Review of machine learning approaches for biomass and soil moisture retrievals from remote sensing data
The enormous increase of remote sensing data from airborne and space-borne platforms, as
well as ground measurements has directed the attention of scientists towards new and …
well as ground measurements has directed the attention of scientists towards new and …
Modeling managed grassland biomass estimation by using multitemporal remote sensing data—A machine learning approach
I Ali, F Cawkwell, E Dwyer… - IEEE Journal of Selected …, 2016 - ieeexplore.ieee.org
More than 80% of agricultural land in Ireland is grassland, which is a major feed source for
the pasture based dairy farming and livestock industry. Many studies have been undertaken …
the pasture based dairy farming and livestock industry. Many studies have been undertaken …
Artificial neural network modeling of a CMOS differential low-noise amplifier using the Bayesian regularization algorithm
B Subburaman, V Thangaraj, V Balu, UM Pandyan… - Sensors, 2023 - mdpi.com
The purpose of this communication is to present the modeling of an Artificial Neural Network
(ANN) for a differential Complementary Metal Oxide Semiconductor (CMOS) Low-Noise …
(ANN) for a differential Complementary Metal Oxide Semiconductor (CMOS) Low-Noise …
Energy modeling and saving potential analysis using a novel extreme learning fuzzy logic network: A case study of ethylene industry
QX Zhu, C Zhang, YL He, Y Xu - Applied Energy, 2018 - Elsevier
Comprehensive energy modeling and saving potential analysis play a key role in
sustainable development of complex petrochemical industry. However, it is difficult to make …
sustainable development of complex petrochemical industry. However, it is difficult to make …
A miniaturized filter design approach using GMDH neural networks
A miniaturized microstrip low‐pass filter (LPF) has been designed and fabricated using
semicircular‐shaped resonators. The designing procedures as well as the LC equivalent …
semicircular‐shaped resonators. The designing procedures as well as the LC equivalent …
Linearization design method in class-F power amplifier using artificial neural network
This paper represents the design of a class-F power amplifier (PA), its artificial neural
network (ANN) model and a PA linearization method. The designed PA operates at 1.8 GHz …
network (ANN) model and a PA linearization method. The designed PA operates at 1.8 GHz …
Modeling of a high gain two stage pHEMT LNA using ANN with Bayesian regularization algorithm
V Thangaraj, SVJ Elangeswaran, B Subburaman… - Wireless …, 2024 - Springer
This paper presents novel way to achieve fast and accurate Artificial Neural Network (ANN)
modeling of Radio Frequency (RF) front end Low Noise Amplifier (LNA). Multilayer …
modeling of Radio Frequency (RF) front end Low Noise Amplifier (LNA). Multilayer …
[PDF][PDF] Design and modeling of RF power amplifiers with radial basis function artificial neural networks
A radial basis function (RBF) artificial neural network model for a designed high efficiency
radio frequency class-F power amplifier (PA) is presented in this paper. The presented …
radio frequency class-F power amplifier (PA) is presented in this paper. The presented …
Design of 2.4 GHz differential low noise amplifier using 0.18 μm CMOS technology
In this paper the inductive degenerated Differential Low Noise Amplifier (DLNA) is designed
with operating frequency 2.4 GHz using 0.18 μm CMOS Technology. The DLNA is biased at …
with operating frequency 2.4 GHz using 0.18 μm CMOS Technology. The DLNA is biased at …
Enhancing Predictive Modeling in Power Plants: A Comparative Analysis of ANFIS and ANN for Electrical Energy Output Estimation
C Vimala, N Jayanthi, P Vijayalakshmi… - 2024 International …, 2024 - ieeexplore.ieee.org
The main goal of this research work is to evaluate two widely known machine learning
models as the potential predictors of electrical power output in a gas turbine and steam …
models as the potential predictors of electrical power output in a gas turbine and steam …