As a paradigm of data processing, granular computation concerns processing complex data
entities called granules, which arise from data abstraction and derivation of knowledge from …

Evolving participatory learning (ePL) modeling joins the concepts of participatory learning
and evolving fuzzy systems. It uses data streams to continuously adapt the structure and …

Volatility modeling and forecasting play a key role in asset allocation, risk management,
derivatives pricing and policy making. The purpose of this paper is to develop an evolving …

Equity assets volatility modeling and forecasting are fundamental in risk management,
portfolio construction, financial decision making and derivative pricing. The use of realized …

This paper develops and estimates an interest rate model with investor attitude factors,
which are extracted by a text mining method. First, we consider two contrastive attitudes …

Multitask modeling methods for Takagi–Sugeno–Kang (TSK) fuzzy systems exhibit better
generalization ability attributed to the utilization of the knowledge of intertask correlation …

Simultaneous flow forecasting using multi-input multi-output (MIMO) processes is an efficient
technique for accurate flow forecasting on river systems. The present study demonstrates the …

Financial interval time series (ITS) is a sequence of the highest and lowest values of
financial data such as the highest and lowest prices of assets observed at successive time …

Financial asset volatility modeling and forecasting play a central role in risk management,
portfolio selection, and derivative pricing. The increasing availability of market data at …

A river system includes the combination of flows occurring simultaneously in the main river
and its contributing tributaries. Any change in the flow condition of the river system is caused …