Search alternatives:
modelling algorithm » scheduling algorithm (Expand Search)
learning algorithm » learning algorithms (Expand Search)
deer algorithm » search algorithm (Expand Search)
element deer » elementi per (Expand Search)
involves » involved (Expand Search)
modelling algorithm » scheduling algorithm (Expand Search)
learning algorithm » learning algorithms (Expand Search)
deer algorithm » search algorithm (Expand Search)
element deer » elementi per (Expand Search)
involves » involved (Expand Search)
-
61
Energy utilization assessment of a semi-closed greenhouse using data-driven model predictive control
Published 2021“…The proposed model predictive control framework is flexible and can be applied to other greenhouse systems by tuning the model on the new data set.…”
-
62
-
63
Integration of Artificial Intelligence in E-Procurement of the Hospitality Industry: A Case Study in the UAE
Published 2020“…Various descriptive, diagnostic, predictive, and prescriptive analysis is done on the e-procurement data. The deep learning model developed can perform thousands of routine and, repetitive tasks within a fairly short period compared to what it would take for a human being without any compromise on the quality of work. …”
Get full text
-
64
Predicting Patient ICU Readmission Using Recurrent Neural Networks With Long Short-Term Memory
Published 2025Subjects: -
65
Calibration of building model based on indoor temperature for overheating assessment using genetic algorithm: Methodology, evaluation criteria, and case study
Published 2022“…This methodology includes a variance-based sensitivity analysis to determine building parameters that significantly influence indoor air temperatures, the Multi-Objective Genetic Algorithm to calibrate different rooms simultaneously based on the significant param eters identified by the sensitivity analysis, and new evaluation criteria to achieve a high-accuracy calibrated model. …”
Get full text
Get full text
Get full text
-
66
Sentiment Analysis of the Emirati Dialect text using Ensemble Stacking Deep Learning Models
Published 2023“…For the basic machine learning algorithms, LR, NB, SVM, RF, DT, MLP, AdaBoost, GBoost, and an ensemble model of machine learning classifiers were used. …”
Get full text
-
67
-
68
Power System Transient Stability Assessment Based on Machine Learning Algorithms and Grid Topology
Published 2023“…This work employs machine learning methods to develop and test a technique for dynamic stability analysis of the mathematical model of a power system. A distinctive feature of the proposed method is the absence of a priori parameters of the power system model. …”
Get full text
article -
69
Evaluation of Aerosol Optical Depth and Aerosol Models from VIIRS Retrieval Algorithms over North China Plain
Published 2017“…The VIIRS Environmental Data Record data (VIIRS_EDR) is produced operationally by NOAA, and is based on the MODIS atmospheric correction algorithm. …”
-
70
Distributed Tree-Based Machine Learning for Short-Term Load Forecasting With Apache Spark
Published 2021“…However, with the huge increase in data size, sophisticated models have to be created which require big data platforms. …”
-
71
Delay Optimization in LoRaWAN by Employing Adaptive Scheduling Algorithm With Unsupervised Learning
Published 2023Subjects: -
72
A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method
Published 2022“…Due to a limited training dataset, an ML-based IDS generates a higher false detection ratio and encounters data imbalance issues. To deal with the data-imbalance issue, this research develops an efficient hybrid network-based IDS model (HNIDS), which is utilized using the enhanced genetic algorithm and particle swarm optimization(EGA-PSO) and improved random forest (IRF) methods. …”
-
73
-
74
Prediction of EV Charging Behavior Using Machine Learning
Published 2021“…Using data-driven tools and machine learning algorithms to learn the EV charging behavior can improve scheduling algorithms. …”
Get full text
article -
75
Intelligent Bilateral Client Selection in Federated Learning Using Game Theory
Published 2022“…Federated Learning (FL) is a novel distributed privacy-preserving learning paradigm, which enables the collaboration among several participants (e.g., Internet of Things devices) for the training of machine learning models. …”
Get full text
Get full text
Get full text
masterThesis -
76
-
77
Information reconciliation through agent controlled graph model. (c2018)
Published 2018“…Multiple models have been proposed and different techniques and data structures were used. …”
Get full text
Get full text
Get full text
masterThesis -
78
-
79
-
80