CS proved to be more accurate and efficient than the Levy CS algorithm.…”

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confidence: 99%