We develop a new nonparametric method to reconstruct the Equation of State (EoS) Neutron Star with multimessenger data. As an universal function approximator, Feed-Forward Neural Network (FFNN) one hidden layer and sigmoidal activation can approximately fit any continuous function. Thus we are able implement FFNN representation EoSs. This is validated by its capabilities fitting theoretical EoS...

This paper presents a relative humidity predictions using feedforward artificial neural network (FFNN). Relative humidity values obtained from weather records for Malaysia are used in training the FFNNs. The prediction of the relative humidity is in terms of Sun shine ration and cloud cover. However, three statistical parameters, namely, mean absolute percentage error, MAPE, mean bias error, MB...

Vibration based techniques of structural damage detection using model updating method, are computationally expensive for large-scale structures. In this study, after locating precisely the eventual damage of a structure using modal strain energy based index (MSEBI), To efficiently reduce the computational cost of model updating during the optimization process of damage severity detection, the M...

This study presents a machine learning (ML)/artificial intelligence (AI)-based perspective to reliably predict and enhance the treatment efficiency of landfill leachate by classical-Fenton (c-Fenton) photo-Fenton (p-Fenton) processes. experiment also sought lower costs evaluating impact using different numbers UV-c (254 nm) lamps during p-Fenton processes, as well develop sustainable process de...

evaporation is one of the most important components of hydrologic cycle.accurate estimation of this parameter is used for studies such as water balance,irrigation system design, and water resource management. in order to estimate theevaporation, direct measurement methods or physical and empirical models can beused. using direct methods require installing meteorological stations andinstruments ...

In this thesis, artificial neural networks (ANNs) are used for prediction of financial and macroeconomic time series. ANNs build internal models of the problem and are therefore suited for fields in which accurate mathematical models cannot be formed, e.g. meteorology and economics. Feedforward neural networks (FFNNs), often trained with backpropagation, constitute a common type of ANNs. Howeve...

The purpose of this study is to analyze the performance of Back propagation algorithm with changing training patterns and the second momentum term in feed forward neural networks. This analysis is conducted on 250 different words of three small letters from the English alphabet. These words are presented to two vertical segmentation programs which are designed in MATLAB and based on portions (1...

The character recognition is the major important part in the area of document analysis. Character Recognition could be evaluated on printed text and handwritten text. Printed texture could be from a good quality image. In this research work, we implemented in the OCR approach to improve the recognition of character with Classification approach. We work on filtration techniques to improve the pi...