Titlebook: Nanostructured Materials for Electronic Nose; Nirav J. Joshi,Sachin Navale Book 2024 The Editor(s) (if applicable) and The Author(s), unde

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Electronic Nose Using Machine Learning Techniques,nce machine learning models like XGBoost, GBDT, etc. work. As well, basic models like SVM, RF, ANN, etc. can be used to analyze data obtained from above-mentioned sectors. We will also discuss how machine learning algorithms are helpful optimum output and discuss how in various fields they are used.

critique

Nanostructured Metal Oxide for High-Performance Electronic Nose,eshness of food, and diagnosing diseases. Furthermore, we have discussed the potential challenges and prospects for metal oxide-based E-noses. It is evident from our review that nanostructured metal oxides hold great promise as potential candidates for assembling E-noses that exhibit excellent gas-sensing capabilities.

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Capitulate

Trends in the Development of Electronic Noses Based on Carbon Nanotubes, the present work, recent studies on CNT-based electronic noses are comparably summarized. Also, the developments in some CNT-based composite materials for electronic noses are reviewed. Finally, the challenges and future perspectives are discussed to comprehend the operational utilization of CNT-based materials.

Osteons

Nirav J. Joshi,Sachin NavaleHighlights recent advances of electronic-nose (E-nose) technology based on advanced nanostructured materials.Includes information on each aspect of novel materials and their sensing mechanisms.Discuss

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978-981-97-1392-9The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor

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Advanced Structured Materialshttp://image.papertrans.cn/n/image/661013.jpg

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https://doi.org/10.1007/978-981-97-1390-52D Materials; Cancer Diagnosis; Metal Oxide Nanostructures; Machine Learning (ML); E-Nose; Carbon Nanotub