Search Results - subject:"Genetic Algorithm"

Whole life cost methods for computer systems

Bradley, Malcolm - 1998

This thesis provides an analysis of cost of ownership issues and techniques, andprovides the supporting data to enable future system designers to make rationaldecisions on design options. It represents the experience gained whilst collectingcost and cost relationship data in the Rolls-Royce...

Persistent link: https://www.econbiz.de/10009461190

Accounting for Additional Heterogeneity: A Theoretic Extension of an Extant Economic Model

Barney, Bradley John 1980- - 2007

-category logit models, and running the genetic algorithm. …

Persistent link: https://www.econbiz.de/10009456722

ON A CLASS OF HYBRID SYSTEMS VIA A NOVEL APPROACH FOR REAL-CODED GENETIC ALGORITHM WITH HYBRID SELECTION

ARUMUGAM, M. SENTHIL; RAO, M. V. C. - In: International Journal of Information Technology & … 06 (2007) 02, pp. 315-332

A real-coded genetic algorithm (RGA) approach with hybrid selection method to compute the optimal control and cost …

Persistent link: https://www.econbiz.de/10004977388

Determination of acceptable operating cost level of nuclear energy for Turkey's power system

Yildirim, Mehmet; Erkan, Kadir - In: Energy 32 (2007) 2, pp. 128-136

the construction and operating costs and the reliability constraints. Adaptive simulated annealing genetic algorithm …

Persistent link: https://www.econbiz.de/10010809387

Effect of inflow forecast accuracy and operating time horizon in optimizing irrigation releases

Sivapragasam, C.; Vasudevan, G.; Vincent, P. - In: Water Resources Management 21 (2007) 6, pp. 933-945

In this study, application of Genetic Algorithms (GA) is demonstrated to optimize reservoir release policies to meet irrigation demand and storage requirements. As it is commonly recognized that accuracy of inflow forecast and operating time horizon affects the optimal policies, a...

Persistent link: https://www.econbiz.de/10010794352

Waste load allocation modeling with fuzzy goals; simulation-optimization approach

Saadatpour, M.; Afshar, A. - In: Water Resources Management 21 (2007) 7, pp. 1207-1224

linear and/or nonlinear and nondecreasing and/or nonincreasing membership functions. QUAL2E and Classified Population Genetic … Algorithm (CPGA) were coupled to develop the optimum strategy resulting in maximum value of the minimum nonzero membership …

Persistent link: https://www.econbiz.de/10010794698

A COLLISION-AVOIDING MECHANISM BASED ON A THEORY OF MIND

ZANLUNGO, FRANCESCO - In: Advances in Complex Systems (ACS) 10 (2007) su, pp. 363-371

We develop a collision-avoiding mechanism for a system of individual agents (pedestrians) that move in a crowd trying to reach their different goal points. The agents avoid collisions on the basis of a model of the other agents' behavior, a "theory of mind," which is realized at different levels...

Persistent link: https://www.econbiz.de/10005047463

AN INTELLIGENT CLASSIFICATION METHOD IN BANK CUSTOMER RELATIONSHIP MANAGEMENT

ZHANG, JIE; LU, JIE; ZHANG, GUANGQUAN - In: New Mathematics and Natural Computation (NMNC) 03 (2007) 01, pp. 111-121

genetic algorithm. The result is then combined with customer static data to give reasonable customer segmentation supported by …

Persistent link: https://www.econbiz.de/10005080813

Design Exploration Using A Shape Grammar With A Genetic Algorithm

Chouchoulas, Orestes; Day, Alan - In: Open House International 32 (2007) 2, pp. 26-35

Although the idea of linking a shape grammar to a genetic algorithm is not new, this paper proposes a novel way of …'s stylistic agenda. A genetic algorithm can then be used to take these designs and develop them into a much richer set of … genetic algorithm can evolve new designs which exhibit the best features of previous generations. The designer is then …

Persistent link: https://www.econbiz.de/10014964550

Evolutionary Algorithms in a Support Vector Regression Financial Forecasting Model : Case of Continuous Ant Colony Optimization Algorithms

Hong, Wei-Chiang - 2007

Traditional time series forecasting models are difficult to capture the nonlinear patterns. Support vector regression (SVR) has been successfully used to solve nonlinear regression and times series problems. However, parameters determination for a SVR model is competent to the forecasting...

Persistent link: https://www.econbiz.de/10014049169