Application of KNN and Semi-Empirical Models for Prediction of Polycyclic Aromatic Hydrocarbons Solubility in Supercritical Carbon Dioxide

Lashkenari, Mohammad Soleimani; KhazaiePoul, Ahmad

doi:10.1080/10406638.2015.1129976

Cited by 3 publications

(1 citation statement)

References 24 publications

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“…Studies by (Saini et al, 2013) and (Jamaluddin et al, 2019) applied KNN in medical fields like urinary tract infection diagnosis classification of QRScomplex delineation and lymph node metastasis etc. KNN was applied in chemistry for the solubility of hydrocarbon (Lashkenaria and KhazaiePoulb, 2015). The study by (Preethi and Priyadarsini, 2017) reviewed the use of the KNN algorithm in medical and social networks.…”

Section: Introductionmentioning

confidence: 99%

A Comparison of KNN Algorithm and MNL Model for Mode Choice Modelling

Vinayakumar¹

2023

European Transport/Trasporti Europei

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Mode choice modelling helps to identify potential users of traffic and plays an important role in policy and decision-making by the government. With the advancement of artificial intelligence and machine learning techniques, several studies were carried out to analyse the performance of mode choice models in which the backpropagation algorithm was used. However, for faster convergence of parameters, it would be interesting to explore other efficient algorithms of machine learning as the conjugated gradient search in spite of the backpropagation algorithm. The present study adds to the literature about the performance of the K-Nearest Neighbour (KNN) algorithm in mode choice modelling and compared the KNN model with the traditional MNL model. It was unveiled that the variables, which are found significant and important in both models are the same. It is also found that the KNN model is outperforming MNL with a prediction accuracy of 73.84%.

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Section: Introductionmentioning

confidence: 99%

A Comparison of KNN Algorithm and MNL Model for Mode Choice Modelling

Vinayakumar¹

2023

European Transport/Trasporti Europei

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Applicability of statistical and machine learning–based regression algorithms in modeling of carbon dioxide emission in experimental pig barns

Basak

Kim

Shahriar

et al. 2022

Air Qual Atmos Health

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Instance Segmentation of Outdoor Sports Ground from High Spatial Resolution Remote Sensing Imagery Using the Improved Mask R-CNN

Liu¹,

Liu²,

Pu³

et al. 2019

IJG

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Aiming at the land cover (features) recognition of outdoor sports venues (football field, basketball court, tennis court and baseball field), this paper proposed a set of object recognition methods and technical flow based on Mask R-CNN. Firstly, through the preprocessing of high spatial resolution remote sensing imagery (HSRRSI) and collecting the artificial samples of outdoor sports venues, the training data set required for object recognition of land cover features was constructed. Secondly, the Mask R-CNN was used as the basic training model to be adapted to cope with outdoor sports venues. Thirdly, the recognition results were compared with the four object-oriented machine learning classification methods in eCognition®. The experiment results of effectiveness verification show that the Mask R-CNN is superior to traditional methods not only in technical procedures but also in outdoor sports venues (football field, basketball court, tennis court and baseball field) recognition results, and it achieves the precision of 0.8927, a recall of 0.9356 and an average precision of 0.9235. Finally, from the aspect of practical engineering application, using and validating the well-trained model, an empirical application experiment was performed on the HSRRSI of Xicheng and Daxing District of Beijing respectively, and the generalization ability of the trained model of Mask R-CNN was thoroughly evaluated.

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Application of KNN and Semi-Empirical Models for Prediction of Polycyclic Aromatic Hydrocarbons Solubility in Supercritical Carbon Dioxide

Cited by 3 publications

References 24 publications

A Comparison of KNN Algorithm and MNL Model for Mode Choice Modelling

A Comparison of KNN Algorithm and MNL Model for Mode Choice Modelling

Applicability of statistical and machine learning–based regression algorithms in modeling of carbon dioxide emission in experimental pig barns

Instance Segmentation of Outdoor Sports Ground from High Spatial Resolution Remote Sensing Imagery Using the Improved Mask R-CNN

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