In this study, it was aimed to compare different normalization methods employed in model
develo** process via artificial neural networks with different sample sizes. As part of …

The penetration of renewable energies has increased during the last decades since it has
become an effective solution to the world's energy challenges. Among all renewable energy …

Normalization is a mandatory preprocessing step in time series problems to guarantee
similarity comparisons invariant to unexpected distortions in amplitude and offset. Such …

Forecasting the stock market has always been one of the challenges for stock market
participants to make more profit. Among the problems of stock price forecasting, we can …

In this study, the impact of data preprocessing on the prediction of 305-day milk yield using
neural networks were investigated with regard to the effect of different normalization …

Over the years, neural networks have shown its strength in various fields of research. There
is a vast improvement in the efficiency and effectiveness of various classification techniques …

Over the past few decades, time series forecasting (TSF) has been predominantly performed
using different artificial neural network (ANN) models. However, the performance of ANN …

The exponential increase in photovoltaic (PV) arrays installed globally, particularly given the
intermittent nature of PV generation, has emphasized the need to accurately forecast the …

Pembangunan ekonomi merupakan salah satu topik yang penting untuk dikaji karena
memberi gambaran tingkat kesejahteraan suatu negara. Akan tetapi, kebutuhan data yang …

Quasi-periodic pulsations (QPPs) with various periods that originate in the underlying
magnetohydrodynamic processes of flaring structures are detected repeatedly in solar flare …