In this study, a radial basis function (RBF) neural network with three-layer feed forward architecture was developed to effectively predict the viscosity ratio of different ethylene glycol/water based nanofluids. A total of 216 experimental data involving CuO, TiO2, SiO2, and SiC nanoparticles were collected from the published literature to train and test the RBF neural network. The parameters ...

runoff estimation is one of the main challenges encountered in water and watershed management. spatial and temporal changes of factors which influence runoff due to het-erogeneity of the basins explain the complicacy of relations. artificial neural network (ann) is one of the intelligence techniques which is flexible and doesn’t call for any much physically complex processes. these networks can...

Network latency is a crucial factor affecting the quality of communications networks due to irregularity vehicular traffic. To address problem performance degradation or instability caused by in networks, this paper proposes time delay prediction algorithm, which digital twin technology employed obtain large quantity actual data for and verify autocorrelation. Subsequently, meet conditions ARMA...

Several investigations around the world have been postulated that the infant cry can be utilized to asses the infant’s status and the use of Artificial Neural Networks (ANN) has been one of the recent alternatives to classify cry signals [4,9]. A Radial Basis Function (RBF) network is implemented for infant cry classification in order to find out relevant aspects concerned with the presence of ...

There are many models that have been used to simulate the rainfall-runoff relationship. The artificial neural network (ANN) model was selected to investigate an approach of improving daily runoff forecasting accuracy in terms of data preprocessing. Singular spectrum analysis (SSA) as one data preprocessing technique was adopted to deal with the model inputs and the SSA-ANN model was developed. ...

Most of the land use change modelers have used to model binary land use change rather than multiple land use changes. As a first objective of this study, we compared two well-known LUC models, called classification and regression tree (CART) and artificial neural network (ANN) from two groups of data mining tools, global parametric and local non-parametric models, to model multiple LUCs. The ca...

accurate estimation of reference evapotranspiration plays a key role in water resources management and irrigation scheduling. the fao penman-monteith (f-p-m) is a reference method for calculation of evapotranspiration that needs temperature, humidity, wind speed and solar radiation. in many stations, it is not an easy task to measure the whole weather variables. thus, in this situation, one mus...

The forecast of fluctuations and prices is the major concern in financial markets. Thus, developing an accurate and robust forecasting decision model is critically favorable to the investors. As gold has shown a special capability to smooth inflation fluctuations, governors use gold as a price controlling lever. Thus, more information about future gold price trends will help to make the firm de...

This paper reports a comparative study between continuous hidden Markov model (CHMM) and artificial neural network (ANN) on text dependent, closed set speaker identification (SID) system with Thai language recording in office environment. Thai isolated digit 0-9 and their concatenation are used as speaking text. Mel frequency cepstral coefficients (MFCC) are selected as the studied features. Tw...