A Hybrid Model of Extreme Learning Machine Based on Bat and Cuckoo Search Algorithm for Regression and Multiclass Classification

Fan, Qinwei; Fan, Tongrang

doi:10.1155/2021/4404088

Cited by 5 publications

(2 citation statements)

References 38 publications

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“…This was followed by the UVE‐SVR model with an RMSEP value of 0.32 g kg − 1 . By comparison, the prediction performance of the ELM model was unremarkable, perhaps because the ELM model had randomly generated input weights and hidden layer node parameters, which sacrificed some accuracy at the same time as improving operational efficiency 35 …”

Section: Resultsmentioning

confidence: 99%

Hydration dominates dielectric spectroscopy‐based high accuracy quantification of lactose content in cow's milk

et al. 2023

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BACKGROUND Lactose is a critical factor in the quality of milk and dairy products. Achieving high accuracy and rapid detection of lactose content in cow's milk remains a challenge. Dielectric spectroscopy has emerged as a promising tool for detecting food components. We explored the effect of lactose content on the dielectric spectra of cow's milk and we propose a rapid analytical method for the quantitative determination of lactose content in cow's milk with high accuracy based on dielectric spectra. RESULTS We obtained the dielectric spectra of 316 cow's milk samples in the frequency range 20–4500 MHz and noticed a strong negative correlation between the lactose content and the value of the dielectric loss factor (ε″) below 1500 MHz. Lactose does not affect cow's milk dielectric properties by excluded volume effect, but dominates the effect on the dielectric properties of cow's milk by hydration. The support vector regression model based on the variable importance in projection has the best prediction performance for lactose content. Its root‐mean‐square error of prediction set and residual prediction deviation is 0.29 g kg−1 and 6.968, respectively, and its prediction performance is better than that of the currently reported near‐infrared (NIR) method and other methods. CONCLUSION Despite the weak polarity of lactose molecules, its hydration is a significant factor affecting the dielectric properties of milk. The present study provides a basis for high accuracy and rapid quantitative detection of lactose in cow's milk based on dielectric spectra. © 2023 Society of Chemical Industry.

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Section: Resultsmentioning

confidence: 99%

Hydration dominates dielectric spectroscopy‐based high accuracy quantification of lactose content in cow's milk

et al. 2023

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“…They show how a simple fusion mechanism can simplify overall structure while also strengthening sophisticated fusion mechanisms. [15] described a deep learning-based method for safeguarding emotion-related codes. The researchers were able to extract acoustic features from raw audio using a SincNet layer, band-pass filtering and NN and output of those band-pass filters was then applied to input to DCNN.…”

Section: Related Workmentioning

confidence: 99%

Multimodal Sentiment Sensing and Emotion Recognition Based on Cognitive Computing Using Hidden Markov Model with Extreme Learning Machine

Verma¹,

Barnwal²,

Barve³

et al. 2022

Int. j. commun. netw. inf. secur.

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In today's competitive business environment, exponential increase of multimodal content results in a massive amount of shapeless data. Big data that is unstructured has no specific format or organisation and can take any form, including text, audio, photos, and video. Many assumptions and algorithms are generally required to recognize different emotions as per literature survey, and the main focus for emotion recognition is based on single modality, such as voice, facial expression and bio signals. This paper proposed the novel technique in multimodal sentiment sensing with emotion recognition using artificial intelligence technique. Here the audio and visual data has been collected based on social media review and classified using hidden Markov model based extreme learning machine (HMM_ExLM). The features are trained using this method. Simultaneously, these speech emotional traits are suitably maximised. The strategy of splitting areas is employed in the research for expression photographs and various weights are provided to each area to extract information. Speech as well as facial expression data are then merged using decision level fusion and speech properties of each expression in region of face are utilized to categorize. Findings of experiments show that combining features of speech and expression boosts effect greatly when compared to using either speech or expression alone. In terms of accuracy, recall, precision, and optimization level, a parametric comparison was made.

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Counter Propagation Network Based Extreme Learning Machine

Kayhan

İşeri

2022

Neural Process Lett

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A Hybrid Model of Extreme Learning Machine Based on Bat and Cuckoo Search Algorithm for Regression and Multiclass Classification

Cited by 5 publications

References 38 publications

Hydration dominates dielectric spectroscopy‐based high accuracy quantification of lactose content in cow's milk

Hydration dominates dielectric spectroscopy‐based high accuracy quantification of lactose content in cow's milk

Multimodal Sentiment Sensing and Emotion Recognition Based on Cognitive Computing Using Hidden Markov Model with Extreme Learning Machine

Counter Propagation Network Based Extreme Learning Machine

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