A survey of neuromorphic computing and neural networks in hardware
Neuromorphic computing has come to refer to a variety of brain-inspired computers, devices,
and models that contrast the pervasive von Neumann computer architecture. This …
and models that contrast the pervasive von Neumann computer architecture. This …
Biodiesel production from Calophyllum inophyllum-Ceiba pentandra oil mixture: Optimization and characterization
In this study, a novel modeling approach (artificial neural networks (ANN) and ant colony
optimization (ACO)) was used to optimize the process variables for alkaline-catalyzed …
optimization (ACO)) was used to optimize the process variables for alkaline-catalyzed …
Mango fruit sortation system using neural network and computer vision
EH Yossy, J Pranata, T Wijaya, H Hermawan… - Procedia computer …, 2017 - Elsevier
Mango has different colors and sizes that indicate the level of maturity. Mango maturity level
often makes farmers confused when choosing a mango that has a good maturity …
often makes farmers confused when choosing a mango that has a good maturity …
[HTML][HTML] An artificial intelligence approach to model and optimize biodiesel production from used cooking oil using CaO incorporated zeolite catalyst
The current work investigated the possibility of employing chicken eggshell-zeolite
composite as a cheap and recyclable heterogeneous catalyst for used cooking oil (UCO) …
composite as a cheap and recyclable heterogeneous catalyst for used cooking oil (UCO) …
[PDF][PDF] An algorithm for training multilayer perceptron (MLP) for Image reconstruction using neural network without overfitting
Recently, back propagation neural network (BPNN) has been applied successfully in many
areas with excellent generalization results, for example, rule extraction, classification and …
areas with excellent generalization results, for example, rule extraction, classification and …
[HTML][HTML] Application of fuzzy–Neuro to model weather parameter variability impacts on electrical load based on long-term forecasting
D Ali, M Yohanna, PM Ijasini, MB Garkida - Alexandria engineering journal, 2018 - Elsevier
Long-term load forecasting provides vital information about future load and it helps the
power industries to make decision regarding electrical energy generation and delivery. In …
power industries to make decision regarding electrical energy generation and delivery. In …
Artificial neural networks model design of Lorenz chaotic system for EEG pattern recognition and prediction
L Zhang - 2017 IEEE Life Sciences Conference (LSC), 2017 - ieeexplore.ieee.org
This paper presents the preliminary work of a multidisciplinary brain research program. The
goal of this research program is to generate accurate and effective signals for non-invasive …
goal of this research program is to generate accurate and effective signals for non-invasive …
Enabling energy-efficient DNN training on hybrid GPU-FPGA accelerators
DNN training consumes orders of magnitude more energy than inference and requires
innovative use of accelerators to improve energy-efficiency. However, despite having …
innovative use of accelerators to improve energy-efficiency. However, despite having …
[PDF][PDF] Image reconstruction using multi layer perceptron (mlp) and support vector machine (svm) classifier and study of classification accuracy
Support Vector Machine (SVM) and back-propagation neural network (BPNN) has been
applied successfully in many areas, for example, rule extraction, classification and …
applied successfully in many areas, for example, rule extraction, classification and …
Design and implementation of multilayer perceptron with on-chip learning in virtex-e
S Murugan, KP Lakshmi, J Sundar, K MathiVathani - AASRI Procedia, 2014 - Elsevier
Due to advancements in technology, many integrated circuits are fabricated to develop an
artificial system that could perform “intelligent” tasks similar to those performed by the human …
artificial system that could perform “intelligent” tasks similar to those performed by the human …