Mixed kernel based extreme learning machine for electric load forecasting
Short term electric load forecasting, as an important tool in the electricity market, plays a
critical role in the management of electric systems. Proposing an accuracy and optimization …
critical role in the management of electric systems. Proposing an accuracy and optimization …
Machine learning approach for predicting electrical features of Schottky structures with graphene and ZnTiO3 nanostructures doped in PVP interfacial layer
In this research, for some different Schottky type structures with and without a
nanocomposite interfacial layer, the current–voltage (I–V) characteristics have been …
nanocomposite interfacial layer, the current–voltage (I–V) characteristics have been …
Evaluation and exploration of machine learning and convolutional neural network classifiers in detection of lung cancer from microarray gene—a paradigm shift
Microarray gene expression-based detection and classification of medical conditions have
been prominent in research studies over the past few decades. However, extracting relevant …
been prominent in research studies over the past few decades. However, extracting relevant …
Credit risk evaluation: a comprehensive study
To date, there has been relatively little research in the field of credit risk analysis that
compares all of the well known statistical, optimization technique (heuristic methods) and …
compares all of the well known statistical, optimization technique (heuristic methods) and …
Long‐term precipitation analysis and estimation of precipitation concentration index using three support vector machine methods
M Gocic, S Shamshirband, Z Razak… - Advances in …, 2016 - Wiley Online Library
The monthly precipitation data from 29 stations in Serbia during the period of 1946–2012
were considered. Precipitation trends were calculated using linear regression method …
were considered. Precipitation trends were calculated using linear regression method …
Appraisal of the support vector machine to forecast residential heating demand for the District Heating System based on the monthly overall natural gas consumption
Abstract DHS (District Heating System) is one of the most efficient technologies which has
been used to meet residential thermal demand. In this study, the most accurate forecasting …
been used to meet residential thermal demand. In this study, the most accurate forecasting …
A decade of machine learning in lithium-ion battery state estimation: a systematic review
Lithium-ion batteries are central to contemporary energy storage systems, yet the precise
estimation of critical states—state of charge (SOC), state of health (SOH), and remaining …
estimation of critical states—state of charge (SOC), state of health (SOH), and remaining …
Precipitation concentration index management by adaptive neuro-fuzzy methodology
This paper reconsiders the precipitation concentration index (PCI) in Serbia using
precipitation measurements such as the mean winter precipitation amount, annual total …
precipitation measurements such as the mean winter precipitation amount, annual total …
Metaheuristic integrated machine learning classification of colon cancer using STFT LASSO and EHO feature extraction from microarray gene expressions
The microarray gene expression data poses a tremendous challenge due to their curse of
dimensionality problem. The sheer volume of features far surpasses available samples …
dimensionality problem. The sheer volume of features far surpasses available samples …
Photonic Kernel machine learning for ultrafast spectral analysis
We introduce photonic kernel machines, a scheme for ultrafast spectral analysis of noisy
radio-frequency signals from single-shot optical intensity measurements. The approach …
radio-frequency signals from single-shot optical intensity measurements. The approach …