Search alternatives:
experimental data » experimental _ (Expand Search)
method algorithm » mould algorithm (Expand Search)
using algorithms » cosine algorithm (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
experimental data » experimental _ (Expand Search)
method algorithm » mould algorithm (Expand Search)
using algorithms » cosine algorithm (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
-
21
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 -
22
A Novel Genetic Algorithm Optimized Adversarial Attack in Federated Learning for Android-Based Mobile Systems
Published 2025“…<p dir="ltr">Federated Learning (FL) is gaining traction in Android-based consumer electronics, enabling collaborative model training across decentralized devices while preserving data privacy. However, the increasing adoption of FL in these devices exposes them to adversarial attacks that can compromise user data and device security. …”
-
23
Stochastic Search Algorithms for Exam Scheduling
Published 2007“…Then, we empirically compare the three proposed algorithms and FESP using realistic data. Our experimental results show that SA and GA produce good exam schedules that are better than those of FESP heuristic procedure. …”
Get full text
Get full text
article -
24
Bee Colony Algorithm for Proctors Assignment.
Published 2015“…We apply the Bee Colony algorithm to previously published data. Experimental results show good solutions that maximize the preferences of proctors while preserving the fairness of the workload given to proctors. …”
Get full text
Get full text
Get full text
article -
25
Data Redundancy Management in Connected Environments
Published 2020“…., building) equipped with sensors that produce and exchange raw data. Although the sensed data is considered to contain useful and valuable information, yet it might include various inconsistencies such as data redundancies, anomalies, and missing values. …”
Get full text
Get full text
Get full text
Get full text
conferenceObject -
26
-
27
Parameter identification of PV solar cells and modules using bio dynamics grasshopper optimization algorithm
Published 2024“…The study evaluates the BDGOA by applying it to identify unknown parameters of five solar modules. The algorithm's effectiveness is demonstrated through the extraction of parameters for RTC France, PWP201, SM55, KC200GT, and SW255 models, validated against experimental data under diverse conditions. …”
-
28
-
29
Graph Contraction for Mapping Data on Parallel Computers
Published 1994“…The mapping solution for the original problem is obtained by a straightforward interpolation. We then present experimental results on using contracted graphs as inputs to two physical optimization methods; namely, genetic algorithm and simulated annealing. …”
Get full text
Get full text
Get full text
article -
30
Mapping realistic data sets on parallel computers
Published 1993“…The GC algorithm allows large-scale mapping to become efficient, especially when slow but high-quality mappers are used.…”
Get full text
Get full text
Get full text
Get full text
conferenceObject -
31
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
-
32
-
33
-
34
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. …”
-
35
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
-
36
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. …”
-
37
A Tabu Search algorithm for mapping data to multicomputers. (c1997)
Published 1997Get full text
Get full text
masterThesis -
38
Three-phase simulated annealing algorithms for exam scheduling
Published 2003“…We empirically compare 3PSA with a 4-phase clustering-based heuristic algorithm using realistic data. Our experimental results show that 3PSA produces good exam schedules, which are better than those of the clustering heuristic procedure.…”
Get full text
Get full text
Get full text
Get full text
conferenceObject -
39
Data redundancy management for leaf-edges in connected environments
Published 2022“…Experimental results highlight the performance and accuracy of our solution in detecting and eliminating edge data redundancies.…”
Get full text
Get full text
Get full text
Get full text
article -
40
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