Search alternatives:
modelling algorithm » scheduling algorithm (Expand Search)
mining algorithm » cosine algorithm (Expand Search)
method algorithm » mould algorithm (Expand Search)
element » elements (Expand Search)
modelling algorithm » scheduling algorithm (Expand Search)
mining algorithm » cosine algorithm (Expand Search)
method algorithm » mould algorithm (Expand Search)
element » elements (Expand Search)
-
81
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
-
82
-
83
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 -
84
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. …”
-
85
Design of adaptive arrays based on element position perturbations
Published 1993“…The main advantage of using this technique over the other commonly used methods is that the amplitudes and phases of the array elements can be used mainly to steer the main beam towards the desired signal. …”
Get full text
Get full text
article -
86
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. …”
-
87
Delay Optimization in LoRaWAN by Employing Adaptive Scheduling Algorithm With Unsupervised Learning
Published 2023Subjects: -
88
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. …”
-
89
-
90
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 -
91
-
92
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 -
93
-
94
-
95
Defining quantitative rules for identifying influential researchers: Insights from mathematics domain
Published 2024“…This selection process was guided by an importance score, that was derived after assessing its influence on the model's performance in the classification of data pertaining to both awardees and non awardees. …”
-
96
-
97
A depth-controlled and energy-efficient routing protocol for underwater wireless sensor networks
Published 2022“…The proposed energy-efficient routing protocol is based on an enhanced genetic algorithm and data fusion technique. In the proposed energy-efficient routing protocol, an existing genetic algorithm is enhanced by adding an encoding strategy, a crossover procedure, and an improved mutation operation that helps determine the nodes. …”
-
98
-
99
-
100
Estimation of the methanol loss in the gas hydrate prevention unit using the artificial neural networks: Investigating the effect of training algorithm on the model accuracy
Published 2023“…Adjusting the weight and bias of the ANN model using an optimization algorithm is known as the training process. …”