Search alternatives:
using algorithms » cosine algorithm (Expand Search)
making algorithm » cosine algorithm (Expand Search)
deer algorithm » search algorithm (Expand Search)
image making » image sharing (Expand Search)
element deer » elementi per (Expand Search)
using algorithms » cosine algorithm (Expand Search)
making algorithm » cosine algorithm (Expand Search)
deer algorithm » search algorithm (Expand Search)
image making » image sharing (Expand Search)
element deer » elementi per (Expand Search)
-
1
An image processing and genetic algorithm-based approach for the detection of melanoma in patients
Published 2018“…The second phase classifies lesions using a Genetic Algorithm. Our technique shows a significant improvement over other well-known algorithms and proves to be more stable on both training and testing data.…”
Get full text
Get full text
Get full text
Get full text
article -
2
An enhanced k-means clustering algorithm for pattern discovery in healthcare data
Published 2015“…Data mining approaches offer the methodology and technology to transform these heterogeneous data into meaningful information for decision making. …”
Get full text
Get full text
Get full text
Get full text
article -
3
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
-
4
-
5
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 -
6
-
7
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
-
8
-
9
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 -
10
-
11
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. …”
-
12
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
-
13
A Novel Steganography Technique for Digital Images Using the Least Significant Bit Substitution Method
Published 2022“…<p>Communication has become a lot easier in this era of technology, development of high-speed computer networks, and the inexpensive uses of Internet. Therefore, data transmission has become vulnerable to and unsafe from different external attacks. …”
-
14
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. …”
-
15
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 -
16
Distributed dimension reduction algorithms for widely dispersed data
Published 2002Get full text
Get full text
Get full text
conferenceObject -
17
A genetic algorithm for testable data path synthesis
Published 2017Get full text
Get full text
Get full text
Get full text
conferenceObject -
18
A neural networks algorithm for data path synthesis
Published 2003“…This paper presents a deterministic parallel algorithm to solve the data path allocation problem in high-level synthesis. …”
Get full text
Get full text
Get full text
article -
19
-
20