Search alternatives:
evolution algorithm » evolutionary algorithms (Expand Search)
coding algorithm » cosine algorithm (Expand Search), colony algorithm (Expand Search), scheduling algorithm (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
time evolution » linear evolution (Expand Search)
evolution algorithm » evolutionary algorithms (Expand Search)
coding algorithm » cosine algorithm (Expand Search), colony algorithm (Expand Search), scheduling algorithm (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
time evolution » linear evolution (Expand Search)
-
1
Adaptive bias simulated evolution algorithm for placement
Published 2001“…This parameter has major impact on the algorithm run-time and the quality of the solution subspace searched. …”
Get full text
Get full text
article -
2
Simulated evolution algorithm for multiobjective VLSI netlist bi-partitioning
Published 2003“…In this paper the Simulated Evolution algorithm (SimE) is engineered to solve the optimization problem of multi-objective VLSI netlist bi-partitioning. …”
Get full text
Get full text
article -
3
-
4
Simulated evolution for timing and low power VLSI standard cell placement
Published 2020Get full text
article -
5
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 -
6
CNN and HEVC Video Coding Features for Static Video Summarization
Published 2022Get full text
article -
7
-
8
-
9
Parallelization of Stochastic Evolution
Published 2006“…In this work, the development of parallel algorithms for Stochastic Evolution, applied on multi-objective VLSI cell-placement problem is presented. …”
Get full text
masterThesis -
10
-
11
UniBFS: A novel uniform-solution-driven binary feature selection algorithm for high-dimensional data
Published 2024“…UniBFS exploits the inherent characteristic of binary algorithms-binary coding-to search the entire problem space for identifying relevant features while avoiding irrelevant ones. …”
-
12
Auto-indexing Arabic texts based on association rule data mining. (c2015)
Published 2015“…Our model denotes extracting new relevant words by relating those chosen by the previous classical methods, to new words using data mining rules. …”
Get full text
Get full text
masterThesis -
13
-
14
Estimating Construction Project Duration Using a Machine Learning Algorithm
Published 2024Get full text
Get full text
Get full text
masterThesis -
15
Fast force-directed/simulated evolution hybrid for multiobjective VLSI cell placement
Published 2004“…In this work, a fast hybrid algorithm is designed to address this problem. The algorithm employs simulated evolution (SE), an iterative search heuristic that comprises three steps: evaluation, selection and allocation. …”
Get full text
Get full text
article -
16
A simulated evolution approach to task-matching and scheduling in heterogeneous computing environments
Published 2020“…The performance of SE is compared with a genetic algorithm approach for the same problem with respect to the quality of solutions generated, and timing requirements of the algorithms. r 2003 Elsevier Science Ltd. …”
Get full text
article -
17
-
18
Automatic Video Summarization Using HEVC and CNN Features
Published 2022Get full text
doctoralThesis -
19
Optimizing Document Classification: Unleashing the Power of Genetic Algorithms
Published 2023“…Additionally, our proposed model optimizes the features using a genetic algorithm. Optimal feature selection performances a crucial role in this domain, enhancing the overall accuracy of the document classification system while reducing the time complexity associated with selecting the most relevant features from this large-dimensional space. …”
-
20
Allocating data to distributed-memory multiprocessors by genetic algorithms
Published 2016“…We present three genetic algorithms (GAs) for allocating irregular data sets to multiprocessors. …”
Get full text
Get full text
Get full text
article