Page - 218 - in Adaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources

Bibliography [web] Introductionofwaveguides. http://www.micro- waveengservices.com/waveguide.html. Accessed: 2014-12-01. [Wer92] Paul J Werbos. Approximate dynamic program- ming for real-time control and neural modeling. Handbookof intelligentcontrol: Neural, fuzzy,andadap- tiveapproaches, 15:493–525,1992. [WF05] IanHWittenandEibeFrank. DataMining: Practical machine learning tools and techniques. Morgan Kauf- mann,2005. [Whi94] DarrellWhitley. Ageneticalgorithmtutorial. Statis- tics andcomputing, 4(2):65–85,1994. [Wil09] JohnKWilliams. Reinforcementlearningofoptimal controls. In Artificial intelligence methods in the envi- ronmental sciences,pages297–327.Springer,2009. [Win99] RHS Winterton. Newton’s law of cooling. Contem- poraryPhysics, 40(3):205–212,1999. [WKK+14] A Wieckowski, P Korpas, M Krysicki, F Dughiero, M Bullo, F Bressan, and Christian Fager. Efficiency optimization for phase controlled multi-source mi- crowave oven. International Journal of Applied Elec- tromagnetics andMechanics, 44(2):235–241,2014. [WMS92] PaulJWerbos,ThomasMcAvoy,andTedSu. Neural networks, system identification, and control in the chemical process industries. Handbook of Intelligent ControlNeural, Fuzzy, and Adaptive approaches, pages 283–356,1992. [WP97] EricWalterandLucPronzato. Identificationofpara- metric models. Communications and Control Engi- neering, 1997. [wr3] IntroductionofWR-340waveguide. http://luxtem. com/wizhome/menu125.html. Accessed: 2015-03- 10. 218