Micro-fault diagnosis of electric vehicle batteries based on the evolution of battery consistency relative position
Micro-faults in Li-ion batteries are a safety hazard for battery packs, and accurately
identifying micro-faulted batteries is a complex problem to solve. In this paper, we propose a …
identifying micro-faulted batteries is a complex problem to solve. In this paper, we propose a …
[HTML][HTML] A hybrid elicit teaching learning based optimization with fuzzy c-means (ETLBO-FCM) algorithm for data clustering
Since its inception, Fuzzy c-means (FCM) technique has been widely used in data
clustering. The advantages of FCM such as balancing of individual number of cluster points …
clustering. The advantages of FCM such as balancing of individual number of cluster points …
Evolutionary improved swarm-based hybrid K-means algorithm for cluster analysis
Improvement in the quality of cluster centers and minimization of intra-cluster distance are
two most challenging areas of K-means clustering algorithm. Due to predetermined number …
two most challenging areas of K-means clustering algorithm. Due to predetermined number …
An energy-efficient routing protocol based on particle swarm clustering algorithm and inter-cluster routing algorithm for WSN
X Li, W Gang, L Zongqi… - 2013 25th Chinese control …, 2013 - ieeexplore.ieee.org
Wireless sensor network (WSN) hierarchical routing protocols meet the efficient
communication of a large-scale network. However, many of them cannot guarantee the …
communication of a large-scale network. However, many of them cannot guarantee the …
An improved swarm based hybrid k-means clustering for optimal cluster centers
Clustering is a frequently used unsupervised pattern recognition technique based on the
grouping properties of data. K-means is one of the best known, simple and efficient method …
grouping properties of data. K-means is one of the best known, simple and efficient method …
Optimizing resource allocation using multi-objective particle swarm optimization in cloud computing systems
E Alkayal - 2018 - eprints.soton.ac.uk
Allocating resources in data centers is a complex task due to their increase in size,
complexity, and consumption of power. At the same time, consumers' requirements …
complexity, and consumption of power. At the same time, consumers' requirements …
Detecting intrusive behaviors using swarm-based fuzzy clustering approach
Modern communication network relies on intrusion detection system which is an important
phenomenon to monitor the suspicious activity and avoid network traffic. Due to security …
phenomenon to monitor the suspicious activity and avoid network traffic. Due to security …
Enhancing Dynamic Wind Power Forecasting Using Cluster-Based Intelligence Swarm Optimization Technique
AS Abdo, E EL-Shafeiy, AE Hassanien - Artificial Intelligence for …, 2024 - Springer
The dynamic forecasting of wind power is critical for the efficient and reliable operation of
wind farms. Accurate predictions in wind power can enhance energy production and …
wind farms. Accurate predictions in wind power can enhance energy production and …
Optimal resource allocation based on particle swarm optimization
Abstract In Heterogeneous Networks (or HetNets), resources (both bandwidth and power)
are apportioned by the Macro Base station to multiple User Equipments (UEs) with the …
are apportioned by the Macro Base station to multiple User Equipments (UEs) with the …
Fuzzy clustering with improved swarm optimization and genetic algorithm: hybrid approach
Fuzzy c-means clustering is one of the popularly used algorithms in various diversified areas
of applications due to its ease of implementation and suitability of parameter selection, but it …
of applications due to its ease of implementation and suitability of parameter selection, but it …