Synergizing the enhanced RIME with fuzzy K-nearest neighbor for diagnose of pulmonary hypertension

Computers in Biology and Medicine, Год журнала: 2023, Номер 165, С. 107408 - 107408

Опубликована: Авг. 29, 2023

Язык: Английский

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A hybrid multimodal machine learning model for Detecting Alzheimer's disease

Computers in Biology and Medicine, Год журнала: 2024, Номер 170, С. 108035 - 108035

Опубликована: Фев. 3, 2024

Язык: Английский

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Super‐evolutionary mechanism and Nelder‐Mead simplex enhanced salp swarm algorithm for photovoltaic model parameter estimation

IET Renewable Power Generation, Год журнала: 2024, Номер 18(14), С. 2209 - 2237

Опубликована: Фев. 24, 2024

Abstract In the pursuit of enhancing efficiency solar cells, accurate estimation unspecified parameters in photovoltaic (PV) cell model is imperative. An advanced salp swarm algorithm called Super‐Evolutionary Nelder‐Mead Salp Swarm Algorithm (SENMSSA) proposed to achieve this objective. The SENMSSA addresses limitations SSA by incorporating a super‐evolutionary mechanism based on Gaussian‐Cauchy mutation and vertical horizontal crossover mechanism. This enhances both global optimization capabilities local search performance convergence speed algorithm. It enables secondary refinement optimum, unlocking untapped potential solution space near optimum elevating algorithm's precision exploitation higher levels. simplex method further introduced enhance accuracy. versatile that improves iteratively adjusting geometric shape (simplex) points. operates without needing derivatives, making it suitable for non‐smooth or complex objective functions. To assess efficacy SENMSSA, comparative analysis conducted against other available algorithms, namely SSA, IWOA, SCADE, LWOA, CBA, RCBA, using CEC2014 benchmark function set. Subsequently, was employed determine unknown PV under fixed conditions three different diode models. Additionally, utilized estimate commercially models (ST40, SM55, KC200GT) varying conditions. experimental results indicate study displays remarkably competitive all test cases compared algorithms. As such, we consider constitutes reliable efficient challenge parameter estimation.

Язык: Английский

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Optimized fuzzy K-nearest neighbor approach for accurate lung cancer prediction based on radial endobronchial ultrasonography

Computers in Biology and Medicine, Год журнала: 2024, Номер 171, С. 108038 - 108038

Опубликована: Фев. 17, 2024

Язык: Английский

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A Cross-Scale Transformer and Triple-View Attention Based Domain-Rectified Transfer Learning for EEG Classification in RSVP Tasks

IEEE Transactions on Neural Systems and Rehabilitation Engineering, Год журнала: 2024, Номер 32, С. 672 - 683

Опубликована: Янв. 1, 2024

Rapid serial visual presentation (RSVP)-based brain-computer interface (BCI) is a promising target detection technique by using electroencephalogram (EEG) signals. However, existing deep learning approaches seldom considered dependencies of multi-scale temporal features and discriminative multi-view spectral simultaneously, which limits the representation ability model undermine EEG classification performance. In addition, recent transfer learning-based methods generally failed to obtain transferable cross-subject invariant representations commonly ignore individual-specific information, leading poor response these limitations, we propose cross-scale Transformer triple-view attention based domain-rectified (CST-TVA-DRTL) for RSVP classification. Specially, first develop (CST) extract exploit different scales features. Then, (TVA) designed capture from triple views multi-channel time-frequency images. Finally, (DRTL) framework proposed simultaneously domain-invariant untransferable domain-specific representations, then utilize information rectify adapt data. Experimental results on two public datasets suggests that our CST-TVA-DRTL outperforms state-of-the-art in task. The source code publicly available https://github.com/ljbuaa/CST_TVA_DRTL.

Язык: Английский

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Optimizing prediction accuracy for early recurrent lumbar disc herniation with a directional mutation-guided SVM model

Computers in Biology and Medicine, Год журнала: 2024, Номер 173, С. 108297 - 108297

Опубликована: Март 14, 2024

Язык: Английский

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IRIME: Mitigating exploitation-exploration imbalance in RIME optimization for feature selection

iScience, Год журнала: 2024, Номер 27(8), С. 110561 - 110561

Опубликована: Июль 22, 2024

Rime optimization algorithm (RIME) encounters issues such as an imbalance between exploitation and exploration, susceptibility to local optima, low convergence accuracy when handling problems. This paper introduces a variant of RIME called IRIME address these drawbacks. integrates the soft besiege (SB) composite mutation strategy (CMS) restart (RS). To comprehensively validate IRIME's performance, IEEE CEC 2017 benchmark tests were conducted, comparing it against many advanced algorithms. The results indicate that performance is best. In addition, applying in four engineering problems reflects solving practical Finally, proposes binary version, bIRIME, can be applied feature selection bIRIMR performs well on 12 low-dimensional datasets 24 high-dimensional datasets. It outperforms other algorithms terms number subsets classification accuracy. conclusion, bIRIME has great potential selection.

Язык: Английский

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A multi-threshold image segmentation method based on arithmetic optimization algorithm: A real case with skin cancer dermoscopic images

Journal of Computational Design and Engineering, Год журнала: 2025, Номер unknown

Опубликована: Янв. 14, 2025

Abstract Multi-threshold image segmentation (MTIS) is a crucial technology in processing, characterized by simplicity and efficiency, the key lies selection of thresholds. However, method's time complexity will grow exponentially with number To solve this problem, an improved arithmetic optimization algorithm (ETAOA) proposed paper, optimizer for optimizing process merging appropriate Specifically, two strategies are introduced to optimize optimal threshold process: elite evolutionary strategy (EES) tracking (ETS). First, verify performance ETAOA, mechanism comparison experiments, scalability tests, experiments nine state-of-the-art peers executed based on benchmark functions CEC2014 CEC2022. After that, demonstrate feasibility ETAOA domain, were performed using ten advanced methods skin cancer dermatoscopy datasets under low high thresholds, respectively. The above experimental results show that performs outstanding compared functions. Moreover, domain has superior conditions.

Язык: Английский

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An Enhancing Diagnostic Pulmonary Diseases Diagnostic method for Differentiating Talaromycosis from Tuberculosis

iScience, Год журнала: 2025, Номер 28(2), С. 111867 - 111867

Опубликована: Янв. 22, 2025

Язык: Английский

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Embracing Open Innovation in Hospitality Management: Leveraging AI-Driven Dynamic Scheduling Systems for Complex Resource Optimization and Enhanced Guest Satisfaction

Journal of Open Innovation Technology Market and Complexity, Год журнала: 2025, Номер unknown, С. 100487 - 100487

Опубликована: Янв. 1, 2025

Язык: Английский

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