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Full-Text Articles in Engineering
Design Of Environment Aware Planning Heuristics For Complex Navigation Objectives, Carter D. Bailey
Design Of Environment Aware Planning Heuristics For Complex Navigation Objectives, Carter D. Bailey
All Graduate Theses and Dissertations, Spring 1920 to Summer 2023
A heuristic is the simplified approximations that helps guide a planner in deducing the best way to move forward. Heuristics are valued in many modern AI algorithms and decision-making architectures due to their ability to drastically reduce computation time. Particularly in robotics, path planning heuristics are widely leveraged to aid in navigation and exploration. As the robotic platform explores and navigates, information about the world can and should be used to augment and update the heuristic to guide solutions. Complex heuristics that can account for environmental factors, robot capabilities, and desired actions provide optimal results with little wasted exploration, but …
Improvement Opportunities In The Two-Source Energy Balance Model For Et Using Uav Imagery And Point Cloud Information, Mahyar Aboutalebi
Improvement Opportunities In The Two-Source Energy Balance Model For Et Using Uav Imagery And Point Cloud Information, Mahyar Aboutalebi
All Graduate Theses and Dissertations, Spring 1920 to Summer 2023
In recent years, satellites and unmanned aerial vehicles (UAVs) provide enormous amounts of spatially-distributed information for monitoring crop conditions by measuring crop’s reflected and emitted radiation at a distance. However, applications of high-resolution UAV imagery and its intermediate products for improving crop water use estimates are not well studied. In other words, the available approaches, methods and algorithms for determining how much water to apply for irrigation using remotely sensed data have been mostly developed at satellite spatial resolutions. High-resolution imageries that have been achieved by small UAVs open new opportunities for revisiting, re-evaluating, and revising available crop water use …
Designing Technology For Different Scales Of Irrigation Scheduling, Paolo Alexander Consalvo
Designing Technology For Different Scales Of Irrigation Scheduling, Paolo Alexander Consalvo
Undergraduate Honors Capstone Projects
Uncertainty in water availability is a significant challenge to the agriculture industry. Farmers and irrigators depend on novel uses of sensors and data to maximize water efficiency. Documented studies have demonstrated scheduling irrigation is a straightforward, deterministic means of achieving water efficiency. Irrigation scheduling uses several parameters to determine the moment of crop water stress due to available water in the soil. However, sensors and data for soil moisture and matric potential, a parameter describing water available to plants, have the potential to train machine learning algorithms to forecast water irrigation needs based on previous measurements. Satellite remote-sensing is another …
Demand Side Management In Smart Grid Using Big Data Analytics, Sidhant Chatterjee
Demand Side Management In Smart Grid Using Big Data Analytics, Sidhant Chatterjee
All Graduate Plan B and other Reports, Spring 1920 to Spring 2023
Smart Grids are the next generation electrical grid system that utilizes smart meter-ing devices and sensors to manage the grid operations. Grid management includes the prediction of load and and classification of the load patterns and consumer usage behav-iors. These predictions can be performed using machine learning methods which are often supervised. Supervised machine learning signifies that the algorithm trains the model to efficiently predict decisions based on the previously available data.
Smart grids are employed with numerous smart meters that send user statistics to a central server. The data can be accumulated and processed using data mining and machine …
Global Thermospheric Response To Geomagnetic Storms, Padmashri Suresh
Global Thermospheric Response To Geomagnetic Storms, Padmashri Suresh
All Graduate Theses and Dissertations, Spring 1920 to Summer 2023
The terrestrial atmospheric region between the altitudes of 90 km and 600 km is known as the thermosphere region. The thermosphere is continuously modulated by particle emissions and magnetic fields that originate from the sun. These fields and emissions are intensified during events known as geomagnetic storms which alter the state of the thermosphere by dumping gigawatts of energy. This energy is mostly deposited in the lower thermosphere regions of 150 km and below and can potentially have hazardous repercussions on the technological assets of mankind. These storms can disrupt radio communication systems, interrupt electric power systems, threaten the safety …
Evapotranspiration Modeling And Forecasting For Efficient Management Of Irrigation Command Areas, Roula Bachour
Evapotranspiration Modeling And Forecasting For Efficient Management Of Irrigation Command Areas, Roula Bachour
All Graduate Theses and Dissertations, Spring 1920 to Summer 2023
It has become very crucial to manage water resources to meet the needs of the growing population. In irrigation command areas, and in order to build a better plan to manage service delivery from canals and reservoirs, it is important to build appropriate knowledge of water needs on a field basis. There is often a lag between the order and delivery of water to the field. Knowledge of the crop water requirement at the field level helps the decision maker to make the right choices leading to more efficient handling of the available water. The purpose of this study was …
Multivariate Bayesian Machine Learning Regression For Operation And Management Of Multiple Reservoir, Irrigation Canal, And River Systems, Andres M. Ticlavilca
Multivariate Bayesian Machine Learning Regression For Operation And Management Of Multiple Reservoir, Irrigation Canal, And River Systems, Andres M. Ticlavilca
All Graduate Theses and Dissertations, Spring 1920 to Summer 2023
The principal objective of this dissertation is to develop Bayesian machine learning models for multiple reservoir, irrigation canal, and river system operation and management. These types of models are derived from the emerging area of machine learning theory; they are characterized by their ability to capture the underlying physics of the system simply by examination of the measured system inputs and outputs. They can be used to provide probabilistic predictions of system behavior using only historical data. The models were developed in the form of a multivariate relevance vector machine (MVRVM) that is based on a sparse Bayesian learning machine …