Search alternatives:
using algorithms » cosine algorithm (Expand Search)
using algorithm » cosine algorithm (Expand Search)
defined » designed (Expand Search)
element » elements (Expand Search)
using algorithms » cosine algorithm (Expand Search)
using algorithm » cosine algorithm (Expand Search)
defined » designed (Expand Search)
element » elements (Expand Search)
-
1
Efficient Dynamic Cost Scheduling Algorithm for Data Batch Processing
Published 2016Get full text
doctoralThesis -
2
-
3
-
4
-
5
A multi-class discriminative motif finding algorithm for autosomal genomic data. (c2015)
Published 2016“…Our algorithm first performs a feature selection step to define differentiable SNPs. …”
Get full text
Get full text
masterThesis -
6
BUC algorithm for iceberg cubes
Published 2003“…The Uniform distribution is used as a basis for comparison. Results show that when the cube is sparse there is a correlation between the data distribution and the running time of the algorithm. …”
Get full text
Get full text
Get full text
conferenceObject -
7
Efficient Approximate Conformance Checking Using Trie Data Structures
Published 2021“…By encoding the proxy behavior using a trie data structure, we obtain a logarithmically reduced search space for alignment computation compared to a set-based representation. …”
Get full text
Get full text
Get full text
-
8
Comparative analysis of metaheuristic load balancing algorithms for efficient load balancing in cloud computing
Published 2023“…This paper provides a comparative analysis of various metaheuristic load balancing algorithms for cloud computing based on performance factors i.e., Makespan time, degree of imbalance, response time, data center processing time, flow time, and resource utilization. …”
-
9
Allocation and re-allocation of data in a grid using an adaptive genetic algorithm
Published 2006“…Allocation and re-allocation of data in a grid using an adaptive genetic algorithm. …”
Get full text
Get full text
Get full text
conferenceObject -
10
-
11
Defining quantitative rules for identifying influential researchers: Insights from mathematics domain
Published 2024“…The rules were developed for each parameter category using the Decision Tree Algorithm, which achieved an average accuracy of 70 to 75 percent for identifying awardees in mathematics domains. …”
-
12
Cryptocurrency Exchange Market Prediction and Analysis Using Data Mining and Artificial Intelligence
Published 2020“…One of the best algorithms in terms of the result is the Long Short Term Memory (LSTM) since it is based on recurrent neural networks which uses loop as a method to learn from heuristics data. …”
Get full text
-
13
-
14
A hybrid heuristic approach to optimize rule based software quality estimation models. (c2008)
Published 2008Get full text
Get full text
masterThesis -
15
Variable Selection in Data Analysis: A Synthetic Data Toolkit
Published 2024“…Variable (feature) selection plays an important role in data analysis and mathematical modeling. This paper aims to address the significant lack of formal evaluation benchmarks for feature selection algorithms (FSAs). …”
Get full text
article -
16
-
17
Using Machine Learning Algorithms to Forecast Solar Energy Power Output
Published 2025“…We focused on the first 30-min, 3-h, 6-h, 12-h, and 24-h windows to gain an appreciation of the impact of forecasting duration on the accuracy of prediction using the selected machine learning algorithms. The study results show that Random Forest outperformed all other tested algorithms. …”
-
18
Predicting Dropouts among a Homogeneous Population using a Data Mining Approach
Published 2019“…Our research relies solely on pre-college and college performance data available in the institutional database. Our research reveals that the Gradient Boosted Trees is a robust algorithm that predicts dropouts with an accuracy of 79.31% and AUC of 88.4% using only pre-enrollment data. …”
Get full text
-
19
Limiting the Collection of Ground Truth Data for Land Use and Land Cover Maps with Machine Learning Algorithms
Published 2022“…This was accomplished by (1) extracting reliable LULC information from Sentinel-2 and Landsat-8 s images, (2) generating remote sensing indices used to train ML algorithms, and (3) comparing the results with ground truth data. …”
-
20
Data reductions and combinatorial bounds for improved approximation algorithms
Published 2016“…Kernelization algorithms in the context of Parameterized Complexity are often based on a combination of data reduction rules and combinatorial insights. …”
Get full text
Get full text
Get full text
Get full text
article