Mitcheson, P.D., et al., MEMS electrostatic micropower generator for low frequency operation. 2004. 115(2-3): p. 523-529.
 Williams, C., R.B.J.s. Yates, and a.A. Physical, Analysis of a micro-electric generator for microsystems. 1996. 52(1-3): p. 8-11.
 Anton, S.R., H.A.J.S.m. Sodano, and Structures, A review of power harvesting using piezoelectric materials (2003–2006). 2007. 16(3): p. R1.
 Cook-Chennault, K.A., et al., Powering MEMS portable devices—a review of non-regenerative and regenerative power supply systems with special emphasis on piezoelectric energy harvesting systems. 2008. 17(4): p. 043001.
 Qaisi, M.I.J.A.A., Application of the harmonic balance principle to the nonlinear free vibration of beams. 1993. 40(2): p. 141-151.
 Zohoor, H. and F.J.S.I. Kakavand, Vibration of Euler–Bernoulli and Timoshenko beams in large overall motion on flying support using finite element method. 2012. 19(4): p. 1105-1116.
 Azrar, L., et al., Semi-analytical approach to the non-linear dynamic response problem of S–S and C–C beams at large vibration amplitudes Part I: general theory and application to the single mode approach to free and forced vibration analysis. 1999. 224(2): p. 183-207.
 Jahani, K., M.M. Rafiei, and R. Aghazadeh Ayoubi, Development of a laboratory system to investigate and store electrical energy from the vibrations of a piezoelectric beam %J Energy Equipment and Systems. 2016. 4(2): p. 161-168.
 Mateu, L., F.J.J.o.I.M.S. Moll, and Structures, Optimum piezoelectric bending beam structures for energy harvesting using shoe inserts. 2005. 16(10): p. 835-845.
 Anderson, T.A. and D.W. Sexton. A vibration energy harvesting sensor platform for increased industrial efficiency. In Smart Structures and Materials 2006: Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems. 2006. International Society for Optics and Photonics.
 Jiang, S., et al., Performance of a piezoelectric bimorph for scavenging vibration energy. 2005. 14(4): p. 769.
 de Almeida, B.V., R.J.J.o.A. Pavanello, and C. Mechanics, Topology Optimization of the Thickness Profile of Bimorph Piezoelectric Energy Harvesting Devices. 2019. 5(1): p. 113-127.
 Mohammadi, A., et al. Passive vibration control of a cantilever beam using shunted piezoelectric element. in 2017 5th RSI International Conference on Robotics and Mechatronics (ICRoM). 2017. IEEE.
 Roundy, S., et al., Improving power output for vibration-based energy scavengers. 2005. 4(1): p. 28-36.
 Park, J., et al., Design optimization of piezoelectric energy harvester subject to tip excitation. 2012. 26(1): p. 137-143.
 Perera, A., et al., Machine learning methods to assist energy system optimization. 2019. 243: p. 191-205.
 Nguyen, T.H., D. Nong, and K.J.E.M. Paustian, Surrogate-based multi-objective optimization of management options for agricultural landscapes using artificial neural networks. 2019. 400: p. 1-13.
 Jeon, K., et al., Development of surrogate model using CFD and deep neural networks to optimize gas detector layout. 2019. 36(3): p. 325-332.
 Mousavi, S.M. and S.M. Rahnama, Shape optimization of impingement and film cooling holes on a flat plate using a feedforward ANN and GA %J Energy Equipment and Systems. 2018. 6(3): p. 247-259.
 Palagi, L., E. Sciubba, and L.J.A.E. Tocci, A neural network approach to the combined multi-objective optimization of the thermodynamic cycle and the radial inflow turbine for Organic Rankine cycle applications. 2019. 237: p. 210-226.
 White, D.A., et al., Multiscale topology optimization using neural network surrogate models. 2019. 346: p. 1118-1135.
 Villarrubia, G., et al., Artificial neural networks used in optimization problems. 2018. 272: p. 10-16.
 Hagood, N.W., et al., Modelling of piezoelectric actuator dynamics for active structural control. 1990. 1(3): p. 327-354.
 Meitzler, A., H. Tiersten, and D.J.N.Y.I.-A. Berlincourt, IEEE standard on piezoelectricity: an american national standard. 1988.
 Park, C.-H.J.J.o.S. and vibration, Dynamics modelling of beams with shunted piezoelectric elements. 2003. 268(1): p. 115-129.
 Inman, D.J., Vibration with control. 2006: Wiley Online Library.
 MacDonald, J.J.P.R., Successive approximations by the Rayleigh-Ritz variation method. 1933. 43(10): p. 830.
 Bengio, Y.J.F. and t.i.M. Learning, Learning deep architectures for AI. 2009. 2(1): p. 1-127.
 Moré, J.J., The Levenberg-Marquardt algorithm: implementation and theory, in Numerical analysis. 1978, Springer. p. 105-116.