Hybridising cuckoo search algorithm for extracting the ODF maxima in spherical harmonic representation

Shehab, Mohammad; Daoud, Mohammad Sh.; Al-Mimi, Hani; Abualigah, Laith; Khader, Ahamad Tajudin

doi:10.1504/ijbic.2019.103606

Cited by 23 publications

(2 citation statements)

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“…As a result, there is no longer a need to distinguish between eggs, cuckoos, and nests. We essentially have the equivalence "egg = cuckoo = nest" as a result [34]. Algorithm 2 shows the pseudocode for AOA algorithm.…”

Section: Cuckoo Search Algorithmmentioning

confidence: 99%

Accelerated Arithmetic Optimization Algorithm by Cuckoo Search for Solving Engineering Design Problems

Hijjawi,

Alshinwan,

Khashan

et al. 2023

Processes

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Several metaheuristic algorithms have been implemented to solve global optimization issues. Nevertheless, these approaches require more enhancement to strike a suitable harmony between exploration and exploitation. Consequently, this paper proposes improving the arithmetic optimization algorithm (AOA) to solve engineering optimization issues based on the cuckoo search algorithm called AOACS. The developed approach uses cuckoo search algorithm operators to improve the ability of the exploitation operations of AOA. AOACS enhances the convergence ratio of the presented technique to find the optimum solution. The performance of the AOACS is examined using 23 benchmark functions and CEC-2019 functions to show the ability of the proposed work to solve different numerical optimization problems. The proposed AOACS is evaluated using four engineering design problems: the welded beam, the three-bar truss, the stepped cantilever beam, and the speed reducer design. Finally, the results of the proposed approach are compared with state-of-the-art approaches to prove the performance of the proposed AOACS approach. The results illustrated an outperformance of AOACS compared to other methods of performance measurement.

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Section: Cuckoo Search Algorithmmentioning

confidence: 99%

Accelerated Arithmetic Optimization Algorithm by Cuckoo Search for Solving Engineering Design Problems

Hijjawi,

Alshinwan,

Khashan

et al. 2023

Processes

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“…Furthermore, patients with Alzheimer's disease have been shown to have approximately a 30% reduction in blood flow to the brain [45]. Moreover, cerebral vascular dysfunction is a major cause of reduced cerebral blood flow, as it is described as a diminished blood vessel diameter and loss of small blood vessels [46,47]. Examples of carotid artery diseases are stenosis and occlusion.…”

Section: Introductionmentioning

confidence: 99%

Early Diagnosis of Alzheimer’s Disease Using Cerebral Catheter Angiogram Neuroimaging: A Novel Model Based on Deep Learning Approaches

Gharaibeh

Almahmoud

Ali

et al. 2021

BDCC

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Neuroimaging refers to the techniques that provide efficient information about the neural structure of the human brain, which is utilized for diagnosis, treatment, and scientific research. The problem of classifying neuroimages is one of the most important steps that are needed by medical staff to diagnose their patients early by investigating the indicators of different neuroimaging types. Early diagnosis of Alzheimer’s disease is of great importance in preventing the deterioration of the patient’s situation. In this research, a novel approach was devised based on a digital subtracted angiogram scan that provides sufficient features of a new biomarker cerebral blood flow. The used dataset was acquired from the database of K.A.U.H hospital and contains digital subtracted angiograms of participants who were diagnosed with Alzheimer’s disease, besides samples of normal controls. Since each scan included multiple frames for the left and right ICA’s, pre-processing steps were applied to make the dataset prepared for the next stages of feature extraction and classification. The multiple frames of scans transformed from real space into DCT space and averaged to remove noises. Then, the averaged image was transformed back to the real space, and both sides filtered with Meijering and concatenated in a single image. The proposed model extracts the features using different pre-trained models: InceptionV3 and DenseNet201. Then, the PCA method was utilized to select the features with 0.99 explained variance ratio, where the combination of selected features from both pre-trained models is fed into machine learning classifiers. Overall, the obtained experimental results are at least as good as other state-of-the-art approaches in the literature and more efficient according to the recent medical standards with a 99.14% level of accuracy, considering the difference in dataset samples and the used cerebral blood flow biomarker.

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Introduction of Diffusion MRI and Cuckoo Search Algorithm

Shehab¹

2019

Artificial Intelligence in Diffusion MRI

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Hybridising cuckoo search algorithm for extracting the ODF maxima in spherical harmonic representation

Cited by 23 publications

References 0 publications

Accelerated Arithmetic Optimization Algorithm by Cuckoo Search for Solving Engineering Design Problems

Accelerated Arithmetic Optimization Algorithm by Cuckoo Search for Solving Engineering Design Problems

Early Diagnosis of Alzheimer’s Disease Using Cerebral Catheter Angiogram Neuroimaging: A Novel Model Based on Deep Learning Approaches

Introduction of Diffusion MRI and Cuckoo Search Algorithm

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