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Showing 1 to 20 of 23 for “"spatial optimization"”.
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Spatial Optimization Techniques for School Redistricting
… decade and the availability of high-quality geospatial data, we opine that an objective treatment of the school redistricting problem by a data-driven model can assist the school board/ decision-makers by providing them with automated plans. These automated plans may serve as possible …
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High-performance evolutionary computation for scalable spatial optimization
Spatial optimization (SO) is an important and prolific field of interdisciplinary research. Spatial optimization methods seek optimal allocation or arrangement of spatial units under spatial constraints such as distance, adjacency, contiguity, partition, etc. As spatial granularity becomes finer …
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Solving large-scale spatial optimization problems in groundwater management
Item marked as restricted to the 'UIUC Users [automated]' Group (id=2) by Seth Robbins (srobbins@illinois.edu) on 2013-05-24T22:18:44Z Item is restricted until 2015-05-24T22:18:31Z
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Design and analysis of genetic algorithms for two classes of spatial optimization
… in civil and environmental engineering have spatial implications. Whether deciding on water management strategies or protecting critical infrastructure, our designs cannot be separated from the world in which they will be built and operated. Common optimization techniques, however, struggle …
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Spatial optimization of an existing, low-cost sensor network for air pollution in London
… in cost and can provide measurements with higher spatial and temporal resolution. In this paper we combine two different Gaussian process methods to optimize spatially an existing low-cost sensor network for air pollution in London. We demonstrate the practical utility of these combined algorithms …
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DeepGridMCLP: A Deep Reinforcement Learning Approach to Solve the Maximal Covering Location Problem with Facilities in Continuous Regions
… Problem (MCLP) is a classic Combinatorial Optimization Problem (COP) in spatial optimization and operations research, predominatnly used for strategic public facility placement. The model’s objective is to determine the optimal locations for a fixed number of facilities in order to serve …
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A distributed workload-aware approach to partitioning geospatial big data for cybergis analytics
… have contributed to tremendous growth of geospatial data during the past several decades. To resolve the volume and velocity of such big data, distributed system approaches have been extensively studied to partition data for scalable analytics and associated applications. However, previous …
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Augmenting Indiana's Groundwater Level Monitoring Network: Optimal Siting of Additional Wells to Address Spatial and Categorical Sampling Gaps
… relevance to groundwater recharge, and (2) spatial optimization by means of maximizing geographic distances that separate monitoring wells. Design objectives are integrated in a discrete facility location model known as the p-median problem, and solved to optimality using a mathematical …
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Adaptive Targeting: Engaging Farmers to Assess Perceptions and Improve Watershed Modeling, Optimization, and Adoption of Agricultural Conservation Practices
… Targeting conservation practices using complex optimization models has become common in the scientific community, and yet targeted results are underutilized in practice because of difficulties such as knowledge transfer and absence of a political framework for their use. For targeting to be …
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A spatial stochastic programming model for timber and core area management under risk of stand-replacing fire
… models. Past models seldom address explicit spatial forest management concerns under the influence of natural disturbances. In this research study, we employ multistage full recourse stochastic programming models to explore the challenges and advantages of building spatial optimization models …
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The economic and environmental implications of feedlot manure utilization in the Texas High Plains
… both feedlot operators and crop producers. Spatial optimization procedures were used to model the economic and environmental implications of utilizing feedlot manure in predominant cropping practices of the THP. The data for this research was constructed from the 5-year average predominant …
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Spatial Quantum Computation in Graph Optimization Problems in Transportation Applications
… potential of Quantum Computing (QC) to address spatial optimization problems in transportation systems. By leveraging the principles of quantum mechanics, this research aims to enhance the efficiency and effectiveness of transportation networks through QC-based solutions to challenges such as …
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The Influence of Environmental Disruption on Offender-Target Interactions and Criminal Activity in Emergency Scenarios
… to the criminal justice system are inherently spatial phenomena, with varying, and often disparate, implications among people and across places. The geography of crime is best understood as a complex adaptive system in which criminogenic spaces emerge from the spatial interactions of law …
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A Geographic Framework for the Optimal Placement of Interventions for Opioid Treatment Deployment in Underserved Areas (OPIOID-UA)
… location. This research seeks to investigate the spatial components of a complex system in response to a gradual onset crisis in an effort to develop a framework of spatial response. The context of the research will be the spatial system in which the health care system delivers care,; the crisis …
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An Economic Study of Carbon Capture and Storage System Design and Policy
… a model, OptimaCCS, that combines economic and spatial optimization for the integration of CCS transport, storage and injection infrastructure to minimize costs. The model solves for the lowest-cost set of pipeline routes and storage/injection sites that connect CO2 sources to the storage. It …
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Agricultural BMP Placement for Cost-effective Pollution Control at the Watershed Level
… The goal was met through development of an optimization procedure for best management practice (BMP) placement at the watershed level. The procedure combines an optimization component, written in the C++ language, with spatially variable nonpoint source (NPS) prediction and economic analysis …
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Optimizing Green Space–Type Placement to Maximize Overall Land Surface Temperature Reduction
… to these changes, we will show how the optimization model formulated herein is useful as the basis for future planning tools. Specifically, this thesis presents a mathematical model that will optimize green space–type placement and do so in a Tuscaloosa, Alabama urban census tract to …
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Improvement of simulating BMPs and LID practices in L-THIA-LID model
… (AMALGAM) method using the multilevel spatial optimization (MLSOPT) framework, was developed to optimally select and place BMPs/LID practices. The decision support tool was applied to an urban watershed near Indianapolis, Indiana. Optimization results at the hydrologic response unit …
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Addressing Genetic Pollution from Pollen Drift on a Heterogeneous Landscape
… rights in place. Although it is well known that spatial variability affects the degree of cross-contamination between GM and non-GM crops, no spatial analysis has been carried out to investigate how heterogeneity of landscapes influences the possibility for GM and non-GM crops to coexist. We aim …
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An optimization of baseball fielder positioning using SEAM
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2024-09-16 without embargo terms
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