The paper offers a synthesis of several widely used estimation methods in survey sampling from a rather personal point of view. The methods which will be discussed include post-stratification estimation, generalized regression estimation and calibration estimation. The presentation puts emphasis...

This paper intends to investigate whether the turning points exist between tax revenue, gross domestic product, government expenditure, and gross domestic saving towards Malaysia's total external debt. The researcher implements the adaptive neuro-fuzzy inference system model to forecast the...

Estimation of missing precipitation records is one of the most important tasks in hydro-logical and environmental study. The efficiency of hydrological and environmental models is sub-ject to the completeness of precipitation data. This study compared some basic soft computing techniques,...

Neural networks are well suited to predict future results of time series for various data types. This paper proposes a hybrid neural network model to describe the results of the database of the New York Stock Exchange (NYSE). This hybrid model brings together a self organizing map (SOM) with a...

Although appealing from a theoretical point of view, empirical assessments of dynamic portfolio optimizations in a mean-variance framework often fail to reach the high expectations set forth by analytical evaluations. A major reason for this shortfall is the imprecise estimation of asset moments...

Accurate forecasting of changes in stock market indices can provide financial managers and individual investors with strategically valuable information. However, predicting the closing prices of stock indices remains a challenging task because stock price movements are characterized by high...

Accurate prediction of stock market behavior is a challenging issue for financial forecasting. Artificial neural networks, such as multilayer perceptron have been established as better approximation and classification models for this domain. This study proposes a chemical reaction optimization...

The use of advanced predictive techniques and reasoning models has greatly assisted clinicians in improving the diagnosis, prognosis, and treatment of diabetes. Although numerous studies have focused on the relationship between abnormal blood glucose levels and diabetes, few have focused on the...