AI-based smart prediction of clinical disease using random forest classifier and Naive Bayes

V Jackins, S Vimal, M Kaliappan, MY Lee - The Journal of …, 2021 - Springer
Healthcare practices include collecting all kinds of patient data which would help the doctor
correctly diagnose the health condition of the patient. These data could be simple symptoms …

IoT based smart agrotech system for verification of Urban farming parameters

AK Podder, A Al Bukhari, S Islam, S Mia… - Microprocessors and …, 2021 - Elsevier
The recent seen intelligent technologies like the internet of things (IoT), computer vision etc.
facilitates farming activities and also provides flexible farm operations. On the other side …

Trend analysis using agglomerative hierarchical clustering approach for time series big data

S Pasupathi, V Shanmuganathan, K Madasamy… - The Journal of …, 2021 - Springer
Road traffic accidents are a 'global tragedy'that generates unpredictable chunks of data
having heterogeneity. To avoid this heterogeneous tragedy, we need to fraternize and …

The application of convolutional neural network model in diagnosis and nursing of MR imaging in Alzheimer's disease

X Chen, L Li, A Sharma, G Dhiman, S Vimal - … Sciences: Computational Life …, 2021 - Springer
The disease Alzheimer is an irrepressible neurologicalbrain disorder. Earlier detection and
proper treatment of Alzheimer's disease can help for brain tissue damage prevention. The …

Novel framework of GIS based automated monitoring process on environmental biodegradability and risk analysis using Internet of Things

S Gopikumar, JR Banu, YH Robinson… - Environmental …, 2021 - Elsevier
A proper method on real-time monitoring of organic biomass degradation and its evaluation
for safeguarding the ecosystem is the need of the hour. The work process designed in this …

Machine learning assisted energy optimization in smart grid for smart city applications

Z Tang, H Xie, C Du, Y Liu, OI Khalaf… - Journal of …, 2022 - World Scientific
Peer-to-peer electricity transaction is predicted to play a substantial role in research into
future power infrastructures as energy consumption in intelligent microgrids increases …

Automated classification of soil images using chaotic Henry's gas solubility optimization: Smart agricultural system

R Agarwal, NS Shekhawat, AK Luhach - Microprocessors and …, 2021 - Elsevier
The advancements in automation and image processing techniques lead to the agricultural
research a prime focus for the researchers. Soil quality prediction is one of the important …

A Deep Learning-Based Discrete-Time Markov Chain Analysis of Cognitive Radio Network for Sustainable Internet of Things in 5G-Enabled Smart City

SK Sethi, A Mahapatro - Iranian Journal of Science and Technology …, 2024 - Springer
The integration of cognitive radio-based Internet of Things devices in 5G network
environments for smart city applications necessitates effective spectrum management. The …

Modified model-agnostic meta-learning

A Pawar - 2020 IEEE International Conference on Machine …, 2020 - ieeexplore.ieee.org
Meta-learning, an idea of" learning to learn," is a machine learning field that applies a
learning algorithm to train a model for performing various tasks. This paper extends the …

Prediction and Diagnosis of Heart Diseases Using Data Mining and Artificial Intelligence-Based Algorithms

S Shaik, V Kakulapati - … Systems, Tools, and Technologies for Smart …, 2023 - igi-global.com
Prediction and diagnosis of heart disease have been a problem concerning practitioners
worldwide. It is envisaged that this investigation would aid in identifying the optimum …