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As a complex mental process, creativity requires the coordination of multiple brain regions. Previous pathological research on figural creativity has indicated that there is a mechanism by which the left side of the brain inhibits the activities of the right side of the brain during figural creative thinking, but this mechanism has not been directly(More)
—In this paper, a data-mining approach is applied to optimize combustion efficiency of a coal-fired boiler. The combustion process is complex, nonlinear, and nonstationary. A virtual testing procedure is developed to validate the results produced by the optimization methods. The developed procedure quantifies improvements in the combustion efficiency(More)
A dynamic predictive-control model of a nonlinear and temporal process is considered. Evolutionary computation and data mining algorithms are integrated for solving the model. Data-mining algorithms learn dynamic equations from process data. Evolutionary algorithms could then be applied to solve the optimization problem guided by the knowledge extracted by(More)
—In this paper, a data-mining approach is used to develop a model for optimizing the efficiency of an electric-utility boiler subject to operating constraints. Selection of process variables to optimize combustion efficiency is discussed. The selected variables are critical for control of combustion efficiency of a coal-fired boiler in the presence of(More)
This paper presents a dynamic predictive-optimization framework of a nonlinear temporal process. Data-mining (DM) and evolutionary strategy algorithms are integrated in the framework for solving the optimization model. DM algorithms learn dynamic equations from the process data. An evolutionary strategy algorithm is then applied to solve the optimization(More)
—Manufacturing companies are currently focusing on mass customization. Delivering products that meet the requirements of individual customers complicates the production process, and diminishes the benefits of the economy of scale. By exploring commonality among products, this complexity can be significantly reduced. To determine product configurations(More)
Keywords: Data mining Wind speed time series Wind power Evolutionary algorithms Markov chain Optimization a b s t r a c t Extracting important statistical patterns from wind speed time series at different time scales is of interest to wind energy industry in terms of wind turbine optimal control, wind energy dispatch/scheduling, wind energy project design(More)
—The motivation for this work is the necessity to be able to select an appropriate Cloud service provider offering for the migration of existing applications, based on cost minimization. While service providers offer pricing information publicly, and online tools allow for the calculation of cost for various Cloud offerings, the selection of which offering(More)
Bilinguals exhibit a feat to control their two languages in conversation. The neural substrates of bilingual language control have been well investigated with language switching paradigm. Yet, most of those studies have taken single lexical items (i.e., words outside a context) as the investigative tool. In the present study, we examined the neural(More)
We present a model for scheduling power generation at a wind farm, and introduce a particle swarm optimization algorithm with a small world network structure to solve the model. The solution generated by the algorithm defines the operational status of wind turbines for a scheduling horizon selected by a decision maker. Different operational scenarios are(More)