Nature-inspired algorithms for wireless sensor networks: A comprehensive survey
A Singh, S Sharma, J Singh - Computer Science Review, 2021 - Elsevier
In order to solve the critical issues in Wireless Sensor Networks (WSNs), with concern for
limited sensor lifetime, nature-inspired algorithms are emerging as a suitable method …
limited sensor lifetime, nature-inspired algorithms are emerging as a suitable method …
Strategies based on various aspects of clustering in wireless sensor networks using classical, optimization and machine learning techniques: Review, taxonomy …
J Amutha, S Sharma, SK Sharma - Computer Science Review, 2021 - Elsevier
Abstract Wireless Sensor Networks (WSNs) have attracted various academic researchers,
engineers, science, and technology communities. This attraction is due to their broad …
engineers, science, and technology communities. This attraction is due to their broad …
Deep learning and data fusion to estimate surface soil moisture from multi-sensor satellite images
We propose a new architecture based on a fully connected feed-forward Artificial Neural
Network (ANN) model to estimate surface soil moisture from satellite images on a large …
Network (ANN) model to estimate surface soil moisture from satellite images on a large …
HDL-IDS: a hybrid deep learning architecture for intrusion detection in the Internet of Vehicles
Internet of Vehicles (IoV) is an application of the Internet of Things (IoT) network that
connects smart vehicles to the internet, and vehicles with each other. With the emergence of …
connects smart vehicles to the internet, and vehicles with each other. With the emergence of …
AutoML-ID: Automated machine learning model for intrusion detection using wireless sensor network
Momentous increase in the popularity of explainable machine learning models coupled with
the dramatic increase in the use of synthetic data facilitates us to develop a cost-efficient …
the dramatic increase in the use of synthetic data facilitates us to develop a cost-efficient …
An energy efficient cluster based hybrid optimization algorithm with static sink and mobile sink node for Wireless Sensor Networks
J Amutha, S Sharma, SK Sharma - Expert Systems with Applications, 2022 - Elsevier
In wireless sensor networks (WSNs), energy efficiency is a significant design challenge that
can be resolved by clustering and routing approaches. They are considered as Non …
can be resolved by clustering and routing approaches. They are considered as Non …
AutoML-GWL: Automated machine learning model for the prediction of groundwater level
Predicting groundwater levels is pivotal in curbing overexploitation and ensuring effective
water resource governance. However, groundwater level prediction is intricate, driven by …
water resource governance. However, groundwater level prediction is intricate, driven by …
A Gaussian process regression approach to predict the k-barrier coverage probability for intrusion detection in wireless sensor networks
Abstract Sensors in a Wireless Sensor Network (WSN) sense, process, and transmit
information simultaneously. They mainly find applications in agriculture monitoring …
information simultaneously. They mainly find applications in agriculture monitoring …
A deep learning approach to predict the number of k-barriers for intrusion detection over a circular region using wireless sensor networks
Abstract Wireless Sensor Networks (WSNs) is a promising technology with enormous
applications in almost every walk of life. One of the crucial applications of WSNs is intrusion …
applications in almost every walk of life. One of the crucial applications of WSNs is intrusion …
A systematic review of localization in WSN: Machine learning and optimization‐based approaches
P Yadav, SC Sharma - International journal of communication …, 2023 - Wiley Online Library
In recent years, wireless sensor networks (WSNs) have been widely used in various
applications. The localization problem has been identified as one of the biggest problems …
applications. The localization problem has been identified as one of the biggest problems …