A review on various secondary controllers and optimization techniques in automatic generation control
This article aims to provide an in-depth analysis of the recent development of various control
strategies and their implementation concerning frequency and power control in automatic …
strategies and their implementation concerning frequency and power control in automatic …
Optimizing bag-of-tasks scheduling on cloud data centers using hybrid swarm-intelligence meta-heuristic
Usually, a large number of concurrent bag-of-tasks (BoTs) application execution requests
are submitted to cloud data centers (CDCs), which needs to be optimally scheduled on the …
are submitted to cloud data centers (CDCs), which needs to be optimally scheduled on the …
Multi-criteria HPC task scheduling on IaaS cloud infrastructures using meta-heuristics
A Chhabra, G Singh, KS Kahlon - Cluster Computing, 2021 - Springer
With the rapid increase in the use of cloud computing systems, an efficient task scheduling
policy, which deals with the assignment of tasks to resources, is required to obtain maximum …
policy, which deals with the assignment of tasks to resources, is required to obtain maximum …
A novel case adaptation method based on differential evolution algorithm for disaster emergency
X Yu, C Li, WX Zhao, H Chen - Applied Soft Computing, 2020 - Elsevier
When disasters happen, time is often very urgent. Case-based reasoning (CBR) is one of
the most effective approaches to support disaster emergency management. CBR takes good …
the most effective approaches to support disaster emergency management. CBR takes good …
Scheduling scientific workflows on virtual machines using a Pareto and hypervolume based black hole optimization algorithm
F Ebadifard, SM Babamir - The Journal of Supercomputing, 2020 - Springer
The problem of workflow scheduling on virtual machines in a cloud environment is to find the
near optimal permutation of the assignment of independent computational jobs on a set of …
near optimal permutation of the assignment of independent computational jobs on a set of …
Evolutionary optimization of the area under precision-recall curve for classifying imbalanced multi-class data
Classification of imbalanced multi-class data is still so far one of the most challenging issues
in machine learning and data mining. This task becomes more serious when classes …
in machine learning and data mining. This task becomes more serious when classes …
Evolutionary algorithms for constructing an ensemble of decision trees
E Dolotov, N Zolotykh - Analysis of Images, Social Networks and Texts: 8th …, 2020 - Springer
Most decision tree induction algorithms are based on a greedy top-down recursive
partitioning strategy for tree growth. In this paper, we propose several methods for induction …
partitioning strategy for tree growth. In this paper, we propose several methods for induction …
Induction of Convolutional Decision Trees with Success-History-Based Adaptive Differential Evolution for Semantic Segmentation
Semantic segmentation is an essential process in computer vision that allows users to
differentiate objects of interest from the background of an image by assigning labels to the …
differentiate objects of interest from the background of an image by assigning labels to the …
[PDF][PDF] Computational intelligence for smart grid's flexibility: prediction, coordination, and optimal pricing
TAEH Nakabi - 2020 - erepo.uef.fi
Recent advances in artificial intelligence (AI) and machine learning (ML) are influencing
many aspects of today's society. The success of AI is a result of the availability of large …
many aspects of today's society. The success of AI is a result of the availability of large …