Operations Research, Systems Engineering and Industrial Engineering Commons^™

Cluster-Based Chained Transfer Learning For Energy Forecasting With Big Data, Yifang Tian

Electronic Thesis and Dissertation Repository

Smart meter popularity has resulted in the ability to collect big energy data and has created opportunities for large-scale energy forecasting. Machine Learning (ML) techniques commonly used for forecasting, such as neural networks, involve computationally intensive training typically with data from a single building/group to predict future consumption for that same building/group. With hundreds of thousands of smart meters, it becomes impractical or even infeasible to individually train a model for each meter. Consequently, this paper proposes Cluster-Based Chained Transfer Learning (CBCTL), an approach for building neural network-based models for many meters by taking advantage of already trained models through …

Development Of An Autonomous Robotic Mushroom Harvester, Nikita Alexeevich Kuchinskiy

Electronic Thesis and Dissertation Repository

The process of development of a new robot is one of the modern technological arts. This process involves multiple complex steps and recursive approach. In this project, a solution for automatic harvesting of mushrooms is developed. In order to design an effective solution, it is necessary to explore and take into consideration the limitations of grasping very soft and fragile objects (particularly mushrooms). We will elaborate several strategies of picking and analyze each strategy to formulate the design requirements, develop a solution, and finally, evaluate the efficiency of the proposed solution in actual farm conditions for real mushrooms. The mushroom …

Automated Image Interpretation For Science Autonomy In Robotic Planetary Exploration, Raymond Francis

Electronic Thesis and Dissertation Repository

Advances in the capabilities of robotic planetary exploration missions have increased the wealth of scientific data they produce, presenting challenges for mission science and operations imposed by the limits of interplanetary radio communications. These data budget pressures can be relieved by increased robotic autonomy, both for onboard operations tasks and for decision- making in response to science data.

This thesis presents new techniques in automated image interpretation for natural scenes of relevance to planetary science and exploration, and elaborates autonomy scenarios under which they could be used to extend the reach and performance of exploration missions on planetary surfaces.

Two …