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The fact that the properties of thermoelectric materials are to be estimated with Artificial Neural Networks without production and measurement will help researchers in terms of time and cost. For this purpose, figure of merit, which is the performance value of thermoelectric materials, is estimated by Artificial Neural Networks without an experimental study. P-and n-type thermoelectric bulk samples were obtained in 19 different compositions by doping different elements into Ca2.7Ag0.3Co4O9- and Zn0.98Al0.02O-based oxide thermoelectric materials. The Seebeck coefficient, electrical resistivity and thermal diffusivity values of the bulk samples were measured from 200 degrees C to 800 degrees C with an increase rate of 100 degrees C, and figure of merit values were calculated. 7 different Artificial Neural Network models were created using 123 measured results of experimental data and the molar masses of the doping elements. In this system aiming to predict the electrical resistivity, thermal diffusivity and figure of merit values of thermoelectric materials, the average R value and accuracy rate of these values were estimated to be 94% and 80%, respectively. (c) 2020 Karabuk University. Publishing services by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Scientific and Technological Research Council of Turkey (TUBITAK)Turkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK) [115M579]; Scientific Research Projects Coordinatorship of Karabuk UniversityKarabuk University [KBU-BAP-16/1-DR-078] This study was supported by the Scientific and Technological Research Council of Turkey (TUBITAK) under Grant No. 115M579 and by the Scientific Research Projects Coordinatorship of Karabuk University under Grant No. KBU-BAP-16/1-DR-078.

Relations between effectiveness (e) and expense coefficients (ζ) were derived, and an economic simulation model was developed to simulate heat exchangers (HE) and HE networks (HEN) in all flow types for the first time. e values of parallel flow, counter flow, cross flow and all HEs under the condition of Cr = 0 were derived in terms of ζ, NTU (Number of Transfer Unit) and minimum heat capacities (Cmin). e values obtained from economic calculations were used for developing economic simulation model of HEs. Vectors including outlet temperatures and inlet temperatures of flows were obtained from static simulation to utilize in economic simulation model. Then, case studies were performed with counter flow HE and e values randomly determined in a sample HEN. Use (N), expense (P) and savings (E) of all HEs in a HEN were calculated easily by the way of linear equation systems without any complex processes, iterations, software and special hardware, in terms of both cold and hot flows properties by using economic simulation model.