A feature selection model for software defect prediction using binary Rao optimization algorithm
K Thirumoorthy - Applied Soft Computing, 2022 - Elsevier
In this digital world, using software has become an important part of daily life and business.
The software must be rigorously tested in order to avert a financial crisis. The defect-free …
The software must be rigorously tested in order to avert a financial crisis. The defect-free …
Identifying the most influential parameters in predicting lighting energy consumption in office buildings using data-driven method
S Norouziasl, A Jafari - Journal of Building Engineering, 2023 - Elsevier
Predicting building energy consumption is a necessary step in energy management, energy
saving and optimization. Recently, data-driven models have shown promising performance …
saving and optimization. Recently, data-driven models have shown promising performance …
Evaluation of three feature dimension reduction techniques for machine learning-based crop yield prediction models
Machine learning (ML) has been widely used worldwide to develop crop yield forecasting
models. However, it is still challenging to identify the most critical features from a dataset …
models. However, it is still challenging to identify the most critical features from a dataset …
A novel machine learning approach for rice yield estimation
Artificial Intelligence is quickly emerging as a technological solution for the agriculture
industry to surmount its classical challenges. Artificial Intelligence is facilitating farmers to …
industry to surmount its classical challenges. Artificial Intelligence is facilitating farmers to …
ONOS flood defender: An intelligent approach to mitigate DDoS attack in SDN
N Aslam, S Srivastava, MM Gore - Transactions on Emerging …, 2022 - Wiley Online Library
Abstract Software‐Defined Networking (SDN) has made its place in the networks as new
technology. SDN's programmable behavior enables it to change behavior on the fly …
technology. SDN's programmable behavior enables it to change behavior on the fly …
Enhancing big data feature selection using a hybrid correlation-based feature selection
This study proposes an alternate data extraction method that combines three well-known
feature selection methods for handling large and problematic datasets: the correlation …
feature selection methods for handling large and problematic datasets: the correlation …
Cloud based ensemble machine learning approach for smart detection of epileptic seizures using higher order spectral analysis
K Singh, J Malhotra - Physical and Engineering Sciences in Medicine, 2021 - Springer
The present paper proposes a smart framework for detection of epileptic seizures using the
concepts of IoT technologies, cloud computing and machine learning. This framework …
concepts of IoT technologies, cloud computing and machine learning. This framework …
Information gain based feature selection for improved textual sentiment analysis
M Ramasamy, A Meena Kowshalya - Wireless Personal Communications, 2022 - Springer
Sentiment analysis or opinion mining is the process of mining the emotion from a given text.
It is a text mining technique that effectively measures the inclination of public opinions and …
It is a text mining technique that effectively measures the inclination of public opinions and …
Accurate prediction of calving in dairy cows by applying feature engineering and machine learning
JA Vázquez-Diosdado, J Gruhier… - Preventive Veterinary …, 2023 - Elsevier
Prediction of calving is key to dairy cow management. Current trends of increasing herd
sizes globally can directly impact the time that farmers spend monitoring individual animals …
sizes globally can directly impact the time that farmers spend monitoring individual animals …
Impact of sleep and training on game performance and injury in division-1 women's Basketball Amidst the Pandemic
We investigated the impact of sleep and training load of Division-1 women's basketball
players on their game performance and injury prediction using machine learning algorithms …
players on their game performance and injury prediction using machine learning algorithms …