Moth flame optimization: theory, modifications, hybridizations, and applications
The Moth flame optimization (MFO) algorithm belongs to the swarm intelligence family and is
applied to solve complex real-world optimization problems in numerous domains. MFO and …
applied to solve complex real-world optimization problems in numerous domains. MFO and …
Binary aquila optimizer for selecting effective features from medical data: A COVID-19 case study
MH Nadimi-Shahraki, S Taghian, S Mirjalili… - Mathematics, 2022 - mdpi.com
Medical technological advancements have led to the creation of various large datasets with
numerous attributes. The presence of redundant and irrelevant features in datasets …
numerous attributes. The presence of redundant and irrelevant features in datasets …
Fuzzy‐based techniques for clustering in wireless sensor networks (WSNs): Recent advances, challenges, and future directions
A wireless sensor network (WSN) is a network of tiny sensors deployed to collect data.
These sensors are powered with batteries that have limited power. Recharging and/or …
These sensors are powered with batteries that have limited power. Recharging and/or …
Machine Learning Frameworks in Carpooling
V Veeraiah, V Talukdar, K Manikandan… - … of Research on AI and …, 2023 - igi-global.com
Due to the development in human population and their requirements, the vehicular
population on the globe is increasing day by day in the medium of public transportation. As a …
population on the globe is increasing day by day in the medium of public transportation. As a …
A bio-inspired multi-population-based adaptive backtracking search algorithm
S Nama, AK Saha - Cognitive Computation, 2022 - Springer
Backtracking search algorithm (BSA) is a nature-based optimization technique extensively
used to solve various real-world global optimization problems for the past few years. The …
used to solve various real-world global optimization problems for the past few years. The …
Density-based IFCM along with its interval valued and probabilistic extensions, and a review of intuitionistic fuzzy clustering methods
Fuzzy clustering has been useful in capturing the uncertainty present in the data during
clustering. Most of the c-Means algorithms such as FCM (Fuzzy c-Means), IFCM …
clustering. Most of the c-Means algorithms such as FCM (Fuzzy c-Means), IFCM …
Artificial intelligence enabled energy aware clustering technique for sustainable wireless communication systems
V Tirth, AH Alghtani, A Algahtani - Sustainable Energy Technologies and …, 2023 - Elsevier
Green energy is one of the effective solutions for future sustainability and finds use in
several application areas. Sustainable communication aims to decrease energy utilization of …
several application areas. Sustainable communication aims to decrease energy utilization of …
An Innovative Approach for Cluster Head Selection and Energy Optimization in Wireless Sensor Networks using Zebra Fish and Sea Horse Optimization Techniques
MK ROBERTS, P Ramasamy, F Dahan - Journal of Industrial Information …, 2024 - Elsevier
ABSTRACT In recent times, Wireless Sensor Networks (WSNs) have become an
indispensable technology across various industries, offering diverse applications and …
indispensable technology across various industries, offering diverse applications and …
Efficient Fuzzy Methodology for Congestion Control in Wireless Sensor Networks
In wireless sensor networks (WSNs), ensuring reliable and efficient communication between
nodes requires effective congestion control. This study presents an innovative approach …
nodes requires effective congestion control. This study presents an innovative approach …
Illuminating Healthcare Management: A Comprehensive Review of IoT-Enabled Chronic Disease Monitoring
Present dynamic performance reputation and technical innovations in Internet of Things
(IoT) technologies have endowed ultra-inexpensive, energy effcient, smart, and tiny IoT …
(IoT) technologies have endowed ultra-inexpensive, energy effcient, smart, and tiny IoT …