This dissertation focuses on introducing and developing Machine Learning techniques in complex systems such as renewable energy systems, supply chain networks and quantum optimization. In the third chapter we investigate multivariate forecasting and reconstruction of the missing characteristics of ocean waves based on information from nearby wave sensors. Moreover, we design a new case study based on ocean wave measurement stations along the east coast of the United States and explore the wave feature selection concept. In the fourth chapter, we introduce parallel structures to tackle the above-mentioned tasks.
