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Your search keyword '"Sharma, Tarun Kumar"' showing total 18 results
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18 results on '"Sharma, Tarun Kumar"'

1. Soft computing approaches for prediction of specific heat capacity of hybrid nanofluids.

Author

Mathur, Priya, Gupta, Amit Kumar, Panwar, Deepak, and Sharma, Tarun Kumar

Subjects
SPECIFIC heat capacity, SOFT computing, NANOFLUIDS, NANOFLUIDICS, MACHINE learning, HEAT transfer coefficient, SPECIFIC heat, THERMAL diffusivity
Abstract

Nanofluids are thermoelectric substance with a greater thermal transmission effectiveness than traditional thermal fluids. Nanofluid's specific heat capacity (SHC) is a crucial thermophysical parameter since it controls the fluid's heat transfer coefficient. Surprisingly few research investigations have been done on the prognostic modelling of the specific heat capacity of fusion nanofluids, despite the fact that numerous experiments have been conducted on the heat transfer capacitance of blended nanofluids. This study focuses on the use of algorithms based on machine learning procedures (MLP) to estimate the SHC of blended nanofluids. Numerous numbers of hybrid nanofluids are investigated in this investigation. Total of 984 samples of hybrid nanofluids for specific heat capacity has been collected from nine experimental research papers. Various MLP techniques were utilized in this analysis, including extreme boost gradient boost regression (XGB), support vector regression augmented with a genetic algorithm (support vector regression [SVR]‐genetic algorithm [GA]), grid search optimized based gradient boost regression algorithm (GBR) (GBR‐GSO), and voting ensemble procedure (VE). The obtained correlation coefficients of the SVR‐GA, XGB, VE and GBR‐GSO models for the testing dataset are 98.43%, 96.29%, 94.4% and 96.55% respectively. The SVR‐GA model showed a better predictive accuracy relative to other ML models. This SVR‐GA anticipated model could be used for quick and reliable prediction of the SHC of blended nanofluids which reduces the burden associated with experimental measurement possible future work includes applying a machine‐learning strategy to the problem of determining the diffusivity of hybrid nanofluids. [ABSTRACT FROM AUTHOR]

Published
2024
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2. Comparative performance analysis of quantum machine learning with deep learning for diabetes prediction.

Author

Gupta, Himanshu, Varshney, Hirdesh, Sharma, Tarun Kumar, Pachauri, Nikhil, and Verma, Om Prakash

Subjects
MACHINE learning, DEEP learning, METABOLIC disorders, DIABETES, DIABETIC nephropathies, COMPARATIVE studies, HUMAN activity recognition
Abstract

Background: Diabetes, the fastest growing health emergency, has created several life-threatening challenges to public health globally. It is a metabolic disorder and triggers many other chronic diseases such as heart attack, diabetic nephropathy, brain strokes, etc. The prime objective of this work is to develop a prognosis tool based on the PIMA Indian Diabetes dataset that will help medical practitioners in reducing the lethality associated with diabetes. Methods: Based on the features present in the dataset, two prediction models have been proposed by employing deep learning (DL) and quantum machine learning (QML) techniques. The accuracy has been used to evaluate the prediction capability of these developed models. The outlier rejection, filling missing values, and normalization have been used to uplift the discriminatory performance of these models. Also, the performance of these models has been compared against state-of-the-art models. Results: The performance measures such as precision, accuracy, recall, F1 score, specificity, balanced accuracy, false detection rate, missed detection rate, and diagnostic odds ratio have been achieved as 0.90, 0.95, 0.95, 0.93, 0.95, 0.95, 0.03, 0.02, and 399.00 for DL model respectively, However for QML, these measures have been computed as 0.74, 0.86, 0.85, 0.79, 0.86, 0.86, 0.11, 0.05, and 35.89 respectively. Conclusion: The proposed DL model has a high diabetes prediction accuracy as compared with the developed QML and existing state-of-the-art models. It also uplifts the performance by 1.06% compared to reported work. However, the performance of the QML model has been found as satisfactory and comparable with existing literature. [ABSTRACT FROM AUTHOR]

Published
2022
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3. Opposition based learning ingrained shuffled frog-leaping algorithm.

Author

Sharma, Tarun Kumar and Pant, Millie

Subjects
METAHEURISTIC algorithms, MACHINE learning, STOCHASTIC processes, INFORMATION technology, ROBUST control
Abstract

Shuffled frog-leaping algorithm (SFLA) is a kind of memetic algorithm. Randomicity and determinacy, the two keywords of SFLA ensures flexibility, robustness and exchange of information effectively in SFLA. In the basic structure of SFLA, the frogs are divided into memeplexes based on their fitness values where they forage for food. In this study the opposition based learning concept is embedded into the memeplexes before the frog initiates foraging. The proposal is investigated, analyzed and compared with latest variants of SFLA on benchmark functions (unimodal and multimodal) along with a real life problem. The result analysis shows that the proposed variant performs consistently well for different types of problems considered in this study. [ABSTRACT FROM AUTHOR]

Published
2017
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4. Sentiment Analysis 'Using SVM, KNN and SVM with PCA'

