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A combined improved dung beetle optimization and extreme learning machine framework for precise SOC estimation.

Authors : Yao, Kaihua^1,2,3 (AUTHOR); Yan, Xinyu^1,2,3 (AUTHOR) ; Mao, Xiling^1,2,3 (AUTHOR)

Source: Scientific Reports. 5/20/2025, Vol. 15 Issue 1, p1-15. 15p.

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A Scalable Hybrid Autoencoder–Extreme Learning Machine Framework for Adaptive Intrusion Detection in High-Dimensional Networks.

Authors : Kumar, Anubhav¹ (AUTHOR); Radhakrishnan, Rajamani^1,2 (AUTHOR); Sumithra, Mani^2,3 (AUTHOR)

Source: Future Internet. May2025, Vol. 17 Issue 5, p221. 18p.

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A robust chronic obstructive pulmonary disease classification model using dragonfly optimized kernel extreme learning machine.

Authors : Chitra, S.¹ (AUTHOR) ; Alqahtani, Tariq Mohammed² (AUTHOR); Alduraywish, Abdulrahman² (AUTHOR)

Source: Scientific Reports. 5/28/2025, Vol. 15 Issue 1, p1-22. 22p.

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Traffic flow prediction based on improved deep extreme learning machine.

Authors : Tian, Xiujuan¹ (AUTHOR); Wu, Shuaihu¹ (AUTHOR); Xing, Xue² (AUTHOR)

Source: Scientific Reports. 3/3/2025, Vol. 15 Issue 1, p1-27. 27p.

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Hybrid prediction method for solar photovoltaic power generation using normal cloud parrot optimization algorithm integrated with extreme learning machine.

Authors : Liu, Huachen¹ (AUTHOR); Cai, Changlong^1,2 (AUTHOR) ; Li, Pangyue¹ (AUTHOR)

Source: Scientific Reports. 2/22/2025, Vol. 15 Issue 1, p1-25. 25p.

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Applying genetic algorithm to extreme learning machine in prediction of tumbler index with principal component analysis for iron ore sintering.

Authors : Wang, Senhui¹ (AUTHOR)

Source: Scientific Reports. 2/8/2025, Vol. 15 Issue 1, p1-19. 19p.

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Academic Journal

Batch-to-Batch Optimization Control of Fed-Batch Fermentation Process Based on Recursively Updated Extreme Learning Machine Models.

Authors : Moore, Alex¹ (AUTHOR); Zhang, Jie¹ (AUTHOR)

Source: Algorithms. Feb2025, Vol. 18 Issue 2, p87. 18p.

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Academic Journal

基于改进粒子群算法和极限学习机模型的配电网物资需求预测.

Authors : 王永利¹ ; 赵中华¹ ; 张一诺¹

Source: Science Technology & Engineering. 2025, Vol. 25 Issue 15, p6410-6418. 9p.

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Academic Journal

基于改进鲸鱼算法优化极限学习机的无氟保护渣黏度预测.

Authors : 王思嘉¹ ; 曾凯^1,2,3,4 ; 陈波¹

Source: Science Technology & Engineering. 2024, Vol. 24 Issue 34, p14614-14622. 9p.

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An empirical evaluation of extreme learning machine uncertainty quantification for automated breast cancer detection.

Authors : Muduli, Debendra¹ (AUTHOR) ; Kumar, Rakesh Ranjan¹ (AUTHOR) ; Pradhan, Jitesh² (AUTHOR)

Source: Neural Computing & Applications. Apr2025, Vol. 37 Issue 12, p7909-7924. 16p.

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A combined improved dung beetle optimization and extreme learning machine framework for precise SOC estimation.

A Scalable Hybrid Autoencoder–Extreme Learning Machine Framework for Adaptive Intrusion Detection in High-Dimensional Networks.

A robust chronic obstructive pulmonary disease classification model using dragonfly optimized kernel extreme learning machine.

Traffic flow prediction based on improved deep extreme learning machine.

Hybrid prediction method for solar photovoltaic power generation using normal cloud parrot optimization algorithm integrated with extreme learning machine.

Applying genetic algorithm to extreme learning machine in prediction of tumbler index with principal component analysis for iron ore sintering.

Batch-to-Batch Optimization Control of Fed-Batch Fermentation Process Based on Recursively Updated Extreme Learning Machine Models.

基于改进粒子群算法和极限学习机模型的配电网物资需求预测.

基于改进鲸鱼算法优化极限学习机的无氟保护渣黏度预测.

An empirical evaluation of extreme learning machine uncertainty quantification for automated breast cancer detection.

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