Browsing by Author "Kilic, H."
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Conference Object Citation Count: 0Artificial agent society simulations in an encounter-based normative action environment(Ieee, 2007) Kilic, H.The purpose of the study is to investigate potential relationship between agents' socialness and society's behavior predictability in an encounter-based normative action environment. For this purpose, we proposed a hypothesis and tested it against different simulation setups in the context of classical single source shortest path problem. By the end of simulations, it is observed that the hypothesis holds for both norm internalization and spreading measures when the agents in society have some degree of autonomy. That means for our setup, we conclude that lower degree of socialness results in lower behavioral predictability of the society when the agents have some degree of autonomy.Article Citation Count: 16On the usage of artificial neural networks in chlorine control applications for water distribution networks with high quality water(Iwa Publishing, 2011) Soyupak, S.; Kilic, H.; Karadirek, I. E.; Muhammetoglu, H.Artificial neural network (ANN) methodology has found some recent applications as efficient control tools for satisfying free residual chlorine (FRC) levels at critical locations of water distribution systems. This particular research was started to critically investigate the potential and applicability of the ANN approach as a tool for controlling FRC levels for complex water distribution systems supplied by high quality waters with low chlorine demands. Konyaalti Water Distribution System, operated by Antalya Water and Wastewater Administration, Turkey, has been selected as a pilot. The selected system is complex in structure and supplied with raw water which has high quality and low decay rate of chlorine. The study has shown that ANN models with high predictive power and precision can be developed for such water distribution systems, and that these models can be utilized for forecasting purposes. The data for model building should be collected properly if the developed ANN models are to be utilized as control instruments for FRC levels within water distribution systems.