Author

Verma, Praveen, Bhardwaj, Tushar, Bhatia, Abhay, Mursleen, Mohd, Kacprzyk, Janusz, Series Editor, Jain, Lakhmi C., Series Editor, Bhardwaj, Tushar, editor, Upadhyay, Himanshu, editor, Sharma, Tarun Kumar, editor, and Fernandes, Steven Lawrence, editor

Published
2023
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7. Learning-Based Model for Phishing Attack Detection

Author

Soni, Jayesh, Sirigineedi, Surya, Vutukuru, Krishna Sai, Sirigineedi, S. S. ChandanaEswari, Prabakar, Nagarajan, Upadhyay, Himanshu, Kacprzyk, Janusz, Series Editor, Jain, Lakhmi C., Series Editor, Bhardwaj, Tushar, editor, Upadhyay, Himanshu, editor, Sharma, Tarun Kumar, editor, and Fernandes, Steven Lawrence, editor

Published
2023
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9. Scrutinization of Urdu Handwritten Text Recognition with Machine Learning Approach

Author

Rashid, Dhuha, Kumar Gondhi, Naveen, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Balas, Valentina E., editor, Sinha, G. R., editor, Agarwal, Basant, editor, Sharma, Tarun Kumar, editor, Dadheech, Pankaj, editor, and Mahrishi, Mehul, editor

Published
2022
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10. Review on Analysis of Classifiers for Fake News Detection

Author

Jain, Mayank Kumar, Garg, Ritika, Gopalani, Dinesh, Meena, Yogesh Kumar, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Balas, Valentina E., editor, Sinha, G. R., editor, Agarwal, Basant, editor, Sharma, Tarun Kumar, editor, Dadheech, Pankaj, editor, and Mahrishi, Mehul, editor

Published
2022
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11. Using a Technique Based on Moment of Inertia About an Axis for the Recognition of Handwritten Digit in Devanagri Script

Author

Sharma, Diwakar, Sood, Manu, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Balas, Valentina E., editor, Sinha, G. R., editor, Agarwal, Basant, editor, Sharma, Tarun Kumar, editor, Dadheech, Pankaj, editor, and Mahrishi, Mehul, editor

Published
2022
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12. A Machine Learning Approach for Multiclass Sentiment Analysis of Twitter Data: A Review

Author

Chougule, Bhagyashree B., Patil, Ajit S., Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Balas, Valentina E., editor, Sinha, G. R., editor, Agarwal, Basant, editor, Sharma, Tarun Kumar, editor, Dadheech, Pankaj, editor, and Mahrishi, Mehul, editor

Published
2022
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13. A Case Study on Machine Learning Techniques for Plant Disease Identification

Author

Jajoo, Palika, Jain, Mayank Kumar, Jangir, Sarla, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Balas, Valentina E., editor, Sinha, G. R., editor, Agarwal, Basant, editor, Sharma, Tarun Kumar, editor, Dadheech, Pankaj, editor, and Mahrishi, Mehul, editor

Published
2022
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14. Assessment of Network Intrusion Detection System Based on Shallow and Deep Learning Approaches

Author

Meena, Gaurav, Babita, Mohbey, Krishna Kumar, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Balas, Valentina E., editor, Sinha, G. R., editor, Agarwal, Basant, editor, Sharma, Tarun Kumar, editor, Dadheech, Pankaj, editor, and Mahrishi, Mehul, editor

Published
2022
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15. Analysis of Crime Rate Prediction Using Machine Learning and Performance Analysis Using Accuracy Metrics

Author

Nawal, Meenakshi, Jain, Kusumlata, Mohapatra, Smaranika, Gupta, Sunita, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Balas, Valentina E., editor, Sinha, G. R., editor, Agarwal, Basant, editor, Sharma, Tarun Kumar, editor, Dadheech, Pankaj, editor, and Mahrishi, Mehul, editor

Published
2022
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16. Performance Analysis of Machine Learning Algorithms in Intrusion Detection and Classification

Author

Dilip, R., Samanvita, N., Pramodhini, R., Vidhya, S. G., Telkar, Bhagirathi S., Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Balas, Valentina E., editor, Sinha, G. R., editor, Agarwal, Basant, editor, Sharma, Tarun Kumar, editor, Dadheech, Pankaj, editor, and Mahrishi, Mehul, editor

Published
2022
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17. Machine Learning Based Rumor Detection on Twitter Data

Author

Maan, Manita, Jain, Mayank Kumar, Trivedi, Sainyali, Sharma, Rekha, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Balas, Valentina E., editor, Sinha, G. R., editor, Agarwal, Basant, editor, Sharma, Tarun Kumar, editor, Dadheech, Pankaj, editor, and Mahrishi, Mehul, editor

Published
2022
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18. An Investigative Analysis for IoT Based Supply Chain Coordination and Control Through Machine Learning

Author

Veerasamy, K., Sanyal, Shouvik, Almahirah, Mohammad Salameh, Saxena, Monika, Manohar Bhanushali, Mahesh, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Balas, Valentina E., editor, Sinha, G. R., editor, Agarwal, Basant, editor, Sharma, Tarun Kumar, editor, Dadheech, Pankaj, editor, and Mahrishi, Mehul, editor

Published
2022
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