Recent advancements in data-driven process control and performance analysis could
provide the wastewater treatment industry with an opportunity to reduce costs and improve …

Though globalization, industrialization, and urbanization have escalated the economic
growth of nations, these activities have played foul on the environment. Better understanding …

Accurate predictions of time series data have motivated the researchers to develop
innovative models for water resources management. Time series data often contain both …

The need for accurate predictions of water quality in rivers has encouraged researchers to
develop new methods and to improve the predictive ability of conventional models. In recent …

Electric load forecasting (ELF) is a vital process in the planning of the electricity industry and
plays a crucial role in electric capacity scheduling and power systems management and …

Learning based on deep neural network brings new opportunities for intelligent design of
metasurfaces as well as exploration of powerful optical functionalities. Inverse design of the …

This book aims to answer two questions that are fundamental to the study of agent-based
economic models: what is agent-based computational economics and why do we need …

With the growing attention on the use of big data in the financial decision making, data
driven finance receives large attention in the recent academic literature. The study aims to …

The combination model of autoregressive integrated moving average (ARIMA) and radial
basis function network (RBFN) is used for the prediction of monthly groundwater level. The …

This paper examines the use of evolutionary programming in agent‐based modelling to
implement the theory of bounded rationality. Evolutionary programming, which draws on …