Search alternatives:
using algorithm » cosine algorithm (Expand Search)
system » systems (Expand Search)
element » elements (Expand Search)
update » updated (Expand Search)
using algorithm » cosine algorithm (Expand Search)
system » systems (Expand Search)
element » elements (Expand Search)
update » updated (Expand Search)
-
121
Transmission Line Fault Location Using Unsynchronized Measurements
Published 2013Get full text
doctoralThesis -
122
The use of multi-task learning in cybersecurity applications: a systematic literature review
Published 2024“…<p dir="ltr">Cybersecurity is crucial in today’s interconnected world, as digital technologies are increasingly used in various sectors. The risk of cyberattacks targeting financial, military, and political systems has increased due to the wide use of technology. …”
-
123
-
124
-
125
-
126
Clustering/partitioning algorithms and comparative analysis
Published 1989Get full text
Get full text
masterThesis -
127
A Non-convex Economic Load Dispatch Using Hybrid Salp Swarm Algorithm
Published 2021“…In this paper, the economic load dispatch (ELD) problem with valve point effect is tackled using a hybridization between salp swarm algorithm (SSA) as a population-based algorithm and β-hill climbing optimizer as a single point-based algorithm. …”
Get full text
-
128
-
129
Genetic Algorithm Based Simultaneous Eigenvalue Placement Of Power Systems
Published 2020“…This paper demonstrates the use of genetic algorithms to design a single output feedback control law for the simultaneous eigenvalue placement of a power system running over a wide range of operating conditions. …”
Get full text
article -
130
-
131
A multi-class discriminative motif finding algorithm for autosomal genomic data. (c2015)
Published 2016“…New technologies, such as Next-Generation Genome Sequencing, can now provide huge amounts of data in little time. Big initiatives such as the International Hapmap Project and the 1000 Genome project are making use of these technologies to provide the scientific community with a detailed genetic reference from different populations. …”
Get full text
Get full text
masterThesis -
132
-
133
Optimal scheduling algorithm for residential building distributed energy source systems using Levy flight and chaos-assisted artificial rabbits optimizer
Published 2023“…The impact of various electricity prices for obtaining energy from the primary grid on the system’s operating costs is examined. The efficiency of LFCARO is compared with other algorithms, and the results show that LFCARO performs better than other algorithms. …”
-
134
-
135
Capturing outline of fonts using genetic algorithm and splines
Published 2001“…Some examples are given to show the results obtained from the algorithm…”
Get full text
Get full text
article -
136
-
137
Prediction of pressure gradient for oil-water flow: A comprehensive analysis on the performance of machine learning algorithms
Published 2022“…<p dir="ltr">Pressure gradient (PG) in liquid-liquid flow is one of the key components to design an energy-efficient transportation system for wellbores. This study aims to develop five robust machine learning (ML) algorithms and their fusions for a wide range of flow patterns (FP) regimes. …”
-
138
A novel IoT intrusion detection framework using Decisive Red Fox optimization and descriptive back propagated radial basis function models
Published 2024“…The novelty of this work is, a recently developed DRF optimization methodology incorporated with the machine learning algorithm is utilized for maximizing the security level of IoT systems. …”
-
139
PILE-UP FREE PARAMETER ESTIMATION AND DIGITAL ONLINE PEAK LOCALIZATION ALGORITHMS FOR GAMMA RAY SPECTROSCOPY
Published 2020“…A fast waveform sampling facility has been recently developed and integrated into the VAX-based data acquisition system at the Energy Research Laboratory (ERL). …”
Get full text
article -
140
Unsupervised outlier detection in multidimensional data
Published 2022“…<p>Detection and removal of outliers in a dataset is a fundamental preprocessing task without which the analysis of the data can be misleading. Furthermore, the existence of anomalies in the data can heavily degrade the performance of machine learning algorithms. …”